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Background Untargeted metabolomics datasets contain large proportions of uninformative features that can impede subsequent statistical analysis such as biomarker discovery and metabolic pathway analysis. Thus, there is a need for versatile and data-adaptive methods for filtering data prior to investigating the underlying biological phenomena. Here, we propose a data-adaptive pipeline for filtering metabolomics data that are generated by liquid chromatography-mass spectrometry (LC-MS) platforms. Our data-adaptive pipeline includes novel methods for filtering features based on blank samples, proportions of missing values, and estimated intra-class correlation coefficients. Results Using metabolomics datasets that were generated in our laboratory from samples of human blood, as well as two public LC-MS datasets, we compared our data-adaptive filtering method with traditional methods that rely on non-method specific thresholds. The data-adaptive approach outperformed traditional approaches in terms of removing noisy features and retaining high quality, biologically informative ones. The R code for running the data-adaptive filtering method is provided at https://github.com/courtneyschiffman/Metabolomics-Filtering . Conclusions Our proposed data-adaptive filtering pipeline is intuitive and effectively removes uninformative features from untargeted metabolomics datasets. It is particularly relevant for interrogation of biological phenomena in data derived from complex matrices associated with biospecimens.

Individuals are exposed to a large number of diverse environmental chemicals simultaneously and the evaluation of multiple chemical exposures is important for identifying cancer risk factors. The measurement of a large number of chemicals (the exposome) in epidemiologic studies is allowing for a more comprehensive assessment of cancer risk factors than was done in earlier studies that focused on only a few chemicals. Empirical evidence from epidemiologic studies shows that chemicals from different chemical classes have different magnitudes and directions of association with cancers. Given increasing data availability, there is a need for the development and assessment of statistical methods to model environmental cancer risk that considers a large number of diverse chemicals with different effects for different chemical classes. The method of grouped weighted quantile sum (GWQS) regression allows for multiple groups of chemicals to be considered in the model such that different magnitudes and directions of associations are possible for each group of chemicals. In this paper, we assessed the ability of GWQS regression to estimate exposure effects for multiple chemical groups and correctly identify important chemicals in each group using a simulation study. We compared the performance of GWQS regression with WQS regression, the least absolute shrinkage and selection operator (lasso), and the group lasso in estimating exposure effects and identifying important chemicals. The simulation study results demonstrate that GWQS is an effective method for modeling exposure to multiple groups of chemicals and compares favorably with other methods used in mixture analysis. As an application, we used GWQS regression in the California Childhood Leukemia Study (CCLS), a population-based case-control study of childhood leukemia in California to estimate exposure effects for many chemical classes while also adjusting for demographic factors. The CCLS analysis found evidence of a positive association between exposure to the herbicide dacthal and an increased risk of childhood leukemia.

Acute lymphoblastic leukemia (ALL) is the most common type of cancer in children (age 0–14 years); however, the etiology remains incompletely understood. Several environmental exposures have been linked to risk of childhood ALL, including air pollution. Closely related to air pollution and human development is artificial light at night (ALAN), which is believed to disrupt circadian rhythm and impact health. We sought to evaluate outdoor ALAN and air pollution on risk of childhood ALL. The California Linkage Study of Early-Onset Cancers is a large population-based case–control in California that identifies and links cancer diagnoses from the California Cancer Registry to birth records. For each case, 50 controls with the same year of birth were obtained from birth records. A total of 2,782 ALL cases and 139,100 controls were identified during 2000–2015. ALAN was assessed with the New World Atlas of Artificial Night Sky Brightness and air pollution with an ensemble-based air pollution model of particulate matter smaller than 2.5 microns (PM 2.5 ). After adjusting for known and suspected risk factors, the highest tertile of ALAN was associated with an increased risk of ALL in Hispanic children (odds ratio [OR] = 1.15, 95% confidence interval [CI] 1.01–1.32). There also appeared to be a borderline association between PM 2.5 level and risk of ALL among non-Hispanic White children (OR per 10 µg/m 3  = 1.24, 95% CI 0.98–1.56). We observed elevated risk of ALL in Hispanic children residing in areas of greater ALAN. Further work is needed to understand the role of ALAN and air pollution in the etiology of childhood ALL in different racial/ethnic groups.

Childhood acute lymphoblastic leukemia (ALL) (age 0–14 years) is 20% more common in Latino Americans than non-Latino whites. We conduct a genome-wide association study in a large sample of 3263 Californian children with ALL (including 1949 of Latino heritage) and 3506 controls matched on month and year of birth, sex, and ethnicity, and an additional 12,471 controls from the Kaiser Resource for Genetic Epidemiology Research on Aging Cohort. Replication of the strongest genetic associations is performed in two independent datasets from the Children’s Oncology Group and the California Childhood Leukemia Study. Here we identify new risk loci on 17q12 near IKZF3/ZPBP2/GSDMB/ORMDL3 , a locus encompassing a transcription factor important for lymphocyte development ( IKZF3 ), and at an 8q24 region known for structural contacts with the MYC oncogene. These new risk loci may impact gene expression via local (four 17q12 genes) or long-range (8q24) interactions, affecting function of well-characterized hematopoietic and growth-regulation pathways. Childhood acute lymphoblastic leukemia is common in Latino Americans. Here, the authors conduct a genome-wide association study in a Californian cohort containing children of Latino heritage, and identify loci on 17q12 and 8q24 which may affect hematopoietic and growth-regulation pathways.

Pilocytic astrocytoma (PA) is the most common pediatric brain tumor. PA has at least a 50% higher incidence in populations of European ancestry compared to other ancestral groups, which may be due in part to genetic differences. We first compared the global proportions of European, African, and Amerindian ancestries in 301 PA cases and 1185 controls of self-identified Latino ethnicity from the California Biobank. We then conducted admixture mapping analysis to assess PA risk with local ancestry. We found PA cases had a significantly higher proportion of global European ancestry than controls (case median = 0.55, control median = 0.51, P value = 3.5x10-3). Admixture mapping identified 13 SNPs in the 6q14.3 region (SNX14) contributing to risk, as well as three other peaks approaching significance on chromosomes 7, 10 and 13. Downstream fine mapping in these regions revealed several SNPs potentially contributing to childhood PA risk. There is a significant difference in genomic ancestry associated with Latino PA risk and several genomic loci potentially mediating this risk.

Background Incidence of childhood Ewing sarcoma, a rare cancer affecting bones and soft tissues, is increasing. Environmental exposures during the perinatal period, like air pollution, may play a role. We examined exposure to perinatal ambient fine particulate matter (PM 2.5 ) and childhood Ewing sarcoma risk in a case-control linkage study nested within a California birth cohort. Methods The study included 388 children born in California (1982–2015) and diagnosed with Ewing sarcoma at age 0–19 years (1988–2015), and 19,341 California-born cancer-free controls frequency-matched to cases on birth year (50:1 ratio). Ambient PM 2.5 concentrations at the maternal residence were averaged separately over two time periods, gestation and the first year after birth, using a validated ensemble-based model (categorized as quartiles). We estimated odds ratios (ORs) and 95% confidence intervals (CIs) for the association between perinatal PM 2.5 exposure and Ewing sarcoma risk, adjusting for sex, birth year, race, ethnicity, birth weight, and maternal education and stratifying by Hispanic ethnicity to assess potential disparities in PM 2.5 -related cancer risk. Results In the overall population, perinatal ambient PM 2.5 exposure was not associated with Ewing sarcoma risk when considering exposure during gestation or the year after birth. Among Hispanic children, who experienced greater air pollution exposure compared to non-Hispanic children, higher PM 2.5 levels during gestation yielded elevated odds of Ewing sarcoma compared to the first quartile (Q2 OR [95% CI] = 1.53 [0.94–2.51]; Q3 = 1.56 [0.95–2.56]; Q4 = 1.39 [0.79–2.47]). Hispanic children also experienced elevated risk in relation to exposure during the year after birth. Conclusion Our results provide new suggestive evidence that ambient PM 2.5 may contribute to Ewing sarcoma risk, although these findings were not statistically significant and were specific to Hispanic children. These findings require replication and underscore the need to further evaluate the potential role of ethnicity in the PM 2.5 -cancer relationship with genetic ancestry measures and through the lens of environmental justice.

Background Oil and gas development (OGD) has been linked to increased pediatric cancer risk, but the literature to date is focused on hematologic malignancies and active wells. The emergence of suspected clusters of cancers such as Ewing sarcoma in children living near OGD and widespread presence of abandoned wells warrants investigation. Methods This study included 558 children born in California (1982–2015) reported to the California Cancer Registry with a diagnosis of Ewing sarcoma at 0–19 years (1988–2015), and 27,800 cancer-free controls frequency-matched to cases on birth-year (50:1 ratio). We used birth address to assign prenatal OGD exposure to active (drilled or producing) and plugged/abandoned wells separately with inverse distance-squared weighted well counts at 5 and 10 km buffer sizes from three months before conception to birth. We evaluated potential exposure disparities and estimated odds ratios (OR) and 95% confidence intervals (CI) for the association between prenatal OGD exposure and Ewing sarcoma risk using multivariable logistic regression. Results Hispanic children were significantly more likely to be exposed to both active and abandoned OGD within 10 km than non-Hispanics (40% vs. 23% and 14% vs. 6%, respectively). There were no associations between prenatal exposure to active OGD within 10 km and Ewing sarcoma risk (OR: 0.88 [95% CI: 0.72–1.08]). However, children within 10 km of abandoned wells were 1.27 [0.96–1.66] times as likely to develop Ewing sarcoma as unexposed children; when stratified by ethnicity, this association appeared in Hispanic children only (1.33 [0.95–1.88]). Conclusion We did not identify an association between exposure to active OGD and pediatric Ewing sarcoma risk in California. Abandoned wells were associated with a suggestive increase in risk among Hispanic children, who were also more likely to be exposed to any OGD activity than non-Hispanic children. This disparity could have implications for other health outcomes including childhood cancers.

Residential dust has been used as a medium for assessing human exposures to a constellation of indoor contaminants including radionuclides, persistent organic pollutants, metals, allergens, and tobacco smoke. Here, we review and comment on investigations of household dust levels of particular analytes of health significance, namely polybrominated diphenyl ethers, polychlorinated biphenyls, and polycyclic aromatic hydrocarbons. In doing so, we not only describe methods for collecting and analyzing residential dust, but also describe global patterns in dust levels. Aside from geographic location, we discuss several potential determinants for dust levels of these contaminants. We also review previous estimates of the contribution of dust to overall intake of these three chemical classes and show how residential-dust measurements could be useful in either augmenting or replacing questionnaire-based assessment of human exposures in epidemiological studies. We conclude our review with a discussion of the current gaps in knowledge of worldwide dust levels and suggestions for how residential-dust measurements could be used to describe human exposures to chemicals in developing countries.

Purpose: The early onset of childhood acute lymphoblastic leukemia (ALL) suggests that critical exposures occurring during pregnancy may increase risk. We investigated the effects of maternal coffee and tea consumption during pregnancy on ALL risk by pooling data from eight case-control studies participating in the Childhood Leukemia International Consortium.Method: Data on maternal coffee intake were available for 2,552 cases and 4,876 controls, and data on tea intake were available for 2,982 cases and 5,367 controls. Coffee and tea intake was categorized into 0, > 0-1, > 1-2, and > 2 cups/day, and covariates were combined and harmonized. Data on genetic variants in NAT2, CYP1A1, and NQO1 were also available in a subset. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using unconditional logistic regression, and linear trends across categories were assessed.Results: No association was seen with 'any' maternal coffee consumption during pregnancy, but there was evidence of a positive exposure-response; the pooled OR for > 2 cups/day versus none was 1.27 (95% CI 1.09-1.43), p trend = 0.005. No associations were observed with tea consumption. No interactions were seen between coffee or tea intake and age, maternal smoking or genotype, and there was little or no evidence that associations with coffee or tea differed among cases with and without chromosomal translocations.Conclusions: Despite some limitations, our findings suggest that high coffee intake during pregnancy may increase risk of childhood ALL. Thus, current advice to limit caffeine intake during pregnancy to reduce risk of preterm birth may have additional benefits.

Recent genome-wide studies conducted in European Whites have identified novel susceptibility genes for childhood acute lymphoblastic leukemia (ALL). We sought to examine whether these loci are susceptibility genes among Hispanics, whose reported incidence of childhood ALL is the highest of all ethnic groups in California, and whether their effects differ between Hispanics and non-Hispanic Whites (NHWs). We genotyped 13 variants in these genes among 706 Hispanic (300 cases, 406 controls) and 594 NHW (225 cases, 369 controls) participants in a matched population-based case-control study in California. We found significant associations for the five studied ARID5B variants in both Hispanics (p values of 1.0 × 10⁻⁹ to 0.004) and NHWs (p values of 2.2 × 10⁻⁶ to 0.018). Risk estimates were in the same direction in both groups (ORs of 1.53–1.99 and 1.37–1.84, respectively) and strengthened when restricted to B-cell precursor high-hyperdiploid ALL (>50 chromosomes; ORs of 2.21–3.22 and 1.67–2.71, respectively). Similar results were observed for the single CEBPE variant. Hispanics and NHWs exhibited different susceptibility loci at CDKN2A. Although IKZF1 loci showed significant susceptibility effects among NHWs (p < 1 × 10⁻⁵), their effects among Hispanics were in the same direction but nonsignificant, despite similar minor allele frequencies. Future studies should examine whether the observed effects vary by environmental, immunological, or lifestyle factors.