A computational approach to chemical etiologies of diabetes

Long-term arsenic exposure decreases mice body weight and liver lipid droplets

Arsenic (As) is a widespread global pollutant, and there is significant controversy surrounding its complex relationship with obesity, primarily focused on short-term exposure. Recognizing the prolonged nature of dietary arsenic exposure, this study involved feeding mice with arsenic-contained food for 14 months. The results showed that mice exposed to arsenic developed a non-alcoholic fatty liver condition, characterized by a light-yellow hue on the liver surface and various pathological alterations in the liver cells, including enlarged nuclei, cellular necrosis, inflammatory infiltration, dysfunctional mitochondria, and endoplasmic reticulum disorganization. There were also disruptions in biochemistry indices, with a significant increase in total cholesterol (TC) level and a decrease in high-density lipoprotein (HDL) level. However, some contradictory observations occurred, such as a significant decrease in body weight, triglyceride (TG) level, and the numbers of lipid droplets. Several genes related to lipid metabolism were tested, and a model was used to explain these discrepancies. Besides, examinations of the colon revealed compromised intestinal barrier function and signs of inflammation. Fecal 16S rRNA sequencing and pseudo-targeted metabolomics revealed disruptions in internal homeostasis, such as modules, nodes, connections, and lipid-related KEGG pathways. Fecal targeted metabolomics analyses of short-chain fatty acids (SCFAs) and bile acids (BAs) demonstrated a significant upregulation in three primary bile acids (CA, CDCA, TCDCA), four secondary bile acids (TUDCA, DCA, LCA, GUDCA), and total SCFAs level. Oxidative stress and inflammation were also evident. Additionally, based on correlation analysis and mediation analysis, it was assumed that changes in the microbiota (e.g., Dubosiella) can impact the liver metabolites (e.g., TGs) through alterations in fecal metabolites (e.g., LPCs). These findings provide a theoretical reference for the long-term effect of arsenic exposure on liver lipid metabolism.

NMR metabolomics study of chronic low-dose exposure to a cocktail of persistent organic pollutants

Nowadays, exposure to endocrine-disrupting chemicals (EDCs), including persistent organic pollutants (POPs), is one of the most critical threats to public health. EDCs are chemicals that mimic, block, or interfere with hormones in the body's endocrine system and have been associated with a wide range of health issues. This innovative, untargeted metabolomics study investigates chronic low-dose internal exposure to a cocktail of POPs on multiple tissues that are known to accumulate these lipophilic compounds. Interestingly, the metabolic response differs among selected tissues/organs in mice. In the liver, we observed a dynamic effect according to the exposure time and the doses of POPs. In the brain tissue, the situation is the opposite, leading to the conclusion that the presence of POPs immediately gives a saturated effect that is independent of the dose and the duration of exposure studied. By contrast, for the adipose tissues, nearly no effect is observed. This metabolic profiling leads to a holistic and dynamic overview of the main metabolic pathways impacted in lipophilic tissues by a cocktail of POPs.

The association between chemical constituents of ambient fine particulate matter and obesity in adults: A large population-based cohort study

OBJECTIVES

Current evidence demonstrated that ambient fine particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5) and its constituents may be obesogenic in children, but evidence from adults is lacking. Our aim was to characterize the association between PM2.5 and its constituents and obesity in adults.

METHODS

We included 68,914 participants from the China Multi-Ethnic Cohort (CMEC) baseline survey. Three-year average concentrations of PM2.5 and its constituents were evaluated by linking pollutant estimates to the geocoded residential addresses. Obesity was defined as body mass index (BMI) ≥ 28 kg/m2. Logistic regression was used to examine the relationship between PM2.5 and its constituents and obesity. We performed weighed quantile sum (WQS) regression to get the overall effect of PM2.5 and its constituents and the relative contribution of each constituent.

RESULTS

Per-SD increase in PM2.5 (odds ratio [OR] = 1.43, 95% confidence interval [CI]: 1.37-1.49), black carbon (BC) (1.42, 1.36-1.48), ammonium (1.43, 1.37-1.49), nitrate (1.44, 1.38-1.50), organic matter (OM) (1.45, 1.39-1.51), sulfate (1.42, 1.35-1.48), and soil particles (SOIL) (1.31, 1.27-1.36) were positively associated with obesity, and SS (0.60, 0.55-0.65) was negatively associated with obesity. The overall effect (OR = 1.34, 95% CI: 1.29-1.41) of the PM2.5 and its constituents was positively associated with obesity, and ammonium made the most contribution to this relationship. Participants who were older, female, never smoked, lived in urban areas, had lower income or higher levels of physical activity were more significantly adversely affected by PM2.5, BC, ammonium, nitrate, OM, sulfate and SOIL compared to other individuals.

CONCLUSION

Our study revealed that PM2.5 constituents except SS were positively associated with obesity, and ammonium played the most important role. These findings provided new evidence for public health interventions, especially the precise prevention and control of obesity.

Gene-environment interactions in the associations of PFAS exposure with insulin sensitivity and beta-cell function in a Faroese cohort followed from birth to adulthood

BACKGROUND

Exposure to perfluoroalkyl substances (PFAS) has been associated with changes in insulin sensitivity and pancreatic beta-cell function in humans. Genetic predisposition to diabetes may modify these associations; however, this hypothesis has not been yet studied.

OBJECTIVES

To evaluate genetic heterogeneity as a modifier in the PFAS association with insulin sensitivity and pancreatic beta-cell function, using a targeted gene-environment (GxE) approach.

METHODS

We studied 85 single-nucleotide polymorphisms (SNPs) associated with type 2 diabetes, in 665 Faroese adults born in 1986-1987. Perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA) were measured in cord whole blood at birth and in participants' serum from age 28 years. We calculated the Matsuda-insulin sensitivity index (ISI) and the insulinogenic index (IGI) based on a 2 h-oral glucose tolerance test performed at age 28. Effect modification was evaluated in linear regression models adjusted for cross-product terms (PFAS*SNP) and important covariates.

RESULTS

Prenatal and adult PFOS exposures were significantly associated with decreased insulin sensitivity and increased beta-cell function. PFOA associations were in the same direction but attenuated compared to PFOS. A total of 58 SNPs were associated with at least one PFAS exposure variable and/or Matsuda-ISI or IGI in the Faroese population and were subsequently tested as modifiers in the PFAS-clinical outcome associations. Eighteen SNPs showed interaction p-values (PGxE) < 0.05 in at least one PFAS-clinical outcome association, five of which passed False Discovery Rate (FDR) correction (PGxE-FDR<0.20). SNPs for which we found stronger evidence for GxE interactions included ABCA1 rs3890182, FTO rs9939609, FTO rs3751812, PPARG rs170036314 and SLC12A3 rs2289116 and were more clearly shown to modify the PFAS associations with insulin sensitivity, rather than with beta-cell function.

DISCUSSION

Findings from this study suggest that PFAS-associated changes in insulin sensitivity could vary between individuals as a result of genetic predisposition and warrant replication in independent larger populations.

Obesity III: Obesogen assays: Limitations, strengths, and new directions

There is increasing evidence of a role for environmental contaminants in disrupting metabolic health in both humans and animals. Despite a growing need for well-understood models for evaluating adipogenic and potential obesogenic contaminants, there has been a reliance on decades-old in vitro models that have not been appropriately managed by cell line providers. There has been a quick rise in available in vitro models in the last ten years, including commercial availability of human mesenchymal stem cell and preadipocyte models; these models require more comprehensive validation but demonstrate real promise in improved translation to human metabolic health. There is also progress in developing three-dimensional and co-culture techniques that allow for the interrogation of a more physiologically relevant state. While diverse rodent models exist for evaluating putative obesogenic and/or adipogenic chemicals in a physiologically relevant context, increasing capabilities have been identified for alternative model organisms such as Drosophila, C. elegans, zebrafish, and medaka in metabolic health testing. These models have several appreciable advantages, including most notably their size, rapid development, large brood sizes, and ease of high-resolution lipid accumulation imaging throughout the organisms. They are anticipated to expand the capabilities of metabolic health research, particularly when coupled with emerging obesogen evaluation techniques as described herein.

Endocrine disrupting chemicals and COVID-19 relationships: A computational systems biology approach

BACKGROUND

Patients at high risk of severe forms of COVID-19 frequently suffer from chronic diseases, but other risk factors may also play a role. Environmental stressors, such as endocrine disrupting chemicals (EDCs), can contribute to certain chronic diseases and might aggravate the course of COVID-19.

OBJECTIVES

To explore putative links between EDCs and COVID-19 severity, an integrative systems biology approach was constructed and applied.

METHODS

As a first step, relevant data sets were compiled from major data sources. Biological associations of major EDCs to proteins were extracted from the CompTox database. Associations between proteins and diseases known as important COVID-19 comorbidities were obtained from the GeneCards and DisGeNET databases. Based on these data, we developed a tripartite network (EDCs-proteins-diseases) and used it to identify proteins overlapping between the EDCs and the diseases. Signaling pathways for common proteins were then investigated by over-representation analysis.

RESULTS

We found several statistically significant pathways that may be dysregulated by EDCs and that may also be involved in COVID-19 severity. The Th17 and the AGE/RAGE signaling pathways were particularly promising.

CONCLUSIONS

Pathways were identified as possible targets of EDCs and as contributors to COVID-19 severity, thereby highlighting possible links between exposure to environmental chemicals and disease development. This study also documents the application of computational systems biology methods as a relevant approach to increase the understanding of molecular mechanisms linking EDCs and human diseases, thereby contributing to toxicology prediction.

Multiple metal exposure and obesity: A prospective cohort study of adults living along the Yangtze River, China

Association between long-term exposure to multiple metals and obesity remains inconclusive, and prospective evidence on the region along the Yangtze River was limited. Thus, our study aimed to examine the association of multiple metal exposure and obesity. We measured baseline urine levels of 22 metals of 982 adults living along the Yangtze River, incidence of obesity was calculated from body mass index (BMI) and waist circumference (WC) measured at follow-up survey. Cox proportional hazards models were used to examine the hazard ratios (HR) and 95% confidence interval (CI) for the association between urinary metals and obesity, and the mixing effect of metals on obesity was estimated by using quantile g-computation. In multiple-metal models, arsenic was significantly associated with BMI/obesity, with the HR in the highest quartiles of 0.33 (95% CI: 0.16, 0.69; p-trend = 0.004). The HRs for WC/obesity of arsenic and molybdenum were 0.49 (95% CI: 0.32, 0.75 for the fourth vs. first quartile; p-trend = 0.002) and 1.83 (95% CI: 1.25, 2.70; p-trend = 0.001), respectively. Quantile g-computation mixtures approach showed a significantly negative joint effect of multiple metals on WC/obesity, with the HR of 0.26 (95% CI: 0.14, 0.47; p < 0.001) when increasing all seventeen metals by one quartile. Our study suggests that all seventeen metal mixed exposure may be negatively associated with obesity. Further cohort studies are needed to confirm these findings and clarify the underlying biological mechanisms.

In Silico Exploration of the Potential Role of Acetaminophen and Pesticides in the Etiology of Autism Spectrum Disorder

Recent epidemiological studies suggest that prenatal exposure to acetaminophen (APAP) is associated with increased risk of Autism Spectrum Disorder (ASD), a neurodevelopmental disorder affecting 1 in 59 children in the US. Maternal and prenatal exposure to pesticides from food and environmental sources have also been implicated to affect fetal neurodevelopment. However, the underlying mechanisms for ASD are so far unknown, likely with complex and multifactorial etiology. The aim of this study was to explore the potential effects of APAP and pesticide exposure on development with regards to the etiology of ASD by highlighting common genes and biological pathways. Genes associated with APAP, pesticides, and ASD through human research were retrieved from molecular and biomedical literature databases. The interaction network of overlapping genetic associations was subjected to network topology analysis and functional annotation of the resulting clusters. These genes were over-represented in pathways and biological processes (FDR p < 0.05) related to apoptosis, metabolism of reactive oxygen species (ROS), and carbohydrate metabolism. Since these three biological processes are frequently implicated in ASD, our findings support the hypothesis that cell death processes and specific metabolic pathways, both of which appear to be targeted by APAP and pesticide exposure, may be involved in the etiology of ASD. This novel exposures-gene-disease database mining might inspire future work on understanding the biological underpinnings of various ASD risk factors.

Endocrine disrupting chemicals and COVID-19 relationships: a computational systems biology approach

Background

Patients at high risk of severe forms of COVID-19 frequently suffer from chronic diseases, but other risk factors may also play a role. Environmental stressors, such as endocrine disrupting chemicals (EDCs), can contribute to certain chronic diseases and might aggravate the course of COVID-19.

Objectives

To explore putative links between EDCs and COVID-19 severity, an integrative systems biology approach was constructed and applied.

Methods

As a first step, relevant data sets were compiled from major data sources. Biological associations of major EDCs to proteins were extracted from the CompTox database. Associations between proteins and diseases known as important COVID-19 comorbidities were obtained from the GeneCards and DisGeNET databases. Based on these data, we developed a tripartite network (EDCs-proteins-diseases) and used it to identify proteins overlapping between the EDCs and the diseases. Signaling pathways for common proteins were then investigated by over-representation analysis.

Results

We found several statistically significant pathways that may be dysregulated by EDCs and that may also be involved in COVID-19 severity. The Th17 and the AGE/RAGE signaling pathways were particularly promising.

Conclusions

Pathways were identified as possible targets of EDCs and as contributors to COVID-19 severity, thereby highlighting possible links between exposure to environmental chemicals and disease development. This study also documents the application of computational systems biology methods as a relevant approach to increase the understanding of molecular mechanisms linking EDCs and human diseases, thereby contributing to toxicology prediction.

Arsenic Exposure Decreases Adiposity During High-Fat Feeding

OBJECTIVE

Arsenic is an endocrine-disrupting chemical associated with diabetes risk. Increased adiposity is a significant risk factor for diabetes and its comorbidities. Here, the impact of chronic arsenic exposure on adiposity and metabolic health was assessed in mice.

METHODS

Male C57BL/6J mice were provided ad libitum access to a normal or high-fat diet and water +/- 50 mg/L of sodium arsenite. Changes in body weight, body composition, insulin sensitivity, energy expenditure, and locomotor activity were measured. Measures of adiposity were compared with accumulated arsenic in the liver.

RESULTS

Despite uniform arsenic exposure, internal arsenic levels varied significantly among arsenic-exposed mice. Hepatic arsenic levels in exposed mice negatively correlated with overall weight gain, individual adipose depot masses, and hepatic triglyceride accumulation. No effects were observed in mice on a normal diet. For mice on a high-fat diet, arsenic exposure reduced fasting insulin levels, homeostatic model assessment of insulin resistance and β-cell function, and systemic insulin resistance. Arsenic exposure did not alter energy expenditure or activity.

CONCLUSIONS

Collectively, these data indicate that arsenic is antiobesogenic and that concentration at the source poorly predicts arsenic accumulation and phenotypic outcomes. In future studies, investigators should consider internal accumulation of arsenic rather than source concentration when assessing the outcomes of arsenic exposure.

Integrative Strategy of Testing Systems for Identification of Endocrine Disruptors Inducing Metabolic Disorders-An Introduction to the OBERON Project

Exposure to chemical substances that can produce endocrine disrupting effects represents one of the most critical public health threats nowadays. In line with the regulatory framework implemented within the European Union (EU) to reduce the levels of endocrine disruptors (EDs) for consumers, new and effective methods for ED testing are needed. The OBERON project will build an integrated testing strategy (ITS) to detect ED-related metabolic disorders by developing, improving and validating a battery of test systems. It will be based on the concept of an integrated approach for testing and assessment (IATA). OBERON will combine (1) experimental methods (in vitro, e.g., using 2D and 3D human-derived cells and tissues, and in vivo, i.e., using zebrafish at different stages), (2) high throughput omics technologies, (3) epidemiology and human biomonitoring studies and (4) advanced computational models (in silico and systems biology) on functional endpoints related to metabolism. Such interdisciplinary framework will help in deciphering EDs based on a mechanistic understanding of toxicity by providing and making available more effective alternative test methods relevant for human health that are in line with regulatory needs. Data generated in OBERON will also allow the development of novel adverse outcome pathways (AOPs). The assays will be pre-validated in order to select the test systems that will show acceptable performance in terms of relevance for the second step of the validation process, i.e., the inter-laboratory validation as ring tests. Therefore, the aim of the OBERON project is to support the organization for economic co-operation and development (OECD) conceptual framework for testing and assessment of single and/or mixture of EDs by developing specific assays not covered by the current tests, and to propose an IATA for ED-related metabolic disorder detection, which will be submitted to the Joint Research Center (JRC) and OECD community.

Linking Bisphenol S to Adverse Outcome Pathways Using a Combined Text Mining and Systems Biology Approach

BACKGROUND

Available toxicity data can be optimally interpreted if they are integrated using computational approaches such as systems biology modeling. Such approaches are particularly warranted in cases where regulatory decisions have to be made rapidly.

OBJECTIVES

The study aims at developing and applying a new integrative computational strategy to identify associations between bisphenol S (BPS), a substitute for bisphenol A (BPA), and components of adverse outcome pathways (AOPs).

METHODS

The proposed approach combines a text mining (TM) procedure and integrative systems biology to comprehensively analyze the scientific literature to enrich AOPs related to environmental stressors. First, to identify relevant associations between BPS and different AOP components, a list of abstracts was screened using the developed text-mining tool AOP-helpFinder, which calculates scores based on the graph theory to prioritize the findings. Then, to fill gaps between BPS, biological events, and adverse outcomes (AOs), a systems biology approach was used to integrate information from the AOP-Wiki and ToxCast databases, followed by manual curation of the relevant publications.

RESULTS

Links between BPS and 48 AOP key events (KEs) were identified and scored via 31 references. The main outcomes were related to reproductive health, endocrine disruption, impairments of metabolism, and obesity. We then explicitly analyzed co-mention of the terms BPS and obesity by data integration and manual curation of the full text of the publications. Several molecular and cellular pathways were identified, which allowed the proposal of a biological explanation for the association between BPS and obesity.

CONCLUSIONS

By analyzing dispersed information from the literature and databases, our novel approach can identify links between stressors and AOP KEs. The findings associating BPS and obesity illustrate the use of computational tools in predictive toxicology and highlight the relevance of the approach to decision makers assessing substituents to toxic chemicals. https://doi.org/10.1289/EHP4200.

IRS1- rs10498210 G/A and CCR5-59029 A/G polymorphisms in patients with type 2 diabetes in Kurdistan

Background

The insulin receptor substrate 1 (IRS1) is a critical factor in the signaling pathway for insulin, and mutations in this gene have been reported, which contribute to the ability to develop type 2 diabetes. The polymorphisms in the promoter region of C‐C motif chemokine receptor5 (CCR5) are also being studied as candidates for susceptibility to develop type 2 diabetes. The aim of the current study was to determine the relationship between IRS1 and CCR5 polymorphisms with type 2 diabetes in the Kurdistan population.

Methods

Genomic DNA was isolated from the blood by salt extraction method and the polymorphisms were examined using Restriction Fragment Length Polymorphism (RFLP) method.

Results

The results of current study indicated that the frequency of AA genotype in type 2 diabetic patients in both CCR5 (OR = 2.9, p = 0.04) and IRS1 (OR = 3.3, p = 0.036) were significantly more than controls.

Conclusion

According to the results of this study, the presence of AA genotype in both CCR5 and IRS1 is associated with type 2 diabetes. There was no significant association between AG or GG genotypes with type 2 diabetes.

Genetic variants linked to T2DM risk in Kurdish populations

Background: The polymorphisms of the C-C chemokine receptor type 5 (CCR5) and the insulin receptor substrate 1 (IRS1) have been studied as candidates for the susceptibility to develop type 2 diabetes mellitus (T2DM). CCR5 is a chemokine receptor, and the polymorphisms in the promoter region of this receptor are being studied as candidates for the susceptibility to develop T2DM. Also, IRS1 is a critical factor in the signaling pathway for insulin, and mutations in this gene have been reported, which contribute to the ability to develop T2DM. The aim of the current study was to determine the relationship between CCR5 (59029A/G) and IRS1 (rs10498210) polymorphisms with T2DM in Sanandajian patients. Methods: Genomic DNA was isolated from 200 healthy individuals and 220 Kurdish T2DM patients by salt extraction method and the polymorphisms were examined by restriction fragment length polymorphism (RFLP) method and then the results were analyzed using Chi-square test. Results: The frequency of AA genotype in 220 Kurdish patients for both genes CCR5 (OR=1.9, P=0.02) and IRS1 (OR [95% CI]=2.62, P=0.02) were significantly more than controls. There was no significant association between AG or GG genotypes in with T2DM. Conclusion: The presence of AA homozygote alleles in both loci of IRS1 (rs10498210) and CCR5 (59029A/G) genes increased the risk of T2DM.

A systems biology approach to predictive developmental neurotoxicity of a larvicide used in the prevention of Zika virus transmission

The need to prevent developmental brain disorders has led to an increased interest in efficient neurotoxicity testing. When an epidemic of microcephaly occurred in Brazil, Zika virus infection was soon identified as the likely culprit. However, the pathogenesis appeared to be complex, and a larvicide used to control mosquitoes responsible for transmission of the virus was soon suggested as an important causative factor. Yet, it is challenging to identify relevant and efficient tests that are also in line with ethical research defined by the 3Rs rule (Replacement, Reduction and Refinement). Especially in an acute situation like the microcephaly epidemic, where little toxicity documentation is available, new and innovative alternative methods, whether in vitro or in silico, must be considered. We have developed a network-based model using an integrative systems biology approach to explore the potential developmental neurotoxicity, and we applied this method to examine the larvicide pyriproxyfen widely used in the prevention of Zika virus transmission. Our computational model covered a wide range of possible pathways providing mechanistic hypotheses between pyriproxyfen and neurological disorders via protein complexes, thus adding to the plausibility of pyriproxyfen neurotoxicity. Although providing only tentative evidence and comparisons with retinoic acid, our computational systems biology approach is rapid and inexpensive. The case study of pyriproxyfen illustrates its usefulness as an initial or screening step in the assessment of toxicity potentials of chemicals with incompletely known toxic properties.

Association of serum levels of perfluoroalkyl substances with gestational diabetes mellitus and postpartum blood glucose

This study was conducted to examine the association of perfluoroalkyl substance (PFAS) exposure with gestational diabetes mellitus (GDM) risk and postpartum fasting blood glucose. We used a 1:2 matched case-control study with 84 GDM subjects and 168 healthy pregnant women from Beijing, China. The maternal blood was collected at 1-2days before delivery, and eight linear isomers and fourteen branched isomers were determined in maternal serum. Logistic regression analyses were performed to evaluate the associations after adjusting for potential confounders. The median of the sum of levels of total PFASs was 4.24ng/mL with a interquartile range (IQR) of 2.82-6.54ng/mL. Although maternal PFAS exposure was not associated with risk of GDM, significant positive associations were observed between evaluated exposure to specific PFAS congeners and increasing blood glucose. The odds ratio (ORs) of the highest category of postpartum fasting blood glucose for perfluoro-1-metylheptylsulfonat (1m-PFOS), perfluoro-3/4-metylheptylsulfonat (3m+4m-PFOS), perfluoro-5-metylheptylsulfonat (5m-PFOS), and perfluorohexane sulfonate (PFHxS) were 2.03 (95% CI: 1.09-3.77), 1.93 (95% CI: 1.04-3.58), 2.48 (95% CI: 1.33-4.65), and 2.26 (95% CI: 1.21-4.21), respectively, suggesting negative effects of maternal exposure to specific PFAS compounds on glucose metabolism.

PFOA is associated with diabetes and metabolic alteration in US men: National Health and Nutrition Examination Survey 2003-2012

Exposure to perfluoroalkyl substances (PFAS) is associated with a range of adverse health effects. However, it remains unclear whether PFAS at environmentally relevant exposure levels are related to diabetes and metabolite concentrations in adults. Using cross-sectional data from 7904 adults (age≥20years) in the 2003-2012 National Health and Nutrition Examination Survey (NHANES), we examined the association of PFAS with the prevalence of diabetes and metabolite concentrations. A multivariate logistic regression was applied to investigate the associations of diabetes prevalence with serum perfluorooctanoate (PFOA), perfluorooctane sulfonate (PFOS), perfluorohexane sulfonate (PFHxS) and perfluorononanoate (PFNA) levels. A multivariate generalised linear regression was further performed to investigate the associations between PFAS exposure and some metabolites. We identified a strong positive association between serum PFOA and diabetes prevalence in men with an adjusted model (OR: 2.66, 95% CI: 1.63-4.35; P for trend=0.001). No significant association between serum PFOA and diabetes prevalence was observed in women (OR: 1.47, 95% CI: 0.88-2.46; P for trend=0.737). Furthermore, diabetes was not related to PFOS, PFHxS and PFNA, regardless of gender. In the gender-stratified generalised linear models, men and women with the highest PFOA levels demonstrated a 1.43% (95% CI: 0.62%-2.34%) and a 1.07% (95% CI: 0.27%-1.97%) greater increase in serum total cholesterol (P for trend=0.006 and 0.001) compared to those with the lowest PFOA levels. There were no significant associations between serum PFOA and other metabolites. These results provide epidemiological evidence that environment-related levels of serum PFOA may be positively associated with the prevalence of diabetes in men and with total cholesterol in adults. Further clinical and animal studies are urgently needed to elucidate putative causal relationships and shed light on the potential mode of action involved.

Association of serum levels of perfluoroalkyl substances (PFASs) with the metabolic syndrome (MetS) in Chinese male adults: A cross-sectional study

As extensively used chemicals in a variety of consumer products, perfluoroalkyl substances (PFASs) are ubiquitous and could bring significant risk to human health. However, the effect of PFASs on metabolic syndrome (MetS) is not fully understood. In 2015, a preliminary cross-sectional study was undertaken. A total of 148 male subjects including 81 affected by MetS and 67 non-MetS participants as the reference were recruited from Physical Examination Center affiliated to Capital Medical University, China. Serum levels of perfluorohexane sulfonic acid (PFHxS), perfluorooctanoic acid (PFOA) and perfluorononanoic acid (PFNA) were significantly higher in the subjects with MetS. Logistic regression results showed that concentration of PFNA in serum was associated with 10.9-fold [95% confidence interval (CI), 2.00-59.1] increased risk of MetS. Moreover, increased serum PFNA concentrations were associated with high blood pressure [both for systolic and diastolic blood pressure (SBP and DBP); odds ratio (OR) 7.52 (95%CI, 1.34-42.1) for SBP and 7.27 (95%CI, 1.17-45.1) for DBP], hypertriglyceridemia [13.2 (95%CI, 2.34-74.2)] and obesity [13.3 (95%CI, 2.38-74.4)], respectively. After adjustment by age in logistic regression models, serum levels of PFOA were associated with 29.4-fold (95%CI, 2.90-299.7) increased risk of MetS. Increased PFOA levels were also correlated with MetS [29.4 (95%CI, 2.9-299.7)], SBP [10.8 (95%CI, 1.31-90.0)], hypertriglyceridemia [16.6 (95%CI, 1.92-147.1)], and obesity [46.7 (95%CI, 4.47-487.7)] with adjustment for age. This study suggests bodily retention of PFASs and its association with MetS. Further clinical and animal studies are warranted to clarify the putative causal relationship.

Plasma Concentrations of Per- and Polyfluoroalkyl Substances at Baseline and Associations with Glycemic Indicators and Diabetes Incidence among High-Risk Adults in the Diabetes Prevention Program Trial

BACKGROUND

Several per- and polyfluoroalkyl substances (PFAS) are ubiquitous anthropogenic pollutants almost universally detected in humans. Experimental evidence indicates that PFAS alter glucose metabolism and insulin secretion. However, epidemiological studies have yielded inconsistent results.

OBJECTIVE

We sought to examine associations between plasma PFAS concentrations, glycemic indicators, and diabetes incidence among high-risk adults.

METHODS

Within the Diabetes Prevention Program (DPP), a trial for the prevention of type 2 diabetes among high-risk individuals, we quantified baseline plasma concentrations of nine PFAS among 957 participants randomized to a lifestyle intervention or placebo. We evaluated adjusted associations for plasma PFAS concentrations with diabetes incidence and key glycemic indicators measured at baseline and annually over up to 4.6 y.

RESULTS

Plasma PFAS concentrations were similar to those reported in the U.S. population in 1999-2000. At baseline, in cross-sectional analysis, a doubling in plasma perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) concentrations was associated with higher homeostatic model assessment of insulin resistance (HOMA-IR) [β_PFOS=0.39; 95% confidence interval (CI): 0.13, 0.66; β_PFOA=0.64; 95% CI: 0.34, 0.94], β-cell function (HOMA-β) (β_PFOS=9.62; 95% CI: 1.55, 17.70; β_PFOA=15.93; 95% CI: 6.78, 25.08), fasting proinsulin (β_PFOS=1.37 pM; 95% CI: 0.50, 2.25; β_PFOA=1.71 pM; 95% CI: 0.72, 2.71), and glycated hemoglobin (HbA_1c) (β_PFOS=0.03%; 95% CI: 0.002, 0.07; β_PFOA=0.04%; 95% CI: 0.001, 0.07). There was no strong evidence of associations between plasma PFAS concentrations and diabetes incidence or prospective changes in glycemic indicators during the follow-up period.

CONCLUSIONS

At baseline, several PFAS were cross-sectionally associated with small differences in markers of insulin secretion and β-cell function. However, there was limited evidence suggesting that PFAS concentrations are associated with diabetes incidence or changes in glycemic indicators during the follow-up period. https://doi.org/10.1289/EHP1612.

Current Challenges and New Opportunities for Gene-Environment Interaction Studies of Complex Diseases

Recently, many new approaches, study designs, and statistical and analytical methods have emerged for studying gene-environment interactions (G×Es) in large-scale studies of human populations. There are opportunities in this field, particularly with respect to the incorporation of -omics and next-generation sequencing data and continual improvement in measures of environmental exposures implicated in complex disease outcomes. In a workshop called "Current Challenges and New Opportunities for Gene-Environment Interaction Studies of Complex Diseases," held October 17-18, 2014, by the National Institute of Environmental Health Sciences and the National Cancer Institute in conjunction with the annual American Society of Human Genetics meeting, participants explored new approaches and tools that have been developed in recent years for G×E discovery. This paper highlights current and critical issues and themes in G×E research that need additional consideration, including the improved data analytical methods, environmental exposure assessment, and incorporation of functional data and annotations.

Effects of arsenic on adipocyte metabolism: Is arsenic an obesogen?

The environmental obesogen model proposes that in addition to a high-calorie diet and diminished physical activity, other factors such as environmental pollutants and chemicals are involved in the development of obesity. Although arsenic has been recognized as a risk factor for Type 2 Diabetes with a specific mechanism, it is still uncertain whether arsenic is also an obesogen. The impairment of white adipose tissue (WAT) metabolism is crucial in the onset of obesity, and distinct studies have evaluated the effects of arsenic on it, however only in some of them for obesity-related purposes. Thus, the known effects of arsenic on WAT/adipocytes were integrated based on the diverse metabolic and physiological processes that occur in WAT and are altered in obesity, specifically: adipocyte growth, adipokine secretion, lipid metabolism, and glucose metabolism. The currently available information suggests that arsenic can negatively affect WAT metabolism, resulting in arsenic being a potential obesogen.

Early-Life Exposure to Perfluoroalkyl Substances and Childhood Metabolic Function

BACKGROUND

Perfluoroalkyl substances (PFASs) are synthetic chemicals that may persist in the environment and in humans. There is a possible association between early-life PFAS exposure and metabolic dysfunction in later life, but data are limited.

METHODS

We studied 665 mother-child pairs in Project Viva, a Boston, Massachusetts-area cohort recruited 1999-2002. We quantified concentrations of PFASs [perfluorooctanoate (PFOA), perfluorooctane sulfonate (PFOS), perfluorononanoate (PFNA), perfluorohexane sulfonate (PFHxS), and perfluorodecanoate (PFDeA)] in maternal plasma collected at the first prenatal visit (median, 9.6 weeks gestation) and in child plasma from the mid-childhood research visit (median, 7.7 years). We assessed leptin, adiponectin, and homeostatic model assessment of insulin resistance (HOMA-IR) in mid-childhood. We fit covariate-adjusted linear regression models and conducted stratified analyses by child sex.

RESULTS

Children with higher PFAS concentrations had lower HOMA-IR [e.g., -10.1% (95% CI: -17.3, -2.3) per interquartile range increment in PFOA]. This inverse association between child PFAS and HOMA-IR was more pronounced in females [e.g., PFOA: -15.6% (95% CI: -25.4, -4.6) vs. -6.1% (95% CI: -16.2, 5.2) for males]. Child PFAS plasma concentrations were not associated with leptin or adiponectin. Prenatal PFAS plasma concentrations were not associated with leptin, adiponectin, or HOMA-IR in offspring.

CONCLUSIONS

We found no evidence for an adverse effect of early-life PFAS exposure on metabolic function in mid-childhood. In fact, children with higher PFAS concentrations had lower insulin resistance. Citation: Fleisch AF, Rifas-Shiman SL, Mora AM, Calafat AM, Ye X, Luttmann-Gibson H, Gillman MW, Oken E, Sagiv SK. 2017. Early-life exposure to perfluoroalkyl substances and childhood metabolic function. Environ Health Perspect 125:481-487; http://dx.doi.org/10.1289/EHP303.

The Next Generation of Risk Assessment Multi-Year Study-Highlights of Findings, Applications to Risk Assessment, and Future Directions

BACKGROUND

The Next Generation (NexGen) of Risk Assessment effort is a multi-year collaboration among several organizations evaluating new, potentially more efficient molecular, computational, and systems biology approaches to risk assessment. This article summarizes our findings, suggests applications to risk assessment, and identifies strategic research directions.

OBJECTIVE

Our specific objectives were to test whether advanced biological data and methods could better inform our understanding of public health risks posed by environmental exposures.

METHODS

New data and methods were applied and evaluated for use in hazard identification and dose-response assessment. Biomarkers of exposure and effect, and risk characterization were also examined. Consideration was given to various decision contexts with increasing regulatory and public health impacts. Data types included transcriptomics, genomics, and proteomics. Methods included molecular epidemiology and clinical studies, bioinformatic knowledge mining, pathway and network analyses, short-duration in vivo and in vitro bioassays, and quantitative structure activity relationship modeling.

DISCUSSION

NexGen has advanced our ability to apply new science by more rapidly identifying chemicals and exposures of potential concern, helping characterize mechanisms of action that influence conclusions about causality, exposure-response relationships, susceptibility and cumulative risk, and by elucidating new biomarkers of exposure and effects. Additionally, NexGen has fostered extensive discussion among risk scientists and managers and improved confidence in interpreting and applying new data streams.

CONCLUSIONS

While considerable uncertainties remain, thoughtful application of new knowledge to risk assessment appears reasonable for augmenting major scope assessments, forming the basis for or augmenting limited scope assessments, and for prioritization and screening of very data limited chemicals. Citation: Cote I, Andersen ME, Ankley GT, Barone S, Birnbaum LS, Boekelheide K, Bois FY, Burgoon LD, Chiu WA, Crawford-Brown D, Crofton KM, DeVito M, Devlin RB, Edwards SW, Guyton KZ, Hattis D, Judson RS, Knight D, Krewski D, Lambert J, Maull EA, Mendrick D, Paoli GM, Patel CJ, Perkins EJ, Poje G, Portier CJ, Rusyn I, Schulte PA, Simeonov A, Smith MT, Thayer KA, Thomas RS, Thomas R, Tice RR, Vandenberg JJ, Villeneuve DL, Wesselkamper S, Whelan M, Whittaker C, White R, Xia M, Yauk C, Zeise L, Zhao J, DeWoskin RS. 2016. The Next Generation of Risk Assessment multiyear study-highlights of findings, applications to risk assessment, and future directions. Environ Health Perspect 124:1671-1682; http://dx.doi.org/10.1289/EHP233.

Assessment of Toxicological Perturbations and Variants of Pancreatic Islet Development in the Zebrafish Model

The pancreatic islets, largely comprised of insulin-producing beta cells, play a critical role in endocrine signaling and glucose homeostasis. Because they have low levels of antioxidant defenses and a high perfusion rate, the endocrine islets may be a highly susceptible target tissue of chemical exposures. However, this endpoint, as well as the integrity of the surrounding exocrine pancreas, is often overlooked in studies of developmental toxicology. Disruption of development by toxicants can alter cell fate and migration, resulting in structural alterations that are difficult to detect in mammalian embryo systems, but that are easily observed in the zebrafish embryo model (Danio rerio). Using endogenously expressed fluorescent protein markers for developing zebrafish beta cells and exocrine pancreas tissue, we documented differences in islet area and incidence rates of islet morphological variants in zebrafish embryos between 48 and 96 h post fertilization (hpf), raised under control conditions commonly used in embryotoxicity assays. We identified critical windows for chemical exposures during which increased incidences of endocrine pancreas abnormalities were observed following exposure to cyclopamine (2–12 hpf), Mono-2-ethylhexyl phthalate (MEHP) (3–48 hpf), and Perfluorooctanesulfonic acid (PFOS) (3–48 hpf). Both islet area and length of the exocrine pancreas were sensitive to oxidative stress from exposure to the oxidant tert-butyl hydroperoxide during a highly proliferative critical window (72 hpf). Finally, pancreatic dysmorphogenesis following developmental exposures is discussed with respect to human disease.

Diabetes and breast cancer in Taiwanese women: a detection bias?

PURPOSE

To evaluate whether diabetes is a risk factor for breast cancer considering confounders and potential detection examinations.

METHODS

National Health Insurance data on 501,747 women without breast cancer were retrieved. Three-year cumulative incidence (2003-2005) and risk ratios (RRs) between diabetic and nondiabetic women were calculated. Potential detection examinations were compared between diabetic and nondiabetic women by chi-square test. Odds ratios (ORs) were estimated by logistic regression for diabetes status/duration with and without adjustment for potential detection examinations and confounders.

RESULTS

The crude RR (95% confidence interval [CI]) for all ages, and age groups < 50, 50-64 and ≥ 65 years, was 2·62 (2·31-2·91), 2·69 (2·11-3·44), 1·39 (1·15-1·68) and 1·37 (1·03-1·84), respectively. Patients with diabetes more frequently received potential detection examinations than nondiabetes (17·5% vs. 7·4%, P-value < 0·001). The unadjusted OR (95% CI) for breast cancer for diabetes status (yes vs. no) was 2·63 (2·31-2·98) and was significant for any diabetes duration. The OR for diabetes status was 1·81 (95% CI: 1·59-2·06) after adjustment for potential detection examinations. In models adjusted for potential detection examinations, age, living region, occupation, comorbidities and used medications, OR for diabetes status attenuated to 1·13 (95% CI 0·96-1·32, P-value = 0·14) and none was significant for any diabetes duration. Potential detection examinations were associated with a fivefold to sevenfold higher risk in various models, indicating a strong impact of detection bias.

CONCLUSIONS

An association between diabetes and breast cancer is observed, but this can be due to potential detection bias and confounders.

Recent advances in the molecular genetics of type 2 diabetes mellitus

Type 2 diabetes mellitus (T2DM) is a complex disease in which both genetic and environmental factors interact in determining impaired β-cell insulin secretion and peripheral insulin resistance. Insulin resistance in muscle, liver and fat is a prominent feature of most patients with T2DM and obesity, resulting in a reduced response of these tissues to insulin. Considerable evidence has been accumulated to indicate that heredity is a major determinant of insulin resistance and T2DM. It is believed that, among individuals destined to develop T2DM, hyperinsulinemia is the mechanism by which the pancreatic β-cell initially compensates for deteriorating peripheral insulin sensitivity, thus ensuring normal glucose tolerance. Most of these people will develop T2DM when β-cells fail to compensate. Despite the progress achieved in this field in recent years, the genetic causes of insulin resistance and T2DM remain elusive. Candidate gene association, linkage and genome-wide association studies have highlighted the role of genetic factors in the development of T2DM. Using these strategies, a large number of variants have been identified in many of these genes, most of which may influence both hepatic and peripheral insulin resistance, adipogenesis and β-cell mass and function. Recently, a new gene has been identified by our research group, the HMGA1 gene, whose loss of function can greatly raise the risk of developing T2DM in humans and mice. Functional genetic variants of the HMGA1 gene have been associated with insulin resistance syndromes among white Europeans, Chinese individuals and Americans of Hispanic ancestry. These findings may represent new ways to improve or even prevent T2DM.

A CTD-Pfizer collaboration: manual curation of 88,000 scientific articles text mined for drug-disease and drug-phenotype interactions

Improving the prediction of chemical toxicity is a goal common to both environmental health research and pharmaceutical drug development. To improve safety detection assays, it is critical to have a reference set of molecules with well-defined toxicity annotations for training and validation purposes. Here, we describe a collaboration between safety researchers at Pfizer and the research team at the Comparative Toxicogenomics Database (CTD) to text mine and manually review a collection of 88 629 articles relating over 1 200 pharmaceutical drugs to their potential involvement in cardiovascular, neurological, renal and hepatic toxicity. In 1 year, CTD biocurators curated 2 54 173 toxicogenomic interactions (1 52 173 chemical–disease, 58 572 chemical–gene, 5 345 gene–disease and 38 083 phenotype interactions). All chemical–gene–disease interactions are fully integrated with public CTD, and phenotype interactions can be downloaded. We describe Pfizer’s text-mining process to collate the articles, and CTD’s curation strategy, performance metrics, enhanced data content and new module to curate phenotype information. As well, we show how data integration can connect phenotypes to diseases. This curation can be leveraged for information about toxic endpoints important to drug safety and help develop testable hypotheses for drug–disease events. The availability of these detailed, contextualized, high-quality annotations curated from seven decades’ worth of the scientific literature should help facilitate new mechanistic screening assays for pharmaceutical compound survival. This unique partnership demonstrates the importance of resource sharing and collaboration between public and private entities and underscores the complementary needs of the environmental health science and pharmaceutical communities.

Database URL: http://ctdbase.org/