Bacterial and cytokine mixtures predict the length of gestation and are associated with miRNA expression in the cervix

AIM

Bacterial vaginosis may lead to preterm birth through epigenetic programming of the inflammatory response, specifically via miRNA expression.

METHODS

We quantified bacterial 16S rRNA, cytokine mRNA and 800 miRNA from cervical swabs obtained from 80 women at 16-19 weeks' gestation. We generated bacterial and cytokine indices using weighted quantile sum regression and examined associations with miRNA and gestational age at delivery.

RESULTS & DISCUSSION

Each decile of the bacterial and cytokine indices was associated with shorter gestations (p < 0.005). The bacterial index was associated with miR-494, 371a, 4286, 185, 320e, 888 and 23a (p < 0.05). miR-494 remained significant after false discovery rate correction (q < 0.1). The cytokine index was associated with 27 miRNAs (p < 0.05; q < 0.01).

CONCLUSION

Future investigation into the role of bacterial vaginosis- and inflammation-associated miRNA and preterm birth is warranted.

Statistical Approaches for Assessing Health Effects of Environmental Chemical Mixtures in Epidemiology: Lessons from an Innovative Workshop

Quantifying the impact of exposure to environmental chemical mixtures is important for identifying risk factors for diseases and developing more targeted public health interventions. The National Institute of Environmental Health Sciences (NIEHS) held a workshop in July 2015 to address the need to develop novel statistical approaches for multi-pollutant epidemiology studies. The primary objective of the workshop was to identify and compare different statistical approaches and methods for analyzing complex chemical mixtures data in both simulated and real-world data sets. At the workshop, participants compared approaches and results and speculated as to why they may have differed. Several themes emerged: a) no one statistical approach appeared to outperform the others, b) many methods included some form of variable reduction or summation of the data before statistical analysis, c) the statistical approach should be selected based upon a specific hypothesis or scientific question, and d) related mixtures data should be shared among researchers to more comprehensively and accurately address methodological questions and statistical approaches. Future efforts should continue to design and optimize statistical approaches to address questions about chemical mixtures in epidemiological studies.

A Statistical Approach to the Construction and Analysis of Isobolograms

Current statistical procedures used in the construction of isobolograms do not use recent advances in mathematical statistics. The variability in the experimental data is either ignored or incompletely accounted for in the analyses. The decision procedures currently used to characterize the type of interaction between two agents do not permit the determination of the level of statistical significance associated with a given conclusion. Furthermore, the often formidable sample size is not exploited in the current isobologram methodology. Statistical techniques exist that may be used to construct isobolograms and decision procedures with a reliable level of significance. An isobologram is a contour of constant response of the underlying dose-response surface. Consequently, response surface methods (RSM) are useful in the estimation and analysis of isobolograms. The interaction between ethanol and chloral hydrate in female ICR mice was evaluated using the RSM approach by fitting the logistic model to quantal data. The loss of righting reflex was quantitated in mice 30 min after coadministration of the two drugs, injected IP on a body weight basis (mg/kg). The study consisted of 39 groups with 6 animals per group. Analysis of our data supports the conclusion of synergy between the drugs as reported by others; however, our results were obtained with a significantly smaller number of animals. These studies also demonstrate that response surface modeling can be used for determining additivity, synergism, and antagonism at a given preselected level of significance.

Efficacy Comparison of Two Cholinolytics, Scopolamine and Azaprophen, When Used in Conjunction with Physostigmine and Pyridostigmine for Protection Against Organophosphate Exposure

Pretreatment with either pyridostigmine (PYR) or physostigmine (PHY) followed by atropineoxime therapy is very effective in reducing the lethality of organophosphorus nerve agents. The therapeutic efficacy of scopolamine (SCP) versus azaprophen (AZA), when used in conjunction with PHY and PYR (PHY/PYR) combination pretreatment, was evaluated in guinea pigs challenged with 2 half-lethal doses of soman. Maximum postsoman decrement of rotarod performance was measured. Response surface methodology was employed to describe the relationship between the decrement and the PHY/PYR dosages. Results show that AZA is a more effective pretreatment adjunct at the behavioral deficit-free doses tested, AZA or SCP is as effective with PHY alone as with a PHY/PYR combination. Thus, PYR adds essentially nothing to the carbamate combination against soman-induced behavioral deficit.

Early-life metal exposure and schizophrenia: A proof-of-concept study using novel tooth-matrix biomarkers

BACKGROUND

Despite evidence for the effects of metals on neurodevelopment, the long-term effects on mental health remain unclear due to methodological limitations. Our objective was to determine the feasibility of studying metal exposure during critical neurodevelopmental periods and to explore the association between early-life metal exposure and adult schizophrenia.

METHODS

We analyzed childhood-shed teeth from nine individuals with schizophrenia and five healthy controls. We investigated the association between exposure to lead (Pb(2+)), manganese (Mn(2+)), cadmium (Cd(2+)), copper (Cu(2+)), magnesium (Mg(2+)), and zinc (Zn(2+)), and schizophrenia, psychotic experiences, and intelligence quotient (IQ). We reconstructed the dose and timing of early-life metal exposures using laser ablation inductively coupled plasma mass spectrometry.

RESULTS

We found higher early-life Pb(2+) exposure among patients with schizophrenia than controls. The differences in log Mn(2+) and log Cu(2+) changed relatively linearly over time to postnatal negative values. There was a positive correlation between early-life Pb(2+) levels and psychotic experiences in adulthood. Moreover, we found a negative correlation between Pb(2+) levels and adult IQ.

CONCLUSIONS

In our proof-of-concept study, using tooth-matrix biomarker that provides direct measurement of exposure in the fetus and newborn, we provide support for the role of metal exposure during critical neurodevelopmental periods in psychosis.

Telephone based cognitive-behavioral screening for frontotemporal changes in patients with amyotrophic lateral sclerosis (ALS)

Our objective was to establish a valid and reliable battery of measures to evaluate frontotemporal dementia (FTD) in patients with ALS over the telephone. Thirty-one subjects were administered either in-person or by telephone-based screening followed by the opposite mode of testing two weeks later, using a modified version of the UCSF Cognitive Screening Battery. Equivalence testing was performed for in-person and telephone based tests. The standard ALS Cognitive Behavioral Screen (ALS-CBS) showed statistical equivalence at the 5% significance level compared to a revised phone version of the ALS-CBS. In addition, the Controlled Oral Word Association Test (COWAT) and Center for Neurologic Study-Lability Scale (CNS-LS) were also found to be equivalent at the 5% and 10% significance level, respectively. Similarly, the Mini-Mental State Examination (MMSE) and the well-established Telephone Interview for Cognitive Status (TICS) were also statistically equivalent. Equivalence could not be claimed for the ALS-Frontal Behavioral Inventory (ALS-FBI) caregiver interview and the Written Verbal Fluency Index (WVFI). In conclusion, our study suggests that telephone-based versions of the ALS-CBS, COWAT, and CNS-LS may offer clinicians valid tools to detect frontotemporal changes in the ALS population. Development of telephone based cognitive testing for ALS could become an integral resource for population based research in the future.

Validation of a Food Frequency Questionnaire for Estimating Micronutrient Intakes in an Urban US Sample of Multi-Ethnic Pregnant Women

OBJECTIVE(S)

To validate the Block98 food frequency questionnaire (FFQ) for estimating antioxidant, methyl-nutrient and polyunsaturated fatty acids (PUFA) intakes in a pregnant sample of ethnic/racial minority women in the United States (US).

METHODS

Participants (n = 42) were from the Programming of Intergenerational Stress Mechanisms study. Total micronutrient intakes from food and supplements was ascertained using the modified Block98 FFQ and two 24-h dietary recalls collected at random on nonconsecutive days subsequent to completion of the FFQ in mid-pregnancy. Correlation coefficients (r) corrected for attenuation from within-person variation in the recalls were calculated for antioxidants (n = 7), methyl-nutrients (n = 8), and PUFAs (n = 2).

RESULT(S)

The sample was largely ethnic minorities (38 % Black, 33 % Hispanic) with 21 % being foreign born and 41 % having less than or equal to a high school degree. Significant and adequate deattenuated correlations (r ≥ 0.40) for total dietary intakes of antioxidants were observed for vitamin C, vitamin E, magnesium, and zinc. Reasonable deattenuated correlations were also observed for methyl-nutrient intakes of vitamin B6, betaine, iron, and n:6 PUFAs; however, they did not reach significance. Most women were classified into the same or adjacent quartiles (≥70 %) for total (dietary + supplements) estimates of antioxidants (5 out of 7) and methyl-nutrients (4 out of 5).

CONCLUSIONS

The Block98 FFQ is an appropriate dietary method for evaluating antioxidants in pregnant ethnic/minorities in the US; it may be less efficient in measuring methyl-nutrient and PUFA intakes.

What Can Epidemiological Studies Tell Us about the Impact of Chemical Mixtures on Human Health?

Humans are exposed to a large number of environmental chemicals: Some of these may be toxic, and many others have unknown or poorly characterized health effects. There is intense interest in determining the impact of exposure to environmental chemical mixtures on human health. As the study of mixtures continues to evolve in the field of environmental epidemiology, it is imperative that we understand the methodologic challenges of this research and the types of questions we can address using epidemiological data. In this article, we summarize some of the unique challenges in exposure assessment, statistical methods, and methodology that epidemiologists face in addressing chemical mixtures. We propose three broad questions that epidemiological studies can address: a) What are the potential health impacts of individual chemical agents? b) What is the interaction among agents? And c) what are the health effects of cumulative exposure to multiple agents? As the field of mixtures research grows, we can use these three questions as a basis for defining our research questions and for developing methods that will help us better understand the effect of chemical exposures on human disease and well-being.

Lifetime exposure to traumatic and other stressful life events and hair cortisol in a multi-racial/ethnic sample of pregnant women

We examined whether lifetime exposure to stressful and traumatic events alters hypothalamic-pituitary-adrenal (HPA) axis functioning, as indexed by hair cortisol, regardless of associated psychopathology, among pregnant women of different racial/ethnic backgrounds. 180 women provided hair samples for measurement of integrated cortisol levels throughout pregnancy and information regarding their lifetime exposure to stressful and traumatic life events. Results indicate that increased lifetime exposure to traumatic events was associated with significantly greater hair cortisol over the course of pregnancy. Similarly, greater lifetime exposure to stressful and traumatic events weighted by reported negative impact (over the previous 12 months) was associated with significantly greater hair cortisol during pregnancy. All analyses controlled for maternal age, education, body mass index (BMI), use of inhaled corticosteroids, race/ethnicity, and post-traumatic stress disorder (PTSD) and depressive symptoms. Following stratification by race/ethnicity, associations between stressful and traumatic life events and hair cortisol were found among Black women only. This is the first study to consider associations between lifetime stress exposures and hair cortisol in a sociodemographically diverse sample of pregnant women. Increased exposure to stressful and traumatic events, independent of PTSD and depressive symptoms, was associated with higher cortisol production, particularly in Black women. Future research should investigate the influence of such increased cortisol exposure on developmental outcomes among offspring.

CO-occurring exposure to perchlorate, nitrate and thiocyanate alters thyroid function in healthy pregnant women

BACKGROUND

Adequate maternal thyroid function during pregnancy is necessary for normal fetal brain development, making pregnancy a critical window of vulnerability to thyroid disrupting insults. Sodium/iodide symporter (NIS) inhibitors, namely perchlorate, nitrate, and thiocyanate, have been shown individually to competitively inhibit uptake of iodine by the thyroid. Several epidemiologic studies examined the association between these individual exposures and thyroid function. Few studies have examined the effect of this chemical mixture on thyroid function during pregnancy

OBJECTIVES

We examined the cross sectional association between urinary perchlorate, thiocyanate and nitrate concentrations and thyroid function among healthy pregnant women living in New York City using weighted quantile sum (WQS) regression.

METHODS

We measured thyroid stimulating hormone (TSH) and free thyroxine (FreeT4) in blood samples; perchlorate, thiocyanate, nitrate and iodide in urine samples collected from 284 pregnant women at 12 (±2.8) weeks gestation. We examined associations between urinary analyte concentrations and TSH or FreeT4 using linear regression or WQS adjusting for gestational age, urinary iodide and creatinine.

RESULTS

Individual analyte concentrations in urine were significantly correlated (Spearman's r 0.4-0.5, p<0.001). Linear regression analyses did not suggest associations between individual concentrations and thyroid function. The WQS revealed a significant positive association between the weighted sum of urinary concentrations of the three analytes and increased TSH. Perchlorate had the largest weight in the index, indicating the largest contribution to the WQS.

CONCLUSIONS

Co-exposure to perchlorate, nitrate and thiocyanate may alter maternal thyroid function, specifically TSH, during pregnancy.

Analysis of Environmental Chemical Mixtures and Non-Hodgkin Lymphoma Risk in the NCI-SEER NHL Study

BACKGROUND

There are several suspected environmental risk factors for non-Hodgkin lymphoma (NHL). The associations between NHL and environmental chemical exposures have typically been evaluated for individual chemicals (i.e., one-by-one).

OBJECTIVES

We determined the association between a mixture of 27 correlated chemicals measured in house dust and NHL risk.

METHODS

We conducted a population-based case-control study of NHL in four National Cancer Institute-Surveillance, Epidemiology, and End Results centers--Detroit, Michigan; Iowa; Los Angeles County, California; and Seattle, Washington--from 1998 to 2000. We used weighted quantile sum (WQS) regression to model the association of a mixture of chemicals and risk of NHL. The WQS index was a sum of weighted quartiles for 5 polychlorinated biphenyls (PCBs), 7 polycyclic aromatic hydrocarbons (PAHs), and 15 pesticides. We estimated chemical mixture weights and effects for study sites combined and for each site individually, and also for histologic subtypes of NHL.

RESULTS

The WQS index was statistically significantly associated with NHL overall [odds ratio (OR) = 1.30; 95% CI: 1.08, 1.56; p = 0.006; for one quartile increase] and in the study sites of Detroit (OR = 1.71; 95% CI: 1.02, 2.92; p = 0.045), Los Angeles (OR = 1.44; 95% CI: 1.00, 2.08; p = 0.049), and Iowa (OR = 1.76; 95% CI: 1.23, 2.53; p = 0.002). The index was marginally statistically significant in Seattle (OR = 1.39; 95% CI: 0.97, 1.99; p = 0.071). The most highly weighted chemicals for predicting risk overall were PCB congener 180 and propoxur. Highly weighted chemicals varied by study site; PCBs were more highly weighted in Detroit, and pesticides were more highly weighted in Iowa.

CONCLUSIONS

An index of chemical mixtures was significantly associated with NHL. Our results show the importance of evaluating chemical mixtures when studying cancer risk.

Development and Validation of a Clinical Risk-Assessment Tool Predictive of All-Cause Mortality

In clinical settings, the diagnosis of medical conditions is often aided by measurement of various serum biomarkers through the use of laboratory tests. These biomarkers provide information about different aspects of a patient's health and overall function of multiple organ systems. We have developed a statistical procedure that condenses the information from a variety of health biomarkers into a composite index, which could be used as a risk score for predicting all-cause mortality. It could also be viewed as a holistic measure of overall physiological health status. This health status metric is computed as a function of standardized values of each biomarker measurement, weighted according to their empirically determined relative strength of association with mortality. The underlying risk model was developed using the biomonitoring and mortality data of a large sample of US residents obtained from the National Health and Nutrition Examination Survey (NHANES) and the National Death Index (NDI). Biomarker concentration levels were standardized using spline-based Cox regression models, and optimization algorithms were used to estimate the weights. The predictive accuracy of the tool was optimized by bootstrap aggregation. We also demonstrate how stacked generalization, a machine learning technique, can be used for further enhancement of the prediction power. The index was shown to be highly predictive of all-cause mortality and long-term outcomes for specific health conditions. It also exhibited a robust association with concurrent chronic conditions, recent hospital utilization, and current health status as assessed by self-rated health.

Childhood abuse is associated with increased hair cortisol levels among urban pregnant women

BACKGROUND

Hypothalamic-pituitary-adrenal (HPA) axis activity is known to be altered following events such as childhood abuse. However, despite potential adverse consequences for the offspring of women who have experienced abuse, very little is known about altered HPA axis activity during pregnancy.

METHODS

During pregnancy, 180 women from diverse racial/ethnic backgrounds reported on their exposure to emotional, physical and/or sexual abuse before the age of 11, and general post-traumatic stress symptoms (ie, not limited to childhood years or abuse experiences). Around delivery, they provided hair samples for the assessment of cortisol levels during pregnancy. Hair cortisol was assessed for each pregnancy trimester. The effect of childhood abuse on hair cortisol was assessed using mixed-effects analyses of covariance models allowing for within-subject correlated observations, and were first performed in the entire sample and subsequently stratified by race/ethnicity.

RESULTS

Controlling for post-traumatic stress symptoms, hair cortisol levels varied by history of child abuse, F(2,166)=3.66, p=0.028. Childhood physical and/or sexual abuse was associated with greater hair cortisol levels, t(166)=2.65, p=0.009, compared with no history of abuse. Because childhood rates of abuse and hair cortisol levels varied by race/ethnicity, analyses were stratified by race/ethnicity. The associations between history of abuse and cortisol levels were only significant among black women, F(2,23)=5.37, p=0.012.

CONCLUSIONS

Childhood abuse, especially physical and/or sexual abuse, is associated with differences in cortisol production during pregnancy, particularly among black women. Future research should investigate how these differences impact physical and mental health outcomes among offspring of affected women.

Assessment of phthalates/phthalate alternatives in children's toys and childcare articles: Review of the report including conclusions and recommendation of the Chronic Hazard Advisory Panel of the Consumer Product Safety Commission

The Consumer Product Safety Commission (CPSC) convened a Chronic Hazard Advisory Panel (CHAP) on Phthalates found in children's toys, and childcare products, and in products used by women of childbearing age. The CHAP conducted a risk assessment on phthalates and phthalate substitutes, and made recommendations to either ban, impose an interim ban, or allow the continued use of phthalates and phthalate substitutes in the above products. After a review of the literature, the evaluation included toxic end points of primary concern, biomonitoring results, extant exposure reconstruction, and epidemiological results. The health end points chosen were associated with the rat phthalate syndrome, which is characterized by malformations of the epididymis, vas deferens, seminal vesicles, prostate, external genitalia (hypospadias), and by cryptorchidism (undescended testes), retention of nipples/areolae, and demasculinization (~incomplete masculinization) of the perineum, resulting in reduced anogenital distance. Risk assessment demonstrated that some phthalates should be permanently banned, removed from the banned list, or remain interim banned. Biomonitoring and toxicology data provided the strongest basis for a mixture risk assessment. In contrast, external exposure data were the weakest and need to be upgraded for epidemiological studies and risk assessments. Such studies would focus on routes and sources. The review presents recommendations and uncertainties.

Selecting spatial scale of covariates in regression models of environmental exposures

Environmental factors or socioeconomic status variables used in regression models to explain environmental chemical exposures or health outcomes are often in practice modeled at the same buffer distance or spatial scale. In this paper, we present four model selection algorithms that select the best spatial scale for each buffer-based or area-level covariate. Contamination of drinking water by nitrate is a growing problem in agricultural areas of the United States, as ingested nitrate can lead to the endogenous formation of N-nitroso compounds, which are potent carcinogens. We applied our methods to model nitrate levels in private wells in Iowa. We found that environmental variables were selected at different spatial scales and that a model allowing spatial scale to vary across covariates provided the best goodness of fit. Our methods can be applied to investigate the association between environmental risk factors available at multiple spatial scales or buffer distances and measures of disease, including cancers.

Assessment of weighted quantile sum regression for modeling chemical mixtures and cancer risk

In evaluation of cancer risk related to environmental chemical exposures, the effect of many chemicals on disease is ultimately of interest. However, because of potentially strong correlations among chemicals that occur together, traditional regression methods suffer from collinearity effects, including regression coefficient sign reversal and variance inflation. In addition, penalized regression methods designed to remediate collinearity may have limitations in selecting the truly bad actors among many correlated components. The recently proposed method of weighted quantile sum (WQS) regression attempts to overcome these problems by estimating a body burden index, which identifies important chemicals in a mixture of correlated environmental chemicals. Our focus was on assessing through simulation studies the accuracy of WQS regression in detecting subsets of chemicals associated with health outcomes (binary and continuous) in site-specific analyses and in non-site-specific analyses. We also evaluated the performance of the penalized regression methods of lasso, adaptive lasso, and elastic net in correctly classifying chemicals as bad actors or unrelated to the outcome. We based the simulation study on data from the National Cancer Institute Surveillance Epidemiology and End Results Program (NCI-SEER) case–control study of non-Hodgkin lymphoma (NHL) to achieve realistic exposure situations. Our results showed that WQS regression had good sensitivity and specificity across a variety of conditions considered in this study. The shrinkage methods had a tendency to incorrectly identify a large number of components, especially in the case of strong association with the outcome.

Evaluating geographically weighted regression models for environmental chemical risk analysis

In the evaluation of cancer risk related to environmental chemical exposures, the effect of many correlated chemicals on disease is often of interest. The relationship between correlated environmental chemicals and health effects is not always constant across a study area, as exposure levels may change spatially due to various environmental factors. Geographically weighted regression (GWR) has been proposed to model spatially varying effects. However, concerns about collinearity effects, including regression coefficient sign reversal (ie, reversal paradox), may limit the applicability of GWR for environmental chemical risk analysis. A penalized version of GWR, the geographically weighted lasso, has been proposed to remediate the collinearity effects in GWR models. Our focus in this study was on assessing through a simulation study the ability of GWR and GWL to correctly identify spatially varying chemical effects for a mixture of correlated chemicals within a study area. Our results showed that GWR suffered from the reversal paradox, while GWL overpenalized the effects for the chemical most strongly related to the outcome.

Phenotypic and molecular analyses of primary lateral sclerosis

OBJECTIVE

To understand phenotypic and molecular characteristics of patients with clinically "definite" primary lateral sclerosis (PLS) in a prospective study.

METHODS

Six sites enrolled 41 patients who had pure upper motor neuron dysfunction, bulbar symptoms, a normal EMG done within 12 months of enrollment, and onset of symptoms ≥5 years before enrollment. For phenotypic analyses, 27 demographic, clinical, and cognitive variables were analyzed using the k-means clustering method. For molecular studies, 34 available DNA samples were tested for the C9ORF72 mutation, and exome sequencing was performed to exclude other neurologic diseases with known genetic cause.

RESULTS

K-means clustering using the 25 patients with complete datasets suggested that patients with PLS can be classified into 2 groups based on clinical variables, namely dysphagia, objective bulbar signs, and urinary urgency. Secondary analyses performed in all 41 patients and including only variables with complete data corroborated the results from the primary analysis. We found no evidence that neurocognitive variables are important in classifying patients with PLS. Molecular studies identified C9ORF72 expansion in one patient. Well-characterized pathogenic mutations were identified in SPG7, DCTN1, and PARK2. Most cases showed no known relevant mutations.

CONCLUSIONS

Cluster analyses based on clinical variables indicated at least 2 subgroups of clinically definite PLS. Molecular analyses further identified 4 cases with mutations associated with amyotrophic lateral sclerosis, Parkinson disease, and possibly hereditary spastic paraplegia. Phenotypic and molecular characterization is the first step in investigating biological clues toward the definition of PLS. Further studies with larger numbers of patients are essential.

Characterization of Weighted Quantile Sum Regression for Highly Correlated Data in a Risk Analysis Setting

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.

Characterization of Weighted Quantile Sum Regression for Highly Correlated Data in a Risk Analysis Setting

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.

Bioenergetic markers in skin fibroblasts of sporadic amyotrophic lateral sclerosis and progressive lateral sclerosis patients

Energy metabolism could influence amyotrophic lateral sclerosis (ALS) and progressive lateral sclerosis (PLS) pathogenesis and the response to therapy. We developed a novel assay to simultaneously assess mitochondrial content and membrane potential in patients' skin fibroblasts. In ALS and PLS fibroblasts, membrane potential was increased and mitochondrial content decreased, relative to healthy controls. In ALS higher mitochondrial membrane potential correlated with age at diagnosis, and in PLS it correlated with disease severity. These unprecedented findings in ALS and PLS fibroblasts could shed new light onto disease pathogenesis and help in developing biomarkers to predict disease evolution and the individual response to therapy in motor neuron diseases.

An empirical approach to sufficient similarity: combining exposure data and mixtures toxicology data

When assessing risks posed by environmental chemical mixtures, whole mixture approaches are preferred to component approaches. When toxicological data on whole mixtures as they occur in the environment are not available, Environmental Protection Agency guidance states that toxicity data from a mixture considered "sufficiently similar" to the environmental mixture can serve as a surrogate. We propose a novel method to examine whether mixtures are sufficiently similar, when exposure data and mixture toxicity study data from at least one representative mixture are available. We define sufficient similarity using equivalence testing methodology comparing the distance between benchmark dose estimates for mixtures in both data-rich and data-poor cases. We construct a "similar mixtures risk indicator"(SMRI) (analogous to the hazard index) on sufficiently similar mixtures linking exposure data with mixtures toxicology data. The methods are illustrated using pyrethroid mixtures occurrence data collected in child care centers (CCC) and dose-response data examining acute neurobehavioral effects of pyrethroid mixtures in rats. Our method shows that the mixtures from 90% of the CCCs were sufficiently similar to the dose-response study mixture. Using exposure estimates for a hypothetical child, the 95th percentile of the (weighted) SMRI for these sufficiently similar mixtures was 0.20 (i.e., where SMRI <1, less concern; >1, more concern).

A cohort study evaluation of maternal PCB exposure related to time to pregnancy in daughters

BACKGROUND

Polychlorinated biphenyls (PCBs) remain ubiquitous environmental contaminants. Developmental exposures are suspected to impact reproduction. Analysis of mixtures of PCBs may be problematic as components have a complex correlation structure, and along with limited sample sizes, standard regression strategies are problematic. We compared the results of a novel, empirical method to those based on categorization of PCB compounds by (1) hypothesized biological activity previously proposed and widely applied, and (2) degree of ortho- substitution (mono, di, tri), in a study of the relation of maternal serum PCBs and daughter's time to pregnancy.

METHODS

We measured PCBs in maternal serum samples collected in the early postpartum in 289 daughters in the Child Health and Development Studies birth cohort. We queried time to pregnancy in these daughters 28-31 years later. We applied a novel weighted quantile sum approach to find the bad-actor compounds in the PCB mixture found in maternal serum. The approach includes empirical estimation of the weights through a bootstrap step which accounts for the variation in the estimated weights.

RESULTS

Bootstrap analyses indicated the dominant functionality groups associated with longer TTP were the dioxin-like, anti-estrogenic group (average weight, 22%) and PCBs not previously classified by biological activity (54%). In contrast, the unclassified PCBs were not important in the association with shorter TTP, where the anti-estrogenic groups and the PB-inducers group played a more important role (60% and 23%, respectively). The highly chlorinated PCBs (average weight, 89%) were mostly associated with longer TTP; in contrast, the degree of chlorination was less discriminating for shorter TTP. Finally, PCB 56 was associated with the strongest relationship with TTP with a weight of 47%.

CONCLUSIONS

Our empirical approach found some associations previously identified by two classification schemes, but also identified other bad actors. This empirical method can generate hypotheses about mixture effects and mechanisms and overcomes some of the limitations of standard regression techniques.