Association between Total and Individual PCB Congener Levels in Maternal Serum and Birth Weight of Newborns: Results from the Chiba Study of Mother and Child Health Using Weighted Quantile Sum Regression.
Ontology highlight
ABSTRACT:
SUBMITTER: Eguchi A
PROVIDER: S-EPMC8775854 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Studies of the health effects of the microbiome often measure overall associations by using diversity metrics, and individual taxa associations in separate analyses, but do not consider the correlated relationships between taxa in the microbiome. In this study, we applied random subset weighted quantile sum regression with repeated holdouts (WQSRSRH), a mixture method successfully applied to ‘omic data to account for relationships between many predictors, to processed amplicon sequencing data from the Human Microbiome Project. We simulated a binary variable associated with 20 operational taxonomic units (OTUs). WQSRSRH was used to test for the association between the microbiome and the simulated variable, adjusted for sex, and sensitivity and specificity were calculated. The WQSRSRH method was also compared to other standard methods for microbiome analysis. The method was further illustrated using real data from the Growth and Obesity Cohort in Chile to assess the association between the gut microbiome and body mass index. In the analysis with simulated data, WQSRSRH predicted the correct directionality of association between the microbiome and the simulated variable, with an average sensitivity and specificity of 75% and 70%, respectively, in identifying the 20 associated OTUs. WQSRSRH performed better than all other comparison methods. In the illustration analysis of the gut microbiome and obesity, the WQSRSRH analysis identified an inverse association between body mass index and the gut microbe mixture, identifying Bacteroides, Clostridium, Prevotella, and Ruminococcus as important genera in the negative association. The application of WQSRSRH to the microbiome allows for analysis of the mixture effect of all the taxa in the microbiome, while simultaneously identifying the most important to the mixture, and allowing for covariate adjustment. It outperformed other methods when using simulated data, and in analysis with real data found results consistent with other study findings.
| S-EPMC9819204 | biostudies-literature
Project description:BackgroundNew statistical methodologies were developed in the last decade to face the challenges of estimating the effects of exposure to multiple chemicals. Weighted Quantile Sum (WQS) regression is a recent statistical method that allows estimating a mixture effect associated with a specific health effect and identifying the components that characterize the mixture effect.ObjectivesIn this study, we propose an extension of WQS regression that estimates two mixture effects of chemicals on a health outcome in the same model through the inclusion of two indices, one in the positive direction and one in the negative direction, with the introduction of a penalization term.MethodsTo evaluate the performance of this new model we performed both a simulation study and a real case study where we assessed the effects of nutrients on obesity among adults using the National Health and Nutrition Examination Survey (NHANES) data.ResultsThe method showed good performance in estimating both the regression parameter and the weights associated with the single elements when the penalized term was set equal to the magnitude of the Akaike information criterion of the unpenalized WQS regression. The two indices further helped to give a better estimate of the parameters [Positive direction Median Error (PME): 0.022; Negative direction Median Error (NME): -0.044] compared to the standard WQS without the penalization term (PME: -0.227; NME: 0.215). In the case study, WQS with two indices was able to find a significant effect of nutrients on obesity in both directions identifying sodium and magnesium as the main actors in the positive and negative association, respectively.DiscussionThrough this work, we introduced an extension of WQS regression that improved the accuracy of the parameter estimates when considering a mixture of elements that can have both a protective and a harmful effect on the outcome; and the advantage of adding a penalization term when estimating the weights.
| S-EPMC10392701 | biostudies-literature
Project description: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.
| S-EPMC7827322 | biostudies-literature
Project description:In risk evaluation, the effect of mixtures of environmental chemicals on a common adverse outcome is of interest. However, due to the high dimensionality and inherent correlations among chemicals that occur together, the traditional methods (e.g. ordinary or logistic regression) suffer from collinearity and variance inflation, and shrinkage methods have limitations in selecting among correlated components. We propose a weighted quantile sum (WQS) approach to estimating a body burden index, which identifies "bad actors" in a set of highly correlated environmental chemicals. We evaluate and characterize the accuracy of WQS regression in variable selection through extensive simulation studies through sensitivity and specificity (i.e., ability of the WQS method to select the bad actors correctly and not incorrect ones). We demonstrate the improvement in accuracy this method provides over traditional ordinary regression and shrinkage methods (lasso, adaptive lasso, and elastic net). Results from simulations demonstrate that WQS regression is accurate under some environmentally relevant conditions, but its accuracy decreases for a fixed correlation pattern as the association with a response variable diminishes. Nonzero weights (i.e., weights exceeding a selection threshold parameter) may be used to identify bad actors; however, components within a cluster of highly correlated active components tend to have lower weights, with the sum of their weights representative of the set.
| S-EPMC6261506 | biostudies-literature
Project description:Per- and poly-fluoroalkyl substances (PFAS) are chemicals, detected in 95% of Americans, that induce osteotoxicity and modulate hormones, thereby influencing bone health. Previous studies found associations between individual PFAS and bone mineral density in adults but did not analyze their combined effects.ObjectiveTo extend weighted quantile sum (WQS) regression to a Bayesian framework (Bayesian extension of the WQS regression [BWQS]) and determine the association between a mixture of serum PFAS and mineral density in lumbar spine, total, and neck femur in 499 adults from the 2013 to 2014 National Health and Nutrition Examination Survey (NHANES).MethodsWe used BWQS to assess the combined association of eight PFAS, as a mixture, with bone mineral density in adults. As secondary analyses, we focused on vulnerable populations (men over 50 years and postmenopausal women). Analyses were adjusted for sociodemographic factors. Sensitivity analyses included bone mineral density associations with individual compounds and results from WQS regressions.ResultsThe mean age was 55 years old (SD = 1) with average spine, total, and neck femur mineral densities of 1.01 (SD = 0.01), 0.95 (SD = 0.01), and 0.78 (SD = 0.01) gm/cm2, respectively. PFAS mixture levels showed no evidence of association with mineral density (spine: β = -0.004; 95% credible interval [CrI] = -0.04, 0.04; total femur: β = 0.002; 95% CrI = -0.04, 0.05; femur neck: β = 0.005; 95%CrI = -0.03, 0.04) in the overall population. Results were also null in vulnerable populations. Findings were consistent across sensitivity analyses.ConclusionsWe introduced a Bayesian extension of WQS and found no evidence of the association between PFAS mixture and bone mineral density.
| S-EPMC7289141 | biostudies-literature
Project description:IntroductionPhthalates are a group of high production chemicals, generally used as plasticizers and odor enhancers. Phthalates cross the blood-placenta barrier and are associated with deficits in cognitive functions and behavior problems in offspring. We previously reported sex-specific associations with motor function when phthalates are considered singly. Because exposure to phthalates usually occurs as mixtures, here we assess these associations between a mixture of phthalates and motor function at age 11 years.MethodsData come from the prospective cohort study of mothers and offspring who participated in the Columbia Center for Children's Environmental Health birth cohort (CCCEH). Seven phthalate metabolites were measured in maternal spot urine obtained during the third trimester and motor function was evaluated using the short form of the Bruininks-Oseretsky Test of Motor Proficiency, 2nd edition (BOT-2) at the age of 11 years. We used Weighted Quartile Sum (WQS) regression models to examine the effect of phthalate metabolites in males and females separately. The models were adjusted for child age in months, child BMI, maternal race (African-American vs. Dominican), prenatal alcohol consumption, maternal demoralization score, HOME score, and urine specific gravity. In a secondary analysis we used linear regression models to examine the association between the sum of molar concentrations of both DEHP and non-DEHP metabolites, and outcomes of gross and fine motor functions.Results209 mother-child pairs were eligible for this analysis. A significant decrease in fine-motor functions was observed among females, but not among males, following exposure to high levels of weighted quartile sum of seven phthalate metabolites (Covariates-adjusted coefficient estimate B = -2.7, 95% Confidence Interval [CI] -4.64 to -0.75, p = 0.01 for females [n = 116] and B = -1.63, 95%CI -3.94 to 0.69, p = 0.16 for males [n = 93]). The most highly weighted phthalate metabolites, associated with fine-motor functions among females, were MBP, MBZP, and MIBP, all non-DEHP phthalates. No significant associations were found between the weighted quartile sum of seven phthalate metabolites and gross-motor functions at the age of 11 years for males (B = -0.81, 95%CI -1.17 to 1.96, p = 0.23). With the molar sum of four non-DEHP phthalates as main predictor of linear regression models, we found significant decrease in gross and fine motor functions among females prenatally exposed to non-DEHP phthalates B = -0.98, 95%CI -1.98 to 0.03, p = 0.05 and B = -0.85, 95%CI -1.49 to -0.20, p = 0.01, respectively).ConclusionsPhthalate exposure during pregnancy was associated with decreased motor functions among 11-year-old girls.
| S-EPMC7023995 | biostudies-literature
Project description:Serum PCB congener concentrations were measured in 602 adults living near a PCB pollution source in eastern Slovakia. We created isoconcentration maps for 21 PCB congeners by geocoding each participant's place of residence and kriging. Concentrations of PCB congeners were inversely associated with the distance of the participants' residence from the source of pollution. Congener-specific risk factors were derived, particularly for PCBs 52 and 153. We observed that the spatial distribution of serum concentrations was influenced by micro-climatic parameters and physicochemical properties of the congeners. PCB congener profiles strongly correlated with that of the PCB commercial product Delor 106, which was manufactured in the region. The isoconcentration maps indicate that the zones with the highest predicted congener concentration have a mean area of approximately 235.75±188.56km2 and the mean enrichment of concentration of congeners in serum in these zones is about 5.12±1.36. We estimate that depending on congener approximately 23,457±18,762 individuals with PCB concentrations exceeding health-based guidance values live in these zones.
| S-EPMC6246788 | biostudies-literature
Project description:There is a growing demand for methods to determine the effects that chemical mixtures have on human health. One statistical challenge is identifying true "bad actors" from a mixture of highly correlated predictors, a setting in which standard approaches such as linear regression become highly variable. Weighted Quantile Sum regression has been proposed to address this problem, through a two-step process where mixture component weights are estimated using bootstrap aggregation in a training dataset and inference on the overall mixture effect occurs in a held-out test set. Weighted Quantile Sum regression is popular in applied papers, but the reliance on data splitting is suboptimal, and analysts who use the same data for both steps risk inflating the Type I error rate. We therefore propose a modification of Weighted Quantile Sum regression that uses a permutation test for inference, which allows for weight estimation using the entire dataset and preserves Type I error. To minimize computational burden, we propose replacing the bootstrap with L1 or L2 penalization and describe how to choose the appropriate penalty given expert knowledge about a mixture of interest. We apply our method to a national pregnancy cohort study of prenatal phthalate exposure and child health outcomes.
| S-EPMC9883011 | biostudies-literature
Project description:BackgroundPCB contamination in the built environment may result from the release of PCBs from building materials. The significance of this contamination as a pathway of human exposure is not well-characterized, however. This research compared the serum PCB concentrations, and congener profiles between 18 teachers in PCB-containing schools and referent populations.MethodsBlood samples from 18 teachers in PCB-containing schools were analyzed for 57 PCB congeners. Serum PCB concentrations and congener patterns were compared between the teachers, to the 2003-4 NHANES (National Health and Nutrition Examination Survey) data, and to data from 358 Greater Boston area men.ResultsTeachers at one school had higher levels of lighter (PCB 6-74) congeners compared to teachers from other schools. PCB congener 47 contributed substantially to these elevated levels. Older teachers (ages 50-64) from all schools had higher total (sum of 33 congeners) serum PCB concentrations than age-comparable NHANES reference values. Comparing the teachers to the referent population of men from the Greater Boston area (all under age 51), no difference in total serum PCB levels was observed between the referents and teachers up to 50 years age. However, the teachers had significantly elevated serum concentrations of lighter congeners (PCB 6-74). This difference was confirmed by comparing the congener-specific ratios between groups, and principal component analysis showed that the relative contribution of lighter congeners differed between the teachers and the referents.ConclusionsThese findings suggest that the teachers in the PCB-containing buildings had higher serum levels of lighter PCB congeners (PCB 6-74) than the referent populations. Examination of the patterns, as well as concentrations of individual PCB congeners in serum is essential to investigating the contributions from potential environmental sources of PCB exposure.
| S-EPMC3136408 | biostudies-literature
Project description:Standard randomization-based inference conditions on the data in the population and makes inference with respect to the repeating sampling properties of the sampling indicators. In some settings these estimators can be quite unstable; Bayesian model-based approaches focus on the posterior predictive distribution of population quantities, potentially providing a better balance between bias correction and efficiency. Previous work in this area has focused on estimation of means and linear and generalized linear regression parameters; these methods do not allow for a general estimation of distributional functions such as quantile or quantile regression parameters. Here we adapt an extended Dirichlet Process Mixture model that allows the DP prior to be a mixture of DP random basis measures that are a function of covariates. These models allow many mixture components when necessary to accommodate the sample design, but can shrink to few components for more efficient estimation when the data allow. We provide an application to the estimation of relationships between serum dioxin levels and age in the US population, either at the mean level (via linear regression) or across the dioxin distribution (via quantile regression) using the National Health and Nutrition Examination Survey.
| S-EPMC8415180 | biostudies-literature