Adolescent idiopathic scoliosis (AIS), environment, exposome and epigenetics: a molecular perspective of postnatal normal spinal growth and the etiopathogenesis of AIS with consideration of a network approach and possible implications for medical therapy

ABSTRACT: Genetic factors are believed to play an important role in the etiology of adolescent idiopathic scoliosis (AIS). Discordant findings for monozygotic (MZ) twins with AIS show that environmental factors including different intrauterine environments are important in etiology, but what these environmental factors may be is unknown. Recent evidence for common chronic non-communicable diseases suggests epigenetic differences may underlie MZ twin discordance, and be the link between environmental factors and phenotypic differences. DNA methylation is one important epigenetic mechanism operating at the interface between genome and environment to regulate phenotypic plasticity with a complex regulation across the genome during the first decade of life. The word exposome refers to the totality of environmental exposures from conception onwards, comprising factors in external and internal environments. The word exposome is used here also in relation to physiologic and etiopathogenetic factors that affect normal spinal growth and may induce the deformity of AIS. In normal postnatal spinal growth we propose a new term and concept, physiologic growth-plate exposome for the normal processes particularly of the internal environments that may have epigenetic effects on growth plates of vertebrae. In AIS, we propose a new term and concept pathophysiologic scoliogenic exposome for the abnormal processes in molecular pathways particularly of the internal environment currently expressed as etiopathogenetic hypotheses; these are suggested to have deforming effects on the growth plates of vertebrae at cell, tissue, structure and/or organ levels that are considered to be epigenetic. New research is required for chromatin modifications including DNA methylation in AIS subjects and vertebral growth plates excised at surgery. In addition, consideration is needed for a possible network approach to etiopathogenesis by constructing AIS diseasomes. These approaches may lead through screening, genetic, epigenetic, biochemical, metabolic phenotypes and pharmacogenomic research to identify susceptible individuals at risk and modulate abnormal molecular pathways of AIS. The potential of epigenetic-based medical therapy for AIS cannot be assessed at present, and must await new research derived from the evaluation of epigenetic concepts of spinal growth in health and deformity. The tenets outlined here for AIS are applicable to other musculoskeletal growth disorders including infantile and juvenile idiopathic scoliosis.     

Does the fetal genotype affect maternal physiology during pregnancy?

Conventional wisdom states that associations between fetal growth and diseases in pregnancy, such as pregnancy-induced hypertension (PIH) and gestational diabetes (GDM), result from effects of the mother's genotype or environment acting on her physiology which subsequently affect the fetus. However, recent evidence from human mothers carrying macrosomic offspring with Beckwith Wiedemann syndrome and pregnant mice carrying p57(kip2)-null offspring suggest that variation in the fetal genome can modify maternal physiology to increase fetal nutrient delivery and optimise growth. These are some of the first documented examples of such effects, whereby the genome of one individual directly affects the physiology of another related individual from the same species. We propose that this mechanism is involved in the aetiology of PIH and GDM.     

The role of caveolae in endothelial cell dysfunction with a focus on nutrition and environmental toxicants

Complications of vascular diseases, including atherosclerosis, are the number one cause of death in Western societies. Dysfunction of endothelial cells is a critical underlying cause of the pathology of atherosclerosis. Lipid rafts, and especially caveolae, are enriched in endothelial cells, and down-regulation of the caveolin-1 gene may provide protection against the development of atherosclerosis. There is substantial evidence that exposure to environmental pollution is linked to cardiovascular mortality, and that persistent organic pollutants can markedly contribute to endothelial cell dysfunction and an increase in vascular inflammation. Nutrition can modulate the toxicity of environmental pollutants, and evidence suggests that these affect health and disease outcome associated with chemical insults. Because caveolae can provide a regulatory platform for pro-inflammatory signalling associated with vascular diseases such as atherosclerosis, we suggest a link between atherogenic risk and functional changes of caveolae by environmental factors such as dietary lipids and organic pollutants. For example, we have evidence that endothelial caveolae play a role in uptake of persistent organic pollutants, an event associated with subsequent production of inflammatory mediators. Functional properties of caveolae can be modulated by nutrition, such as dietary lipids (e.g. fatty acids) and plant-derived polyphenols (e.g. flavonoids), which change activation of caveolae-associated signalling proteins. The following review will focus on caveolae providing a platform for pro-inflammatory signalling, and the role of caveolae in endothelial cell functional changes associated with environmental mediators such as nutrients and toxicants, which are known to modulate the pathology of vascular diseases.     

Gestational diabetes mellitus epigenetically affects genes predominantly involved in metabolic diseases

Offspring exposed to gestational diabetes mellitus (GDM) have an increased risk for chronic diseases, and one promising mechanism for fetal metabolic programming is epigenetics. Therefore, we postulated that GDM exposure impacts the offspring’s methylome and used an epigenomic approach to explore this hypothesis. Placenta and cord blood samples were obtained from 44 newborns, including 30 exposed to GDM. Women were recruited at first trimester of pregnancy and followed until delivery. GDM was assessed after a 75-g oral glucose tolerance test at 24–28 weeks of pregnancy. DNA methylation was measured at > 485,000 CpG sites (Infinium HumanMethylation450 BeadChips). Ingenuity Pathway Analysis was conducted to identify metabolic pathways epigenetically affected by GDM. Our results showed that 3,271 and 3,758 genes in placenta and cord blood, respectively, were potentially differentially methylated between samples exposed or not to GDM (p-values down to 1 × 10⁻⁰⁶; none reached the genome-wide significance levels), with more than 25% (n = 1,029) being common to both tissues. Mean DNA methylation differences between groups were 5.7 ± 3.2% and 3.4 ± 1.9% for placenta and cord blood, respectively. These genes were likely involved in the metabolic diseases pathway (up to 115 genes (11%), p-values for pathways = 1.9 × 10⁻¹³ < p < 4.0 × 10⁻⁰³; including diabetes mellitus p = 4.3 × 10⁻¹¹). Among the differentially methylated genes, 326 in placenta and 117 in cord blood were also associated with newborn weight. Our results therefore suggest that GDM has epigenetic effects on genes preferentially involved in the metabolic diseases pathway, with consequences on fetal growth and development, and provide supportive evidence that DNA methylation is involved in fetal metabolic programming.     

Rule-Based Models of the Interplay between Genetic and Environmental Factors in Childhood Allergy

Both genetic and environmental factors are important for the development of allergic diseases. However, a detailed understanding of how such factors act together is lacking. To elucidate the interplay between genetic and environmental factors in allergic diseases, we used a novel bioinformatics approach that combines feature selection and machine learning. In two materials, PARSIFAL (a European cross-sectional study of 3113 children) and BAMSE (a Swedish birth-cohort including 2033 children), genetic variants as well as environmental and lifestyle factors were evaluated for their contribution to allergic phenotypes. Monte Carlo feature selection and rule based models were used to identify and rank rules describing how combinations of genetic and environmental factors affect the risk of allergic diseases. Novel interactions between genes were suggested and replicated, such as between ORMDL3 and RORA, where certain genotype combinations gave odds ratios for current asthma of 2.1 (95% CI 1.2-3.6) and 3.2 (95% CI 2.0-5.0) in the BAMSE and PARSIFAL children, respectively. Several combinations of environmental factors appeared to be important for the development of allergic disease in children. For example, use of baby formula and antibiotics early in life was associated with an odds ratio of 7.4 (95% CI 4.5-12.0) of developing asthma. Furthermore, genetic variants together with environmental factors seemed to play a role for allergic diseases, such as the use of antibiotics early in life and COL29A1 variants for asthma, and farm living and NPSR1 variants for allergic eczema. Overall, combinations of environmental and life style factors appeared more frequently in the models than combinations solely involving genes. In conclusion, a new bioinformatics approach is described for analyzing complex data, including extensive genetic and environmental information. Interactions identified with this approach could provide useful hints for further in-depth studies of etiological mechanisms and may also strengthen the basis for risk assessment and prevention.     

Inference of Cross-Level Interaction between Genes and Contextual Factors in a Matched Case-Control Metabolic Syndrome Study: A Bayesian Approach

Genes, environment, and the interaction between them are each known to play an important role in the risk for developing complex diseases such as metabolic syndrome. For environmental factors, most studies focused on the measurements observed at the individual level, and therefore can only consider the gene-environment interaction at the same individual scale. Indeed the group-level (called contextual) environmental variables, such as community factors and the degree of local area development, may modify the genetic effect as well. To examine such cross-level interaction between genes and contextual factors, a flexible statistical model quantifying the variability of the genetic effects across different categories of the contextual variable is in need. With a Bayesian generalized linear mixed-effects model with an unconditional likelihood, we investigate whether the individual genetic effect is modified by the group-level residential environment factor in a matched case-control metabolic syndrome study. Such cross-level interaction is evaluated by examining the heterogeneity in allelic effects under various contextual categories, based on posterior samples from Markov chain Monte Carlo methods. The Bayesian analysis indicates that the effect of rs1801282 on metabolic syndrome development is modified by the contextual environmental factor. That is, even among individuals with the same genetic component of PPARG_Pro12Ala, living in a residential area with low availability of exercise facilities may result in higher risk. The modification of the group-level environment factors on the individual genetic attributes can be essential, and this Bayesian model is able to provide a quantitative assessment for such cross-level interaction. The Bayesian inference based on the full likelihood is flexible with any phenotype, and easy to implement computationally. This model has a wide applicability and may help unravel the complexity in development of complex diseases.     

Placental contribution to the origins of sexual dimorphism in health and diseases: sex chromosomes and epigenetics

Sex differences occur in most non-communicable diseases, including metabolic diseases, hypertension, cardiovascular disease, psychiatric and neurological disorders and cancer. In many cases, the susceptibility to these diseases begins early in development. The observed differences between the sexes may result from genetic and hormonal differences and from differences in responses to and interactions with environmental factors, including infection, diet, drugs and stress. The placenta plays a key role in fetal growth and development and, as such, affects the fetal programming underlying subsequent adult health and accounts, in part for the developmental origin of health and disease (DOHaD). There is accumulating evidence to demonstrate the sex-specific relationships between diverse environmental influences on placental functions and the risk of disease later in life. As one of the few tissues easily collectable in humans, this organ may therefore be seen as an ideal system for studying how male and female placenta sense nutritional and other stresses, such as endocrine disruptors. Sex-specific regulatory pathways controlling sexually dimorphic characteristics in the various organs and the consequences of lifelong differences in sex hormone expression largely account for such responses. However, sex-specific changes in epigenetic marks are generated early after fertilization, thus before adrenal and gonad differentiation in the absence of sex hormones and in response to environmental conditions. Given the abundance of X-linked genes involved in placentogenesis, and the early unequal gene expression by the sex chromosomes between males and females, the role of X- and Y-chromosome-linked genes, and especially those involved in the peculiar placenta-specific epigenetics processes, giving rise to the unusual placenta epigenetic landscapes deserve particular attention. However, even with recent developments in this field, we still know little about the mechanisms underlying the early sex-specific epigenetic marks resulting in sex-biased gene expression of pathways and networks. As a critical messenger between the maternal environment and the fetus, the placenta may play a key role not only in buffering environmental effects transmitted by the mother but also in expressing and modulating effects due to preconceptional exposure of both the mother and the father to stressful conditions.     

High-performance metabolic profiling with dual chromatography-Fourier-transform mass spectrometry (DC-FTMS) for study of the exposome

Studies of gene–environment (G × E) interactions require effective characterization of all environmental exposures from conception to death, termed the exposome. The exposome includes environmental exposures that impact health. Improved metabolic profiling methods are needed to characterize these exposures for use in personalized medicine. In the present study, we compared the analytic capability of dual chromatography-Fourier-transform mass spectrometry (DC-FTMS) to previously used liquid chromatography-FTMS (LC-FTMS) analysis for high-throughput, top-down metabolic profiling. For DC-FTMS, we combined data from sequential LC-FTMS analyses using reverse phase (C18) chromatography and anion exchange (AE) chromatography. Each analysis was performed with electrospray ionization in the positive ion mode and detection from m/z 85 to 850. Run time for each column was 10 min with gradient elution; 10 μl extracts of plasma from humans and common marmosets were used for analysis. In comparison to analysis with the AE column alone, addition of the second LC-FTMS analysis with the C18 column increased m/z feature detection by 23–36%, yielding a total number of features up to 7,000 for individual samples. Approximately 50% of the m/z matched to known chemicals in metabolomic databases, and 23% of the m/z were common to analyses on both columns. Database matches included insecticides, herbicides, flame retardants, and plasticizers. Modularity clustering algorithms applied to MS-data showed the ability to detection clusters and ion interactions. DC-FTMS thus provides improved capability for high-performance metabolic profiling of the exposome and development of personalized medicine.     

Environmental-induced oxidative stress in neurodegenerative disorders and aging

The aetiology of most neurodegenerative disorders is multifactorial and consists of an interaction between environmental factors and genetic predisposition. Free radicals derived primarily from molecular oxygen have been implicated and considered as associated risk factors for a variety of human disorders including neurodegenerative diseases and aging. Damage to tissue biomolecules, including lipids, proteins and DNA, by free radicals is postulated to contribute importantly to the pathophysiology of oxidative stress. The potential of environmental exposure to metals, air pollution and pesticides as well as diet as risk factors via the induction of oxidative stress for neurodegenerative diseases and aging is discussed. The role of genetic background is discussed on the light of the oxidative stress implication, focusing on both complex neurodegenerative diseases (Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis) and monogenic neurological disorders (Huntington's disease, Ataxia telangiectasia, Friedreich Ataxia and others). Emphasis is given to role of the repair mechanisms of oxidative DNA damage in delaying aging and protecting against neurodegeneration. The emerging interplay between environmental-induced oxidative stress and epigenetic modifications of critical genes for neurodegeneration is also discussed.     

Environmental influence on neurodevelopmental disorders: Potential association of heavy metal exposure and autism

Environmental factors have been severally established to play major roles in the pathogenesis of neurodevelopmental disorders including autism spectrum disorder (ASD). ASD is a neurodevelopmental disorder that is associated with symptoms that reduce the quality of life of affected individuals such as social interaction deficit, cognitive impairment, intellectual disabilities, restricted and repetitive behavioural patterns. ASD pathogenesis has been associated with environmental and genetic factors that alter physiologic processes during development. Here, we review literatures highlighting the environmental impact on neurodevelopmental disorders, and mechanisms by which environmental toxins may influence neurodevelopment. Furthermore, this review discusses reports highlighting neurotoxic metals (specifically, lead, mercury, cadmium, nickel and manganese) as environmental risk factors in the aetiology of ASD. This work, thus suggests that improving the environment could be vital in the management of ASD.     

Intergenerational transmission of insulin resistance and type 2 diabetes

Studies in women with type 1 or type 2 diabetes mellitus (DM) and their children suggest that the in utero ‘diabetic’ environment in which the fetus develops can increase the risk of diabetes in the child, in a non-genetic but heritable fashion. Studies in rodents provide strong evidence for maternal transmission of diabetes, but are based primarily on a model type 1 DM and there is no standard animal model of type 2 DM in pregnancy or of gestational diabetes mellitus (GDM), although those reported uniformly show glucose intolerance in the offspring. Rodent models of diet-induced obesity have relevance to current upward trends in maternal obesity and GDM, although maternal glucose homeostasis is not always assessed and elements of the diet may have an independent influence. The mechanisms by which maternal type 2DM evokes a higher risk of the disorder in the offspring are likely to result from epigenetic modification in early life of pathways of pancreatic β cells and of liver and muscle insulin signalling pathways. Also, epigenetic processes associated with hormonal imbalance may lead to irreversible ‘reordering’ of hypothalamic neural networks in fetal/neonatal life, permanently alter energy balance and lead to obesity with associated insulin resistance.     

A Novel Approach for Identifying Causal Models of Complex Diseases from Family Data

Causal models including genetic factors are important for understanding the presentation mechanisms of complex diseases. Familial aggregation and segregation analyses based on polygenic threshold models have been the primary approach to fitting genetic models to the family data of complex diseases. In the current study, an advanced approach to obtaining appropriate causal models for complex diseases based on the sufficient component cause (SCC) model involving combinations of traditional genetics principles was proposed. The probabilities for the entire population, i.e., normal–normal, normal–disease, and disease–disease, were considered for each model for the appropriate handling of common complex diseases. The causal model in the current study included the genetic effects from single genes involving epistasis, complementary gene interactions, gene–environment interactions, and environmental effects. Bayesian inference using a Markov chain Monte Carlo algorithm (MCMC) was used to assess of the proportions of each component for a given population lifetime incidence. This approach is flexible, allowing both common and rare variants within a gene and across multiple genes. An application to schizophrenia data confirmed the complexity of the causal factors. An analysis of diabetes data demonstrated that environmental factors and gene–environment interactions are the main causal factors for type II diabetes. The proposed method is effective and useful for identifying causal models, which can accelerate the development of efficient strategies for identifying causal factors of complex diseases.     

Genetic Determinants for Gestational Diabetes Mellitus and Related Metabolic Traits in Mexican Women

Epidemiological and physiological similarities among Gestational Diabetes Mellitus (GDM) and Type 2 Diabetes (T2D) suggest that both diseases, share a common genetic background. T2D risk variants have been associated to GDM susceptibility. However, the genetic architecture of GDM is not yet completely understood. We analyzed 176 SNPs for 115 loci previously associated to T2D, GDM and body mass index (BMI), as well as a set of 118 Ancestry Informative Markers (AIMs), in 750 pregnant Mexican women. Association with GDM was found for two of the most frequently replicated T2D loci: a TCF7L2 haplotype (CTTC: rs7901695, rs4506565, rs7903146, rs12243326; P=2.16x10^-06; OR=2.95) and a KCNQ1 haplotype (TTT: rs2237892, rs163184, rs2237897; P=1.98x10^-05; OR=0.55). In addition, we found two loci associated to glycemic traits: CENTD2 (60’ OGTT glycemia: rs1552224, P=0.03727) and MTNR1B (HOMA B: rs1387153, P=0.05358). Remarkably, a major susceptibility SLC16A11 locus for T2D in Mexicans was not shown to play a role in GDM risk. The fact that two of the main T2D associated loci also contribute to the risk of developing GDM in Mexicans, confirm that both diseases share a common genetic background. However, lack of association with a Native American contribution T2D risk haplotype, SLC16A11, suggests that other genetic mechanisms may be in play for GDM.     

Epigenetics of asthma

Asthma is caused by both heritable and environmental factors. It has become clear that genetic studies do not adequately explain the heritability and susceptibility to asthma. The study of epigenetics, heritable non-coding changes to DNA may help to explain the heritable component of asthma. Additionally, epigenetic modifications can be influenced by the environment, including pollution and cigarette smoking, which are known asthma risk factors. These environmental trigger-induced epigenetic changes may be involved in skewing the immune system towards a Th2 phenotype following in utero exposure and thereby enhancing the risk of asthma. Alternatively, they may directly or indirectly modulate the immune and inflammatory processes in asthmatics via effects on treatment responsiveness. The study of epigenetics may therefore play an important role in our understanding and possible treatment of asthma and other allergic diseases. This article is part of a Special Issue entitled: Biochemistry of Asthma.     

Proteins and metabolites fingerprints of gestational diabetes mellitus forming protein–metabolite interactomes are its potential biomarkers

Gestational diabetes mellitus (GDM) is a consequence of glucose intolerance with an inadequate production of insulin that happens during pregnancy and leads to adverse health consequences for both mother and fetus. GDM patients are at higher risk for preeclampsia, and developing diabetes mellitus type 2 in later life, while the child born to GDM mothers are more prone to macrosomia, and hypoglycemia. The universally accepted diagnostic criteria for GDM are lacking, therefore there is a need for a diagnosis of GDM that can identify GDM at its early stage (first trimester). We have reviewed the literature on proteins and metabolites fingerprints of GDM. Further, we have performed protein–protein, metabolite–metabolite, and protein–metabolite interaction network studies on GDM proteins and metabolites fingerprints. Notably, some proteins and metabolites fingerprints are forming strong interaction networks at high confidence scores. Therefore, we have suggested that those proteins and metabolites that are forming protein–metabolite interactomes are the potential biomarkers of GDM. The protein–metabolite biomarkers interactome may help in a deep understanding of the prognosis, pathogenesis of GDM, and also detection of GDM. The protein–metabolites interactome may be further applied in planning future therapeutic strategies to promote long-term health benefits in GDM mothers and their children.     

Xenogenetics in multifactorial disease susceptibility

Susceptibility to multifactorial disease includes both genetic and environmental components. These two aspects of susceptibility are interlinked through genetic control of an individual's response to the environment. As a first step in identifying disease susceptibility genes that influence the response of an individual to foreign compounds (xenobiotics), it is necessary to study disorders in which there is an identified environmental trigger. Establishing a DNA resource from individuals with known environmental exposure (‘a xenogenetic register’) for diseases with an established environmental aetiology is an essential step in beginning to understand how environmental factors contribute to the susceptibility to polygenic diseases. A complementary approach to identification of environmental factors is suggested using a comparison of genetically homogeneous subdivisions of individuals with polygenic disease where there is no clue to the environmental trigger.     

The rs2237892 Polymorphism in KCNQ1 Influences Gestational Diabetes Mellitus and Glucose Levels: A Case-Control Study and Meta-Analysis

Objective

Recent genetic studies have shown that potassium voltage-gated channel, KQT-like subfamily, member1 (KCNQ1) gene is related to gestational diabetes mellitus (GDM). However, studies for the rs2237892 polymorphism in KCNQ1 and GDM remain conflicting in Asians. Furthermore, associations of this polymorphism with glucose levels during oral glucose tolerance test (OGTT) have not been described in Chinese pregnant women. The present study aimed to provide evidence for the associations of rs2237892 in KCNQ1 with GDM and glucose levels, and to systematically evaluate the effect of rs2237892 on GDM in Asians.

Methods

A case-control study on 562 women with GDM and 453 controls was conducted in Beijing, China. The association of rs2237892 with risk of GDM was analyzed using logistic regression. The associations with quantitative glucose levels were assessed using linear regression models. A meta-analysis including the present case-control study and four previously published reports in Asians was conducted.

Results

The rs2237892 polymorphism in KCNQ1 was associated with GDM (OR (95%CI) =1.99(1.26-3.15)). Additionally, the polymorphism was associated with levels of 1h and 2h glucose during OGTT. The pre-pregnancy BMI, age and genotypes of KCNQ1 polymorphism were independent risk factors of GDM. Subsequently, we performed a meta-analysis in Asians. In total, C-allele carriers of rs2237892 polymorphism had a 50% higher risk for GDM (OR (95%CI) =1.50(1.15-1.78)).

Conclusion

The study demonstrated for the first time that the KCNQ1 rs2237892 polymorphism was associated with GDM and glucose levels in Chinese women. The study provides systematic evidence for the association between this polymorphism and GDM in Asians.     

Glycaemia dynamics in gestational diabetes mellitus

Pregnant women may develop gestational diabetes mellitus (GDM), a disease of pregnancy characterised by maternal and fetal hyperglycaemia with hazardous consequences to the mother, the fetus, and the newborn. Maternal hyperglycaemia in GDM results in fetoplacental endothelial dysfunction. GDM-harmful effects result from chronic and short periods of hyperglycaemia. Thus, it is determinant to keep glycaemia within physiological ranges avoiding short but repetitive periods of hyper or hypoglycaemia. The variation of glycaemia over time is defined as ‘glycaemia dynamics’. The latter concept regards with a variety of mechanisms and environmental conditions leading to blood glucose handling. In this review we summarized the different metrics for glycaemia dynamics derived from quantitative, plane distribution, amplitude, score values, variability estimation, and time series analysis. The potential application of the derived metrics from self-monitoring of blood glucose (SMBG) and continuous glucose monitoring (CGM) in the potential alterations of pregnancy outcome in GDM are discussed.     

Embryos as targets of endocrine disrupting contaminants in wildlife

Environmental contaminants are now a ubiquitous part of the ecological landscape, and a growing literature describes the ability of many of these chemicals to alter the developmental trajectory of the embryo. Because many environmental pollutants readily bioaccumulate in lipid rich tissues, wildlife can attain considerable body burdens. Embryos are often exposed to these pollutants through maternal transfer, and a growing number of studies report long-term or permanent developmental consequences. Many biological mechanisms are reportedly affected by environmental contaminants in the developing embryo and fetus, including neurodevelopment, steroidogenesis, gonadal differentiation, and liver function. Embryos are not exposed to one chemical at a time, but are chronically exposed to many chemicals simultaneously. Mixture studies show that for some developmental disorders, mixtures of chemicals cause a more deleterious response than would be predicted from their individual toxicities. Synergistic responses to low dose mixtures make it difficult to estimate developmental outcomes, and as such, traditional toxicity testing often results in an underestimate of exposure risks. In addition, the knowledge that biological systems do not necessarily respond in a dose-dependent fashion, and that very low doses of a chemical can prove more harmful than higher doses, has created a paradigm shift in studies of environmental contaminant-induced dysfunction. Although laboratory studies are critical for providing dose-response relationships and determining specific mechanisms involved in disease etiology, wildlife sentinels more accurately reflect the genetic diversity of real world exposure conditions, and continue to alert scientists and health professionals alike of the consequences of developmental exposures to environmental pollutants.