A statistical model for assessing genetic susceptibility as a risk factor in multifactorial diseases: lessons from occupational asthma

Considerations for Using Genetic and Epigenetic Information in Occupational Health Risk Assessment and Standard Setting

Risk assessment forms the basis for both occupational health decision-making and the development of occupational exposure limits (OELs). Although genetic and epigenetic data have not been widely used in risk assessment and ultimately, standard setting, it is possible to envision such uses. A growing body of literature demonstrates that genetic and epigenetic factors condition biological responses to occupational and environmental hazards or serve as targets of them. This presentation addresses the considerations for using genetic and epigenetic information in risk assessments, provides guidance on using this information within the classic risk assessment paradigm, and describes a framework to organize thinking about such uses. The framework is a 4 × 4 matrix involving the risk assessment functions (hazard identification, dose-response modeling, exposure assessment, and risk characterization) on one axis and inherited and acquired genetic and epigenetic data on the other axis. The cells in the matrix identify how genetic and epigenetic data can be used for each risk assessment function. Generally, genetic and epigenetic data might be used as endpoints in hazard identification, as indicators of exposure, as effect modifiers in exposure assessment and dose-response modeling, as descriptors of mode of action, and to characterize toxicity pathways. Vast amounts of genetic and epigenetic data may be generated by high-throughput technologies. These data can be useful for assessing variability and reducing uncertainty in extrapolations, and they may serve as the foundation upon which identification of biological perturbations would lead to a new paradigm of toxicity pathway-based risk assessments.

Systems Biology and Biomarkers of Early Effects for Occupational Exposure Limit Setting

In a recent National Research Council document, new strategies for risk assessment were described to enable more accurate and quicker assessments. This report suggested that evaluating individual responses through increased use of bio-monitoring could improve dose-response estimations. Identification of specific biomarkers may be useful for diagnostics or risk prediction as they have the potential to improve exposure assessments. This paper discusses systems biology, biomarkers of effect, and computational toxicology approaches and their relevance to the occupational exposure limit setting process. The systems biology approach evaluates the integration of biological processes and how disruption of these processes by chemicals or other hazards affects disease outcomes. This type of approach could provide information used in delineating the mode of action of the response or toxicity, and may be useful to define the low adverse and no adverse effect levels. Biomarkers of effect are changes measured in biological systems and are considered to be preclinical in nature. Advances in computational methods and experimental -omics methods that allow the simultaneous measurement of families of macromolecules such as DNA, RNA, and proteins in a single analysis have made these systems approaches feasible for broad application. The utility of the information for risk assessments from -omics approaches has shown promise and can provide information on mode of action and dose-response relationships. As these techniques evolve, estimation of internal dose and response biomarkers will be a critical test of these new technologies for application in risk assessment strategies. While proof of concept studies have been conducted that provide evidence of their value, challenges with standardization and harmonization still need to be overcome before these methods are used routinely.

Considerations for Using Genetic and Epigenetic Information in Occupational Health Risk Assessment and Standard Setting

Risk assessment forms the basis for both occupational health decision-making and the development of occupational exposure limits (OELs). Although genetic and epigenetic data have not been widely used in risk assessment and ultimately, standard setting, it is possible to envision such uses. A growing body of literature demonstrates that genetic and epigenetic factors condition biological responses to occupational and environmental hazards or serve as targets of them. This presentation addresses the considerations for using genetic and epigenetic information in risk assessments, provides guidance on using this information within the classic risk assessment paradigm, and describes a framework to organize thinking about such uses. The framework is a 4 × 4 matrix involving the risk assessment functions (hazard identification, dose-response modeling, exposure assessment, and risk characterization) on one axis and inherited and acquired genetic and epigenetic data on the other axis. The cells in the matrix identify how genetic and epigenetic data can be used for each risk assessment function. Generally, genetic and epigenetic data might be used as endpoints in hazard identification, as indicators of exposure, as effect modifiers in exposure assessment and dose-response modeling, as descriptors of mode of action, and to characterize toxicity pathways. Vast amounts of genetic and epigenetic data may be generated by high-throughput technologies. These data can be useful for assessing variability and reducing uncertainty in extrapolations, and they may serve as the foundation upon which identification of biological perturbations would lead to a new paradigm of toxicity pathway-based risk assessments.

Screening of susceptibility genes and multi-gene risk analysis in gastric cancer

The aim of the study was to explore the relations between the genetic polymorphism and the susceptibility to the gastric cancer in Chinese Han population, and to analyze the multi-genes risk in the development of gastric carcinoma. A case-control study of 1:1 matching was performed on 564 individuals with primary gastric carcinoma in Nanjing, China. The genotypes of CYP2E1, GSTMl, GSTTl, NAT2, ALDH2, MTHFR, XRCCl, IL-1β, VDR, and TNF were detected by molecular biological techniques (PCR-RFLP and AS-PCR). Sole gene and gene-gene interactions were analyzed using Logistic regression model. The effect of multi-genes on gastric carcinoma was analyzed using multi-gene risk analysis model, which focused on the effect of multi-gene interaction on the development of gastric carcinoma. The genotypes involved in the susceptibility of gastric carcinoma were CYP2E1(c1/c1), NAT2M1(T/T), NAT2M2(A/A), XRCC1194(T/T), NAT2 phenotype (slow acetylator), MTHFR1298(A/C), and VDR TaqI(T/T), respectively. Multi-gene risk analysis model was introduced to analyze the effect of these genes on the gastric carcinoma. The results showed that there was a strong relation between odds ratio (OR) value of polygene combination and the gene frequency. With the increase of susceptibility gene frequency, the risk distribution curve of gastric carcinoma would shift to a more dangerous phase and exhibit a quantitative relation. Our results demonstrated that the OR of each gene can be utilized as an index to assess the effect of multiple susceptible genes on the occurrence of gastric carcinoma.

Genetic polymorphism in metabolism and host defense enzymes: implications for human health risk assessment

Genetic polymorphisms in xenobiotic metabolizing enzymes can have profound influence on enzyme function, with implications for chemical clearance and internal dose. The effects of polymorphisms have been evaluated for certain therapeutic drugs but there has been relatively little investigation with environmental toxicants. Polymorphisms can also affect the function of host defense mechanisms and thus modify the pharmacodynamic response. This review and analysis explores the feasibility of using polymorphism data in human health risk assessment for four enzymes, two involved in conjugation (uridine diphosphoglucuronosyltransferases [UGTs], sulfotransferases [SULTs]), and two involved in detoxification (microsomal epoxide hydrolase [EPHX1], NADPH quinone oxidoreductase I [NQO1]). This set of evaluations complements our previous analyses with oxidative and conjugating enzymes. Of the numerous UGT and SULT enzymes, the greatest likelihood for polymorphism effect on conjugation function are for SULT1A1 (*2 polymorphism), UGT1A1 (*6, *7, *28 polymorphisms), UGT1A7 (*3 polymorphism), UGT2B15 (*2 polymorphism), and UGT2B17 (null polymorphism). The null polymorphism in NQO1 has the potential to impair host defense. These highlighted polymorphisms are of sufficient frequency to be prioritized for consideration in chemical risk assessments. In contrast, SNPs in EPHX1 are not sufficiently influential or defined for inclusion in risk models. The current analysis is an important first step in bringing the highlighted polymorphisms into a physiologically based pharmacokinetic (PBPK) modeling framework.

Risk assessment and pharmacogenetics in molecular and genomic epidemiology

In this article, we reviewed the literature on risk assessment (RA) models with and without molecular genomic markers and the current utility of the markers in the pharmacogenetic field. Epidemiological risk assessment is applied using statistical models and equations established from current scientific knowledge of risk and disease. Several papers have reported that traditional RA tools have significant limitations in decision-making in management strategies for individuals as predictions of diseases and disease progression are inaccurate. Recently, the model added information on the genetic susceptibility factors that are expected to be most responsible for differences in individual risk. On the continuum of health care, from diagnosis to treatment, pharmacogenetics has been developed based on the accumulated knowledge of human genomic variation involving drug distribution and metabolism and the target of action, which has the potential to facilitate personalized medicine that can avoid therapeutic failure and serious side effects. There are many challenges for the applicability of genomic information in a clinical setting. Current uses of genetic markers for managing drug therapy and issues in the development of a valid biomarker in pharmacogenetics are discussed.

Evaluating diagnostic accuracy of genetic profiles in affected offspring families

Diagnostic accuracy of a genetic test involving multiple disease genes is evaluated using sensitivity and specificity. For estimation, data from both affected and unaffected subjects are required. For early onset diseases, such as autism spectrum disorder (ASD), only data from families with affected offspring are available. To enable estimation of specificity when no data for unaffected offspring are available (single affected offspring, SAO, data), we combine the pseudocontrol method of Cordell and Clayton (Am. J. Hum. Genet. 2002; 70:124-141) with the approach of DeLong et al. (Biometrics 1985; 41:947-958) in a logistic regression model for disease outcome with a risk score (RS) constructed from genotype information as prognostic variable. The area under the receiver operating characteristic curve (AUC) is then computed using the non-parametric Mann-Whitney method. Extensive simulation studies show that, analogous to other approaches utilizing pseudocontrols, the resulting estimates of AUC using SAO data are slightly conservative when compared with the estimates computed using the full population-based data. The method is illustrated using data from a study of ASD.

A genetic approach to stratification of risk for age-related macular degeneration

The genetic determinants of age-related macular degeneration (AMD) are reviewed and a novel approach to risk determination based upon inherited genetic polymorphisms and smoking history is presented. Although AMD was long thought to have primarily an environmental etiology, genetic variation is now known to account for the majority of the disease risk, with variations in the genes of the complement pathways playing a prominent role. Independent and validated clinical studies have implicated the C3 gene and its regulator, complement factor H (1q31.1), complement component 2 (6q21.33), and complement factor B (6q21.33). Subtle variations in complement activity increase the risk of symptomatic macular inflammation with age. A second group of AMD-associated genetic markers may aggravate complement-mediated inflammation by permitting retinal oxidative damage. Variation within the chromosomal site (10q26) coding a mitochondrial-associated protein (age-related maculopathy susceptibility 2) and an independent variation within the mitochondrial genome itself (A4917G) suggest a contributing pathophysiological role of retinal oxidative stress. A genetic panel of disease-susceptibility markers and smoking history can identify a group of individuals with greater than 65% lifetime risk of AMD. The introduction of genetic marker testing into clinical practice may identify patients with early disease who may be aided by presymptomatic monitoring or inclusion into trials of newer prophylactic agents.

Early incidence of occupational asthma among young bakers, pastry-makers and hairdressers: design of a retrospective cohort study

Background

Occupational exposures are thought to be responsible for 10-15% of new-onset asthma cases in adults, with disparities across sectors. Because most of the data are derived from registries and cross-sectional studies, little is known about incidence of occupational asthma (OA) during the first years after inception of exposure. This paper describes the design of a study that focuses on this early asthma onset period among young workers in the bakery, pastry making and hairdressing sectors in order to assess early incidence of OA in these "at risk" occupations according to exposure duration, and to identify risk factors of OA incidence.

Methods/Design

The study population is composed of subjects who graduated between 2001 and 2006 in these sectors where they experience exposure to organic or inorganic allergenic or irritant compounds (with an objective of 150 subjects by year) and 250 young workers with no specific occupational exposure. A phone interview focusing on respiratory and 'Ear-Nose-Throat' (ENT) work-related symptoms screen subjects considered as "possibly OA cases". Subjects are invited to participate in a medical visit to complete clinical and lung function investigations, including fractional exhaled nitric oxide (FE_NO) and carbon monoxide (CO) measurements, and to collect blood samples for IgE (Immunoglobulin E) measurements (total IgE and IgE for work-related and common allergens). Markers of oxidative stress and genetic polymorphisms exploration are also assessed. A random sample of 200 "non-cases" (controls) is also visited, following a nested case-control design.

Discussion

This study may allow to describ a latent period between inception of exposure and the rise of the prevalence of asthma symptoms, an information that would be useful for the prevention of OA. Such a time frame would be suited for conducting screening campaigns of this emergent asthma at a stage when occupational hygiene measures and adapted therapeutic interventions might be effective.

Trial registration

Clinical trial registration number is NCT01096537.

Single nucleotide polymorphisms of complement component 5 and periodontitis

BACKGROUND AND OBJECTIVE

Polymorphisms of host defence genes might increase one's risks for periodontitis. This study investigated whether tagging single nucleotide polymorphisms (SNPs) of the gene encoding complement component 5 (C5) are associated with periodontitis in a Hong Kong Chinese population.

MATERIAL AND METHODS

Eleven tagging SNPs of 229 patients with at least moderate periodontitis and 207 control subjects without periodontitis were genotyped using an i-plexGOLD MassARRAY mass-spectrometry system.

RESULTS

Genotype AG of SNP rs17611 was more prevalent in the group of periodontitis patients than in the controls (54.6% vs. 41.7%, p = 0.007). The haplotype CGCA of the haplotype block consisting of rs1035029, rs17611, rs25681 and rs992670 was significantly associated with periodontitis in a dominant model (p = 0.001). The SNP rs17611 showed high linkage disequilibrium with rs1035029, rs25681 and rs992670. Smoking was also significantly associated with periodontitis (p = 0.006).

CONCLUSION

The tagging SNP rs17611 of the C5 gene and smoking may be associated with periodontitis among the Hong Kong Chinese population.

The application of genetic information for regulatory standard setting under the clean air act: a decision-analytic approach

In 2002, the U.S. Environmental Protection Agency (EPA) released an "Interim Policy on Genomics," stating a commitment to developing guidance on the inclusion of genetic information in regulatory decision making. This statement was followed in 2004 by a document exploring the potential implications. Genetic information can play a key role in understanding and quantifying human susceptibility, an essential step in many of the risk assessments used to shape policy. For example, the federal Clean Air Act (CAA) requires EPA to set National Ambient Air Quality Standards (NAAQS) for criteria pollutants at levels to protect even sensitive populations from adverse health effects with an adequate margin of safety. Asthmatics are generally regarded as a sensitive population, yet substantial research gaps in understanding genetic susceptibility and disease have hindered quantitative risk analysis. This case study assesses the potential role of genomic information regarding susceptible populations in the NAAQS process for fine particulate matter (PM(2.5)) under the CAA. In this initial assessment, we model the contribution of a single polymorphism to asthma risk and mortality risk; however, multiple polymorphisms and interactions (gene-gene and gene-environment) are known to play key roles in the disease process. We show that the impact of new information about susceptibility on estimates of population risk or average risk derived from large epidemiological studies depends on the circumstances. We also suggest that analysis of a single polymorphism, or other risk factor such as health status, may or may not change estimates of individual risk enough to alter a particular regulatory decision, but this depends on specific characteristics of the decision and risk information. We also show how new information about susceptibility in the context of the NAAQS for PM(2.5) could have a large impact on the estimated distribution of individual risk. This would occur if a group were consequently identified (based on genetic and/or disease status), that accounted for a disproportionate share of observed effects. Our results highlight certain conditions under which genetic information is likely to have an impact on risk estimates and the balance of costs and benefits within groups, and highlight critical research needs. As future studies explore more fully the relationship between exposure, genetic makeup, and disease status, the opportunity for genetic information and disease status to play pivotal roles in regulation can only increase.

The contact allergen dinitrochlorobenzene (DNCB) and respiratory allergy in the Th2-prone Brown Norway rat

All LMW respiratory allergens known to date can also induce skin allergy in test animals. The question here was if in turn skin allergens can induce allergy in the respiratory tract. Respiratory allergy was tested in Th2-prone Brown Norway (BN) rats by dermal sensitization with the contact allergen dinitrochlorobenzene (DNCB; 1%, day 0; 0.5%, day 7) and a head/nose-only inhalation challenge of 27mg/m3 of DNCB (15 min, day 21), using a protocol that successfully identified chemical respiratory allergens. Skin allergy to DNCB was examined in BN rats and Th1-prone Wistar rats in a local lymph node assay followed by a topical patch challenge of 0.1% DNCB. Sensitization of BN rats via the skin induced DNCB-specific IgG in serum, but not in all animals, and an increased number of CD4+ cells in the lung parenchyma. Subsequent inhalation challenge with DNCB did not provoke apneas or allergic inflammation (signs of respiratory allergy) in the BN rats. However, microarray analysis of mRNA isolated from the lung revealed upregulation of the genes for Ccl2 (MCP-1), Ccl4 (MIP-1beta), Ccl7 and Ccl17. Skin challenge induced considerably less skin irritation and allergic dermatitis in the BN rat than in the Wistar rat. In conclusion, the Th2-prone BN rat appeared less sensitive to DNCB than the Wistar rat; nevertheless, DNCB induced allergic inflammation in the skin of BN rats but even a relatively high challenge concentration did not induce allergy in the respiratory tract, although genes associated with allergy were upregulated in lung tissue.