Integrative multi-omics analyses to identify the genetic and functional mechanisms underlying ovarian cancer risk regions.

To identify credible causal risk variants (CCVs) associated with different histotypes of epithelial ovarian cancer (EOC), we performed genome-wide association analysis for 470,825 genotyped and 10,163,797 imputed SNPs in 25,981 EOC cases and 105,724 controls of European origin. We identified five histotype-specific EOC risk regions (p value <5 × 10-8) and confirmed previously reported associations for 27 risk regions. Conditional analyses identified an additional 11 signals independent of the primary signal at six risk regions (p value <10-5). Fine mapping identified 4,008 CCVs in these regions, of which 1,452 CCVs were located in ovarian cancer-related chromatin marks with significant enrichment in active enhancers, active promoters, and active regions for CCVs from each EOC histotype. Transcriptome-wide association and colocalization analyses across histotypes using tissue-specific and cross-tissue datasets identified 86 candidate susceptibility genes in known EOC risk regions and 32 genes in 23 additional genomic regions that may represent novel EOC risk loci (false discovery rate <0.05). Finally, by integrating genome-wide HiChIP interactome analysis with transcriptome-wide association study (TWAS), variant effect predictor, transcription factor ChIP-seq, and motifbreakR data, we identified candidate gene-CCV interactions at each locus. This included risk loci where TWAS identified one or more candidate susceptibility genes (e.g., HOXD-AS2, HOXD8, and HOXD3 at 2q31) and other loci where no candidate gene was identified (e.g., MYC and PVT1 at 8q24) by TWAS. In summary, this study describes a functional framework and provides a greater understanding of the biological significance of risk alleles and candidate gene targets at EOC susceptibility loci identified by a genome-wide association study.

Urinary biomonitoring of glyphosate exposure among male farmers and nonfarmers in the Biomarkers of Exposure and Effect in Agriculture (BEEA) study.

Glyphosate is the most widely applied herbicide worldwide. Glyphosate biomonitoring data are limited for agricultural settings. We measured urinary glyphosate concentrations and assessed exposure determinants in the Biomarkers of Exposure and Effect in Agriculture (BEEA) study. We selected four groups of BEEA participants based on self-reported pesticide exposure: recently exposed farmers with occupational glyphosate use in the last 7 days (n = 98), farmers with high lifetime glyphosate use (>80th percentile) but no use in the last 7 days (n = 70), farming controls with minimal lifetime use (n = 100), and nonfarming controls with no occupational pesticide exposures and no recent home/garden glyphosate use (n = 100). Glyphosate was quantified in first morning void urine using ion chromatography isotope-dilution tandem mass spectrometry. We estimated associations between urinary glyphosate concentrations and potential determinants using multivariable linear regression. Glyphosate was detected (≥0.2 µg/L) in urine of most farmers with recent (91 %) and high lifetime (93 %) use, as well as farming (88 %) and nonfarming (81 %) controls; geometric mean concentrations were 0.89, 0.59, 0.46, and 0.39 µg/L (0.79, 0.51, 0.42, and 0.37 µg/g creatinine), respectively. Compared with both control groups, urinary glyphosate concentrations were significantly elevated among recently exposed farmers (P < 0.0001), particularly those who used glyphosate in the previous day [vs. nonfarming controls; geometric mean ratio (GMR) = 5.46; 95 % confidence interval (CI): 3.75, 7.93]. Concentrations among high lifetime exposed farmers were also elevated (P < 0.01 vs. nonfarming controls). Among recently exposed farmers, glyphosate concentrations were higher among those not wearing gloves when applying glyphosate (GMR = 1.91; 95 % CI: 1.17, 3.11), not wearing long-sleeved shirts when mixing/loading glyphosate (GMR = 2.00; 95 % CI: 1.04, 3.86), applying glyphosate exclusively using broadcast/boom sprayers (vs. hand sprayer only; GMR = 1.70; 95 % CI: 1.00, 2.92), and applying glyphosate to crops (vs. non-crop; GMR = 1.72; 95 % CI: 1.04, 2.84). Both farmers and nonfarmers are exposed to glyphosate, with recency of occupational glyphosate use being the strongest determinant of urinary glyphosate concentrations. Continued biomonitoring of glyphosate in various settings is warranted.

Urinary mutagenicity and bladder cancer risk in northern New England.

The etiology of bladder cancer among never smokers without occupational or environmental exposure to established urothelial carcinogens remains unclear. Urinary mutagenicity is an integrative measure that reflects recent exposure to genotoxic agents. Here, we investigated its potential association with bladder cancer in rural northern New England. We analyzed 156 bladder cancer cases and 247 cancer-free controls from a large population-based case-control study conducted in Maine, New Hampshire, and Vermont. Overnight urine samples were deconjugated enzymatically and the extracted organics were assessed for mutagenicity using the plate-incorporation Ames assay with the Salmonella frameshift strain YG1041 + S9. Logistic regression was used to estimate the odds ratios (OR) and 95% confidence intervals (CI) of bladder cancer in relation to having mutagenic versus nonmutagenic urine, adjusted for age, sex, and state, and stratified by smoking status (never, former, and current). We found evidence for an association between having mutagenic urine and increased bladder cancer risk among never smokers (OR = 3.8, 95% CI: 1.3-11.2) but not among former or current smokers. Risk could not be estimated among current smokers because nearly all cases and controls had mutagenic urine. Urinary mutagenicity among never-smoking controls could not be explained by recent exposure to established occupational and environmental mutagenic bladder carcinogens evaluated in our study. Our findings suggest that among never smokers, urinary mutagenicity potentially reflects genotoxic exposure profiles relevant to bladder carcinogenesis. Future studies are needed to replicate our findings and identify compounds and their sources that influence bladder cancer risk.

Pesticide use and inflammatory bowel disease in licensed pesticide applicators and spouses in the Agricultural Health Study.

BACKGROUND: Pesticide exposure has been linked to some autoimmune diseases and colorectal cancer, possibly via alteration of gut microbiota or other mechanisms. While pesticides have been linked to gut dysbiosis and inflammation in animal models, few epidemiologic studies have examined pesticides in relation to inflammatory bowel disease (IBD). OBJECTIVES: We evaluated use of pesticides and incident IBD in 68,480 eligible pesticide applicators and spouses enrolled in the Agricultural Health Study. METHODS: Self-reported IBD cases were identified from follow-up questionnaires between enrollment (1993-1997) and 2022. We evaluated IBD incidence in relation to self-reported ever use of 50 pesticides among applicators and spouses. We also explored associations with intensity-weighted lifetime days (IWLD) of pesticide use among male applicators. Covariate-adjusted hazard ratios (HR) and 95% confidence intervals (CI) were calculated using Cox regression. RESULTS: We identified 454 IBD cases, including 227 among male applicators. In analyses with applicators and spouses combined, associations were positive (HR > 1.2) for ever vs. never use of five organochlorine insecticides, three organophosphate insecticides, one fungicide, and five herbicides. HRs were highest for dieldrin (HR = 1.59, 95%CI: 1.03, 2.44), toxaphene (HR = 1.61, 95%CI: 1.17, 2.21), parathion (HR = 1.42, 95%CI: 1.03, 1.95), and terbufos (HR = 1.53, 95%CI: 1.19, 1.96). We had limited power in many IWLD of pesticide use analyses and did not find clear evidence of exposure-response trends; however, we observed elevated HRs in all tertiles of IWLD use of terbufos compared to never use (T1 vs. never use HR = 1.52, 95%CI: 1.03, 2.24; T2 vs. never use HR = 1.53, 95%CI: 1.04, 2.26; T3 vs. never use HR = 1.51, 95%CI: 1.03, 2.23). CONCLUSIONS: Exposure to specific pesticides was associated with elevated hazards of IBD. These findings may have public health importance given the widespread use of pesticides and the limited number of known modifiable environmental risk factors for IBD.

An Updated Evaluation of Atrazine-Cancer Incidence Associations among Pesticide Applicators in the Agricultural Health Study Cohort.

BACKGROUND: Atrazine is a common agricultural herbicide in the United States. Few epidemiologic studies have evaluated cancer risks. Previous analyses within the Agricultural Health Study (AHS) have found some evidence of associations with cancer at some sites. OBJECTIVE: We updated exposure information, incident cases, and follow-up time to assess the associations between atrazine use and cancer at specific sites in the AHS. METHODS: Information about lifetime pesticide use was reported at enrollment (1993-1997) and follow-up (1999-2005). Among 53,562 pesticide applicators in North Carolina and Iowa, we identified 8,915 incident cases through cancer registry linkages through 2014 (North Carolina)/2017 (Iowa). We used Poisson regression to evaluate the association between ever/never and intensity-weighted lifetime days of atrazine use and incident cancer risk controlling for several confounders. We also evaluated lagged exposures and age-stratified risk. RESULTS: Approximately 71.2% of applicators reported ever using atrazine, which was associated with lung cancer [rate ratios (RR)=1.24; 95% confidence interval (CI): 1.04, 1.46]. Aggressive prostate cancer risk was increased in the highest quartile (RRQ4=1.20; 95% CI: 0.95, 1.52; p-trend=0.19), particularly among those <60 years old (RRQ4=3.04; 95% CI: 1.61, 5.75; p-trend<0.001; p-interaction=0.04). Among applicators <50 years of age, ever-atrazine use was associated with non-Hodgkin lymphoma (NHL) (RR=2.43; 95% CI: 1.10, 5.38; p-interaction=0.60). For soft tissue sarcoma, there was an elevated risk in the highest tertile of exposure (RRT3: 2.54; 95% CI: 0.97, 6.62; p-trend=0.31). In analyses with exposure lagged by 25 years, there was an elevated risk of pharyngeal (RRT3=3.04; 95% CI: 1.45, 6.36; p-trend=0.07) and kidney (RRQ4=1.62; 95% CI: 1.15, 2.29; p-trend<0.005) cancers. DISCUSSION: We observed suggestive associations with some malignancies in overall, age-specific, and lagged analyses. Associations with aggressive prostate cancer and NHL were apparent among those diagnosed at younger ages and with cancers of the pharynx and kidney, and soft tissue sarcomas were observed in lagged analyses. Further work is needed to confirm these observed associations and elucidate potential underlying mechanisms. https://doi.org/10.1289/EHP13684.

Ingested nitrate and nitrite and end-stage renal disease in licensed pesticide applicators and spouses in the Agricultural Health Study.

BACKGROUND: Nitrate and nitrite ingestion has been linked to kidney cancer, possibly via the endogenous formation of carcinogenic N-nitroso compounds. These exposures might also contribute to end-stage renal disease (ESRD). OBJECTIVES: We investigated associations of drinking water nitrate and dietary nitrate and nitrite intakes (total and by food type) with incident ESRD in the Agricultural Health Study. We also explored modifying effects of vitamin C and heme iron intake, which may affect endogenous nitrosation. METHODS: We performed complete case analyses among private pesticide applicators and their spouses. We obtained water nitrate estimates for participants whose primary drinking water source at enrollment (1993-1997) was public water supplies (PWS) or private wells (N = 59,632). Average nitrate concentrations were computed from historical data for PWS users and predicted from random forest models for private well users. Analysis of dietary nitrate and nitrite was restricted to the 30,177 participants who completed the NCI Dietary History Questionnaire during follow-up (1999-2003). Incident ESRD through 2018 was ascertained through linkage with the U.S. Renal Data System. We estimated adjusted hazard ratios (HRs) and 95%CI for associations of tertiles (T) of exposure with ESRD overall and explored effects in strata of vitamin C and heme iron intake. RESULTS: We identified 469 incident ESRD cases (206 for dietary analysis). Water nitrate and total dietary nitrate/nitrite were not associated with ESRD, but increased ESRD was associated with nitrate and nitrite from processed meats. We found apparent associations between nitrite and ESRD only among participants with vitamin C

Occupational farm work activities influence workers' indoor home microbiome.

BACKGROUND: Farm work entails a heterogeneous mixture of exposures that vary considerably across farms and farmers. Farm work is associated with various health outcomes, both adverse and beneficial. One mechanism by which farming exposures can impact health is through the microbiome, including the indoor home environment microbiome. It is unknown how individual occupational exposures shape the microbial composition in workers' homes. OBJECTIVES: We investigated associations between farm work activities, including specific tasks and pesticide use, and the indoor microbiome in the homes of 468 male farmers. METHODS: Participants were licensed pesticide applicators, mostly farmers, enrolled in the Agricultural Lung Health Study from 2008 to 2011. Vacuumed dust from participants' bedrooms underwent whole-genome shotgun sequencing for indoor microbiome assessment. Using questionnaire data, we evaluated 6 farm work tasks (processing of either hay, silage, animal feed, fertilizer, or soy/grains, and cleaning grain bins) and 19 pesticide ingredients currently used in the past year, plus 7 banned persistent pesticide ingredients ever used. RESULTS: All 6 work tasks were associated with increased microbial diversity levels, with a positive dose-response for the total number of tasks performed (P = 0.001). All tasks were associated with altered microbial compositions (weighted UniFrac P = 0.001) and with higher abundance of specific microbes, including soil-based commensal microbes such as Haloterrigena. Among the 19 pesticides, current use of glyphosate and past use of lindane were associated with increased microbial diversity (P = 0.02-0.04). Ten currently used pesticides and all 7 banned pesticides were associated with altered microbial composition (P = 0.001-0.04). Six pesticides were associated with differential abundance of certain microbes. DISCUSSION: Different farm activities and exposures can uniquely impact the dust microbiome inside homes. Our work suggests that changes to the home microbiome could serve as one pathway for how occupational exposures impact the health of workers and their cohabitating family members, offering possible future intervention targets.

Glyphosate Use and Mosaic Loss of Chromosome Y among Male Farmers in the Agricultural Health Study.

BACKGROUND: Glyphosate is the most commonly used herbicide worldwide and has been implicated in the development of certain hematologic cancers. Although mechanistic studies in human cells and animals support the genotoxic effects of glyphosate, evidence in human populations is scarce. OBJECTIVES: We evaluated the association between lifetime occupational glyphosate use and mosaic loss of chromosome Y (mLOY) as a marker of genotoxicity among male farmers. METHODS: We analyzed blood-derived DNA from 1,606 farmers ≥50 years of age in the Biomarkers of Exposure and Effect in Agriculture study, a subcohort of the Agricultural Health Study. mLOY was detected using genotyping array intensity data in the pseudoautosomal region of the sex chromosomes. Cumulative lifetime glyphosate use was assessed using self-reported pesticide exposure histories. Using multivariable logistic regression, we estimated odds ratios (ORs) and 95% confidence intervals (CIs) for the associations between glyphosate use and any detectable mLOY (overall mLOY) or mLOY affecting ≥10% of cells (expanded mLOY). RESULTS: Overall, mLOY was detected in 21.4% of farmers, and 9.8% of all farmers had expanded mLOY. Increasing total lifetime days of glyphosate use was associated with expanded mLOY [highest vs. lowest quartile; OR=1.75 (95% CI: 1.00, 3.07), ptrend=0.03] but not with overall mLOY; the associations with expanded mLOY were most apparent among older (≥70 years of age) men [OR=2.30 (95% CI: 1.13, 4.67), ptrend=0.01], never smokers [OR=2.32 (95% CI: 1.04, 5.21), ptrend=0.04], and nonobese men [OR=2.04 (95% CI: 0.99, 4.19), ptrend=0.03]. Similar patterns of associations were observed for intensity-weighted lifetime days of glyphosate use. DISCUSSION: High lifetime glyphosate use could be associated with mLOY affecting a larger fraction of cells, suggesting glyphosate could confer genotoxic or selective effects relevant for clonal expansion. As the first study to investigate this association, our findings contribute novel evidence regarding the carcinogenic potential of glyphosate and require replication in future studies. https://doi.org/10.1289/EHP12834.

Mosquito control exposures and breast cancer risk: analysis of 1071 cases and 2096 controls from the Ghana Breast Health Study.

Epidemiologic data on insecticide exposures and breast cancer risk are inconclusive and mostly from high-income countries. Using data from 1071 invasive pathologically confirmed breast cancer cases and 2096 controls from the Ghana Breast Health Study conducted from 2013 to 2015, we investigated associations with mosquito control products to reduce the spread of mosquito-borne diseases, such as malaria. These mosquito control products were insecticide-treated nets, mosquito coils, repellent room sprays, and skin creams for personal protection against mosquitos. Multivariable and polytomous logistic regression models were used to estimate odds ratios (ORadj) and 95% confidence intervals (CI) with breast cancer risk-adjusted for potential confounders and known risk factors. Among controls, the reported use of mosquito control products were mosquito coils (65%), followed by insecticide-treated nets (56%), repellent room sprays (53%), and repellent skin creams (15%). Compared to a referent group of participants unexposed to mosquito control products, there was no significant association between breast cancer risk and mosquito coils. There was an association in breast cancer risk with reported use of insecticide-treated nets; however, that association was weak and not statistically significant. Participants who reported using repellent sprays were at elevated risks compared to women who did not use any mosquito control products, even after adjustment for all other mosquito control products (OR = 1.42, 95% CI=1.15-1.75). We had limited power to detect an association with repellent skin creams. Although only a few participants reported using repellent room sprays weekly/daily or < month-monthly, no trends were evident with increased frequency of use of repellent sprays, and there was no statistical evidence of heterogeneity by estrogen receptor (ER) status (p-het > 0.25). Our analysis was limited when determining if an association existed with repellent skin creams; therefore, we cannot conclude an association. We found limited evidence of risk associations with widely used mosquito coils and insecticide-treated nets, which are reassuring given their importance for malaria prevention. Our findings regarding specific breast cancer risk associations, specifically those observed between repellent sprays, require further study.

High pesticide exposures events, pesticide poisoning, and shingles: A medicare-linked study of pesticide applicators in the agricultural health study.

OBJECTIVES: Self-reported shingles was associated with history of high pesticide exposure events (HPEE) in licensed pesticide applicators aged >60 years in the Agricultural Health Study (AHS). In the current study, using AHS-linked Medicare claims data, we examined incident shingles in relation to pesticide-related illness and pesticide poisoning, as well as HPEE. METHODS: We studied 22,753 licensed private pesticide applicators (97% white males, enrolled in the AHS 1993-97), aged ≥66 years with >12 consecutive months of Medicare fee-for-service hospital and outpatient coverage between 1999 and 2016. Incident shingles was identified based on having ≥1 shingles claim(s) after 12 months without claims. At AHS enrollment, participants were asked if they ever sought medical care or were hospitalized for pesticide-related illness, and a supplemental questionnaire (completed by 51%) asked about HPEE and poisoning. Hazard ratios (HR) and 95% confidence intervals (CI) were estimated using Cox proportional hazards regression, adjusted for age, sex, race, state, and education. RESULTS: Over 192,053 person-years (PY), 2396 applicators were diagnosed with shingles (10.5%; age-standardized rate, 13.6 cases per 1,000PY), with higher rates among those reporting hospitalization for pesticide-related illness, pesticide poisoning, and HPEE (23.2, 22.5, and 16.6 per 1,000PY, respectively). In adjusted models, shingles was associated with hospitalization for pesticide-related illness (HR 1.69; 1.18, 2.39), poisoning (1.49; 1.08, 1.46), and HPEE (1.23; 95% CI = 1.03, 1.46), especially HPEE plus medical care/poisoning (1.78; 1.30, 2.43). CONCLUSION: These novel findings suggest that acute, high-level, and clinically impactful pesticide exposures may increase risk of shingles in subsequent years to decades following exposure.

Occupational Farm Work Activities Influence Workers' Indoor Home Microbiome.

Background: Farm work entails a heterogeneous mixture of exposures that vary considerably across farms and farmers. Farm work is associated with various health outcomes, both adverse and beneficial. One mechanism by which farming exposures can impact health is through the microbiome, including the indoor built environment microbiome. It is unknown how individual occupational exposures shape the microbial composition in workers' homes. Objectives: We investigated associations between farm work activities, including specific tasks and pesticide use, and the indoor microbiome in the homes of 468 male farmers. Methods: Participants were licensed pesticide applicators, mostly farmers, enrolled in the Agricultural Lung Health Study from 2008-2011. Vacuumed dust from participants' bedrooms underwent whole-genome shotgun sequencing for indoor microbiome assessment. Using questionnaire data, we evaluated 6 farm work tasks (processing of either hay, silage, animal feed, fertilizer, or soy/grains, and cleaning grain bins) and 19 pesticide ingredients currently used in the past year, plus 7 persistent banned pesticide ingredients ever used. Results: All 6 work tasks were associated with increased within-sample microbial diversity, with a positive dose-response for the sum of tasks (p=0.001). All tasks were associated with altered overall microbial compositions (weighted UniFrac p=0.001) and with higher abundance of specific microbes, including soil-based microbes such as Haloterrigena. Among the 19 pesticides, only current use of glyphosate and past use of lindane were associated with increased within-sample diversity (p=0.02-0.04). Ten currently used pesticides and all 7 banned pesticides were associated with altered microbial composition (p=0.001-0.04). Six pesticides were associated with differential abundance of certain microbes. Discussion: Specific farm activities and exposures can impact the dust microbiome inside homes. Our work suggests that occupational farm exposures could impact the health of workers and their families through modifying the indoor environment, specifically the microbial composition of house dust, offering possible future intervention targets.

Joint associations between established genetic susceptibility loci, pesticide exposures, and risk of prostate cancer.

More than 200 genetic variants have been independently associated with prostate cancer risk. Studies among farmers have also observed increased prostate cancer risk associated with exposure to specific organophosphate (fonofos, terbufos, malathion, dimethoate) and organochlorine (aldrin, chlordane) insecticides. We examined the joint associations between these pesticides, established prostate cancer loci, and prostate cancer risk among 1,162 cases (588 aggressive) and 2,206 frequency-matched controls nested in the Agricultural Health Study cohort. History of lifetime pesticide use was combined with a polygenic risk score (PRS) generated using 256 established prostate cancer risk variants. Logistic regression models estimated the joint associations of the pesticides, the PRS, and the 256 individual genetic variants with risk of total and aggressive prostate cancer. Likelihood ratio tests assessed multiplicative interaction. We observed interaction between ever use of fonofos and the PRS in relation to total and aggressive prostate cancer risk. Compared to the reference group (never use, PRS < median), men with ever use of fonofos and PRS > median had elevated risks of total (OR 1.35 [1.06-1.73], p-interaction = 0.03) and aggressive (OR 1.49 [1.09-2.04], p-interaction = 0.19) prostate cancer. There was also suggestion of interaction between pesticides and individual genetic variants occurring in regions associated with DNA damage response (CDH3, EMSY genes) and with variants related to altered androgen receptor-driven transcriptional programs critical for prostate cancer. Our study provides evidence that men with greater genetic susceptibility to prostate cancer may be at higher risk if they are also exposed to pesticides and suggests potential mechanisms by which pesticides may increase prostate cancer risk.

A latent functional approach for modeling the effects of multidimensional exposures on disease risk.

Understanding the relationships between exposure and disease incidence is an important problem in environmental epidemiology. Typically, a large number of these exposures are measured, and it is found either that a few exposures transmit risk or that each exposure transmits a small amount of risk, but, taken together, these may pose a substantial disease risk. Further, these exposure effects can be nonlinear. We develop a latent functional approach, which assumes that the individual effect of each exposure can be characterized as one of a series of unobserved functions, where the number of latent functions is less than or equal to the number of exposures. We propose Bayesian methodology to fit models with a large number of exposures and show that existing Bayesian group LASSO approaches are a special case of the proposed model. An efficient Markov chain Monte Carlo sampling algorithm is developed for carrying out Bayesian inference. The deviance information criterion is used to choose an appropriate number of nonlinear latent functions. We demonstrate the good properties of the approach using simulation studies. Further, we show that complex exposure relationships can be represented with only a few latent functional curves. The proposed methodology is illustrated with an analysis of the effect of cumulative pesticide exposure on cancer risk in a large cohort of farmers.

Endogenous sex steroid hormones and risk of liver cancer among US men: Results from the Liver Cancer Pooling Project.

Background & Aims: Incidence rates of liver cancer in most populations are two to three times higher among men than women. The higher rates among men have led to the suggestion that androgens are related to increased risk whereas oestrogens are related to decreased risk. This hypothesis was investigated in the present study via a nested case-control analysis of pre-diagnostic sex steroid hormone levels among men in five US cohorts. Methods: Concentrations of sex steroid hormones and sex hormone-binding globulin were quantitated using gas chromatography-mass spectrometry and a competitive electrochemiluminescence immunoassay, respectively. Multivariable conditional logistic regression was used to calculate odds ratios (ORs) and 95% CIs for associations between hormones and liver cancer among 275 men who subsequently developed liver cancer and 768 comparison men. Results: Higher concentrations of total testosterone (OR per one-unit increase in log2 = 1.77, 95% CI = 1.38-2.29), dihydrotestosterone (OR = 1.76, 95% CI = 1.21-2.57), oestrone (OR = 1.74, 95% CI = 1.08-2.79), total oestradiol (OR = 1.58, 95% CI=1.22-20.05), and sex hormone-binding globulin (OR = 1.63, 95% CI = 1.27-2.11) were associated with increased risk. Higher concentrations of dehydroepiandrosterone (DHEA), however, were associated with a 53% decreased risk (OR = 0.47, 95% CI = 0.33-0.68). Conclusions: Higher concentrations of both androgens (testosterone, dihydrotestosterone) and their aromatised oestrogenic metabolites (oestrone, oestradiol) were observed among men who subsequently developed liver cancer compared with men who did not. As DHEA is an adrenal precursor of both androgens and oestrogens, these results may suggest that a lower capacity to convert DHEA to androgens, and their subsequent conversion to oestrogens, confers a lower risk of liver cancer, whereas a greater capacity to convert DHEA confers a greater risk. Impact and implications: This study does not fully support the current hormone hypothesis as both androgen and oestrogen levels were associated with increased risk of liver cancer among men. The study also found that higher DHEA levels were associated with lower risk, thus suggesting the hypothesis that greater capacity to convert DHEA could be associated with increased liver cancer risk among men.

Metagenomics reveals novel microbial signatures of farm exposures in house dust.

Indoor home dust microbial communities, important contributors to human health, are shaped by environmental factors, including farm-related exposures. Advanced metagenomic whole genome shotgun sequencing (WGS) improves detection and characterization of microbiota in the indoor built-environment dust microbiome, compared to conventional 16S rRNA amplicon sequencing (16S). We hypothesized that the improved characterization of indoor dust microbial communities by WGS will enhance detection of exposure-outcome associations. The objective of this study was to identify novel associations of environmental exposures with the dust microbiome from the homes of 781 farmers and farm spouses enrolled in the Agricultural Lung Health Study. We examined various farm-related exposures, including living on a farm, crop versus animal production, and type of animal production, as well as non-farm exposures, including home cleanliness and indoor pets. We assessed the association of the exposures on within-sample alpha diversity and between-sample beta diversity, and the differential abundance of specific microbes by exposure. Results were compared to previous findings using 16S. We found most farm exposures were significantly positively associated with both alpha and beta diversity. Many microbes exhibited differential abundance related to farm exposures, mainly in the phyla Actinobacteria, Bacteroidetes, Firmicutes, and Proteobacteria. The identification of novel differential taxa associated with farming at the genera level, including Rhodococcus, Bifidobacterium, Corynebacterium, and Pseudomonas, was a benefit of WGS compared to 16S. Our findings indicate that characterization of dust microbiota, an important component of the indoor environment relevant to human health, is heavily influenced by sequencing techniques. WGS is a powerful tool to survey the microbial community that provides novel insights on the impact of environmental exposures on indoor dust microbiota. These findings can inform the design of future studies in environmental health.

Firefighting and Cancer: A Meta-analysis of Cohort Studies in the Context of Cancer Hazard Identification.

Objective: We performed a meta-analysis of epidemiological results for the association between occupational exposure as a firefighter and cancer as part of the broader evidence synthesis work of the IARCMonographs program. Methods: A systematic literature search was conducted to identify cohort studies of firefighters followed for cancer incidence and mortality. Studies were evaluated for the influence of key biases on results. Random-effects meta-analysis models were used to estimate the association between ever-employment and duration of employment as a firefighter and risk of 12 selected cancers. The impact of bias was explored in sensitivity analyses. Results: Among the 16 included cancer incidence studies, the estimated meta-rate ratio, 95% confidence interval (CI), and heterogeneity statistic (I2) for ever-employment as a career firefighter compared mostly to general populations were 1.58 (1.14-2.20, 8%) for mesothelioma, 1.16 (1.08-1.26, 0%) for bladder cancer, 1.21 (1.12-1.32, 81%) for prostate cancer, 1.37 (1.03-1.82, 56%) for testicular cancer, 1.19 (1.07-1.32, 37%) for colon cancer, 1.36 (1.15-1.62, 83%) for melanoma, 1.12 (1.01-1.25, 0%) for non-Hodgkin lymphoma, 1.28 (1.02-1.61, 40%) for thyroid cancer, and 1.09 (0.92-1.29, 55%) for kidney cancer. Ever-employment as a firefighter was not positively associated with lung, nervous system, or stomach cancer. Results for mesothelioma and bladder cancer exhibited low heterogeneity and were largely robust across sensitivity analyses. Conclusions: There is epidemiological evidence to support a causal relationship between occupational exposure as a firefighter and certain cancers. Challenges persist in the body of evidence related to the quality of exposure assessment, confounding, and medical surveillance bias.

Using a smartphone application to capture daily work activities: a longitudinal pilot study in a farming population.

OBJECTIVES: Smartphones are increasingly used to collect real-time information on time-varying exposures. We developed and deployed an application (app) to evaluate the feasibility of using smartphones to collect real-time information on intermittent agricultural activities and to characterize agricultural task variability in a longitudinal study of farmers. METHODS: We recruited 19 male farmers, aged 50-60 years, to report their farming activities on 24 randomly selected days over 6 months using the Life in a Day app. Eligibility criteria include personal use of an iOS or Android smartphone and >4 h of farming activities at least two days per week. We developed a study-specific database of 350 farming tasks that were provided in the app; 152 were linked to questions that were asked when the activity ended. We report eligibility, study compliance, number of activities, duration of activities by day and task, and responses to the follow-up questions. RESULTS: Of the 143 farmers we reached out to for this study, 16 were not reached by phone or refused to answer eligibility questions, 69 were ineligible (limited smartphone use and/or farming time), 58 met study criteria, and 19 agreed to participate. Refusals were mostly related to uneasiness with the app and/or time commitment (32 of 39). Participation declined gradually over time, with 11 farmers reporting activities through the 24-week study period. We obtained data on 279 days (median 554 min/day; median 18 days per farmer) and 1,321 activities (median 61 min/activity; median 3 activities per day per farmer). The activities were predominantly related to animals (36%), transportation (12%), and equipment (10%). Planting crops and yard work had the longest median durations; short-duration tasks included fueling trucks, collecting/storing eggs, and tree work. Time period-specific variability was observed; for example, crop-related activities were reported for an average of 204 min/day during planting but only 28 min/day during pre-planting and 110 min/day during the growing period. We obtained additional information for 485 (37%) activities; the most frequently asked questions were related to "feed animals" (231 activities) and "operate fuel-powered vehicle (transportation)" (120 activities). CONCLUSIONS: Our study demonstrated feasibility and good compliance in collecting longitudinal activity data over 6 months using smartphones in a relatively homogeneous population of farmers. We captured most of the farming day and observed substantial heterogeneity in activities, highlighting the need for individual activity data when characterizing exposure in farmers. We also identified several areas for improvement. In addition, future evaluations should include more diverse populations.

Genetic Susceptibility to Nonalcoholic Fatty Liver Disease and Risk for Pancreatic Cancer: Mendelian Randomization.

BACKGROUND: There are conflicting data on whether nonalcoholic fatty liver disease (NAFLD) is associated with susceptibility to pancreatic cancer. Using Mendelian randomization (MR), we investigated the relationship between genetic predisposition to NAFLD and risk for pancreatic cancer. METHODS: Data from genome-wide association studies (GWAS) within the Pancreatic Cancer Cohort Consortium (PanScan; cases n = 5,090, controls n = 8,733) and the Pancreatic Cancer Case Control Consortium (PanC4; cases n = 4,163, controls n = 3,792) were analyzed. We used data on 68 genetic variants with four different MR methods [inverse variance weighting (IVW), MR-Egger, simple median, and penalized weighted median] separately to predict genetic heritability of NAFLD. We then assessed the relationship between each of the four MR methods and pancreatic cancer risk, using logistic regression to calculate ORs and 95% confidence intervals (CI), adjusting for PC risk factors, including obesity and diabetes. RESULTS: No association was found between genetically predicted NAFLD and pancreatic cancer risk in the PanScan or PanC4 samples [e.g., PanScan, IVW OR, 1.04; 95% confidence interval (CI), 0.88-1.22; MR-Egger OR, 0.89; 95% CI, 0.65-1.21; PanC4, IVW OR, 1.07; 95% CI, 0.90-1.27; MR-Egger OR, 0.93; 95% CI, 0.67-1.28]. None of the four MR methods indicated an association between genetically predicted NAFLD and pancreatic cancer risk in either sample. CONCLUSIONS: Genetic predisposition to NAFLD is not associated with pancreatic cancer risk. IMPACT: Given the close relationship between NAFLD and metabolic conditions, it is plausible that any association between NAFLD and pancreatic cancer might reflect host metabolic perturbations (e.g., obesity, diabetes, or metabolic syndrome) and does not necessarily reflect a causal relationship between NAFLD and pancreatic cancer.