Herbicide use in farming and other jobs in relation to non-Hodgkin's lymphoma (NHL) risk

Modeling variation in mixture effects over space with a Bayesian spatially varying mixture model

Mixture analysis is an emerging statistical tool in epidemiological research that seeks to estimate the health effects associated with mixtures of several exposures. This approach acknowledges that individuals experience many simultaneous exposures and it can estimate the relative importance of components in the mixture. Health effects due to mixtures may vary over space driven by to political, demographic, environmental, or other differences. In such cases, estimating a global mixture effect without accounting for spatial variation would induce bias in effect estimates and potentially lower statistical power. To date, no methods have been developed to estimate spatially varying chemical mixture effects. We developed a Bayesian spatially varying mixture model that estimates spatially varying mixture effects and the importance weights of components in the mixture, while adjusting for covariates. We demonstrate the efficacy of the model through a simulation study that varies the number of mixtures (one and two) and spatial pattern (global, one-dimensional, radial) and magnitude of mixture effects, showing that the model is able to accurately reproduce the spatial pattern of mixture effects across a diverse set of scenarios. Finally, we apply our model to a multi-center case-control study of non-Hodgkin lymphoma (NHL) in Detroit, Iowa, Los Angeles, and Seattle. We identify significant spatially varying positive and inverse associations with NHL for two mixtures of pesticides in Iowa and do not find strong spatial effects at the other three centers. In conclusion, the Bayesian spatially varying mixture model represents a novel method for modeling spatial variation in mixture effects.

New sensitive LC-MS/MS method for the simultaneous determination of 13 phenolic and carboxylic acid pesticide biomarkers in human urine, including dicamba

The commercialization in 2016 of genetically engineered seeds tolerant to dicamba and/or 2,4-dichlorophenoxyacetic acid (2,4-D) has caused a rapid increase in the use of these herbicides. New questions about the reproductive and chronic health effects of long-term exposure to these herbicides have been raised. To assess exposure to dicamba and other pesticides of interest in the Heartland Study, a birth cohort study based in the United States, a new analytical method was needed. The present study describes the development and validation of this new solid phase extraction and liquid chromatography-tandem mass spectrometry method that detects simultaneously 13 pesticides or their metabolites in 250 μL of urine. More specifically, the method allows the analysis of dicamba, 2,4-D and 2,4,5-trichlorophenoxyacetic acid (2,4,5-T), which are herbicides, of malathion dicarboxylic acid (MDA), para-nitrophenol (PNP), 3,5,6-trichloro-2-pyridinol (TCPy), 2-diethylamino-6-methylpyrimidin-4-ol (DEAMPY) and 2-isopropyl-6-methyl-4-pyrimidinol (IMPY), which are metabolites of organophosphate insecticides, and finally of cis-3-(2,2-Dichlorovinyl)-2,2-dimethylcyclopropane carboxylic acid (cis-DCCA), trans-3-(2,2-Dichlorovinyl)-2,2-dimethylcyclopropane carboxylic acid (trans-DCCA), 3-Phenoxybenzoic acid (3-PBA), 4-Fluoro-3-phenoxybenzoic acid (4-F-3-PBA) and cis-3-(2,2-Dibromovinyl)-2,2-dimethylcyclopropane carboxylic acid (cis-DBCA), which are metabolites of synthetic pyrethroids insecticides. The method was validated under ISO/IEC 17025 guidance. The limit of detection (LOD) in urine samples was 0.10 μg/L for dicamba, while the LOD for other analytes ranged between 0.0038 μg/L and 0.091 μg/L. Accuracy was evaluated by analyzing samples from two External Quality Assessment Schemes, namely G-EQUAS and OSEQAS. Preliminary results obtained following the analysis of 91 urine samples taken from pregnant women enrolled in the Heartland Study are presented here. This method is suitable for human biomonitoring studies.

Epidemiologic studies of glyphosate and non-Hodgkin's lymphoma: A review with consideration of exposure frequency, systemic dose, and study quality

I reviewed the epidemiologic literature for glyphosate and non-Hodgkin's lymphoma (NHL) in the context of the frequency of exposure in each epidemiologic study, systemic dose from biomonitoring studies of applicators, and aspects of study quality. Nine studies were identified, 7 case control and 2 cohort, by a literature search and a review of reference lists from published studies and recent regulatory evaluations. All but one study involved exposure scenarios that were so infrequent that they are not credible for cancer causation. Most studies failed to address potential confounding from other pesticides. Only one study - the US Agricultural Health Study (AHS) - included individuals with relatively frequent exposure to glyphosate and involved comprehensive statistical analyses to address potential confounding by personal factors and other pesticide exposures. The AHS did not find an association between glyphosate and NHL, even among the most frequently exposed participants (≥ 109 days of use) (RR = 0.80, 95% CI 0.60, 1.06). These findings are consistent with observations that glyphosate systemic doses from agricultural applications are many orders of magnitude less than daily lifetime doses considered by regulatory agencies to impart no excess risk of deleterious health effects, even for sensitive subpopulations.

Epidemiology and etiology of diffuse large B-cell lymphoma

As the most common non-Hodgkin lymphoma subtype, diffuse large B-cell lymphoma (DLBCL) incidence patterns generally parallel that for NHL overall. Globally, DLBCL accounts for a third of all NHLs, ranging between 20% and 50% by country. Based on United States (U.S.) cancer registry data, age-standardized incidence rate for DLBCL was 7.2 per 100,000. DLBCL incidence rises with age and is generally higher in males than females; in the U.S., incidence is highest among non-Hispanic whites (9.2/100,000). Like NHL incidence, DLBCL incidence rose in the first half of the 20th century but has largely plateaued. However, there is some evidence that incidence rates are rising in areas of historically low rates, such as Asia; there are also estimates for rising DLBCL incidence in the near future due to the changing demographics in developed countries whose aging population is growing. Established risk factors for DLBCL include those that result in severe immune deficiency such as HIV/AIDS, inherited immunodeficiency syndromes, and organ transplant recipients. Factors that lead to chronic immune dysregulations are also established risk factors, and include a number of autoimmune conditions (eg, Sjögren syndrome, systemic lupus erythematosus, rheumatoid arthritis), viral infections (eg, HIV, KSHV/HHV8, HCV, EBV), and obesity. Family history of NHL/DLBCL, personal history of cancer, and multiple genetic susceptibility loci are also well-established risk factors for DLBCL. There is strong evidence for multiple environmental exposures in DLBCL etiology, including exposure to trichloroethylene, benzene, and pesticides and herbicides, with recent associations noted with glyphosate. There is also strong evidence for associations with other viruses, such as HBV. Recent estimates suggest that obesity accounts for nearly a quarter of DLBCLs that develop, but despite recent gains in the understanding of DLBCL etiology, the majority of disease remain unexplained. An understanding of the host and environmental contributions to disease etiology, and concerted efforts to expand our understanding to multiple race/ethnic groups, will be essential for constructing clinically relevant risk prediction models and develop effective strategies for disease prevention.