Do we need genomic research for the prevention of common diseases with environmental causes?

Family history of cancer and lung cancer: Utility of big data and artificial intelligence for exploring the role of genetic risk

OBJECTIVES

Lung Cancer (LC) is a multifactorial disease for which the role of genetic susceptibility has become increasingly relevant. Our aim was to use artificial intelligence (AI) to analyze differences between patients with LC based on family history of cancer (FHC).

MATERIALS AND METHODS

From August 2016 to June 2020 clinical information was obtained from Thoracic Tumors Registry (TTR), a nationwide database sponsored by the Spanish Lung Cancer Group. In addition to descriptive statistical analysis, an AI-assisted analysis was performed. The German Technical Information Library supported the merging of data from the electronic medical records and database of the TTR. The results of the AI-assisted analysis were reported using Knowledge Graph, Unified Schema and descriptive and predictive analyses.

RESULTS

Analyses were performed in two phases: first, conventional statistical analysis including 11,684 patients of those 5,806 had FHC. Median overall survival (OS) for the global population was 23 months (CI 95 %: 21.39-24.61) in patients with FHC versus 21 months (CI 95 %: 19.53-22.48) in patients without FHC (NFHC), p < 0.001. The second AI-assisted analysis included 5,788 patients of those 939 had FHC. 58.48 % of women with FHC had LC. 9.53 % of patients had an EGFR or HER2 mutation or ALK translocation and at least one relative with cancer. A family history of LC was associated with an increased risk of smoking-related LC. Non-smokers with a family history of LC were more likely to have an EGFR mutation in NSCLC. In Bayesian network analysis, 55 % of patients with a family history of LC and never-smokers had an EGFR mutation.

CONCLUSION

In our population, the incidence of LC in patients with a FHC is higher in women and younger patients. FHC is a risk factor and predictor of LC development, especially in people ≤ 50 years. These results were confirmed by conventional statistics and AI-assisted analysis.

Integrating Genome-Wide Association Studies and Gene Expression Profiles With Chemical-Genes Interaction Networks to Identify Chemicals Associated With Colorectal Cancer

Colorectal cancer (CRC) is the third most common cancer and has the second highest mortality rate in global cancer. Exploring the associations between chemicals and CRC has great significance in prophylaxis and therapy of tumor diseases. This study aims to explore the relationships between CRC and environmental chemicals on genetic basis by bioinformatics analysis. The genome-wide association study (GWAS) datasets for CRC were obtained from the UK Biobank. The GWAS data for colon cancer (category C18) includes 2,581 individuals and 449,683 controls, while that of rectal cancer (category C20) includes 1,244 individuals and 451,020 controls. In addition, we derived CRC gene expression datasets from the NCBI-GEO (GSE106582). The chemicals related gene sets were acquired from the comparative toxicogenomics database (CTD). Transcriptome-wide association study (TWAS) analysis was applied to CRC GWAS summary data and calculated the expression association testing statistics by FUSION software. We performed chemicals related gene set enrichment analysis (GSEA) by integrating GWAS summary data, mRNA expression profiles of CRC and the CTD chemical-gene interaction networks to identify relationships between chemicals and genes of CRC. We observed several significant correlations between chemicals and CRC. Meanwhile, we also detected 5 common chemicals between colon and rectal cancer, including methylnitronitrosoguanidine, isoniazid, PD 0325901, sulindac sulfide, and importazole. Our study performed TWAS and GSEA analysis, linked prior knowledge to newly generated data and thereby helped identifying chemicals related to tumor genes, which provides new clues for revealing the associations between environmental chemicals and cancer.

Environmental and genetic contributions to diabetes

Diabetes mellitus (DM) is a heterogeneous group of disorders characterized by persistent hyperglycemia. Its two most common forms are type 1 diabetes (T1D) and type 2 diabetes (T2D), for which genetic and environmental risk factors act in synergy. Because it occurs in children and involves infectious, autoimmune or toxic destruction of the insulin-secreting pancreatic beta-cells, type 1 diabetes has been called juvenile or insulin-deficient diabetes. In type 2, patients can still secrete some insulin but its effectiveness may be attenuated by 'insulin resistance.' There is also a group of rare forms of diabetes in the young which are inherited as monogenetic diseases. Whether one calls the underlying process 'genes vs. environment' or 'nature vs nurture', diabetes occurs at the interface of the two domains. Together with our genetic background we are born tabula rasa-a blank slate upon which the story of life, with all its environmental inputs will be written. There is one proviso: the influence of epigenetic inheritance must also be considered. Thus, in the creation of databases that include "big data" originating from genomic as well as exposome (defined as: the totality of environmental exposure from conception to death), a broad perspective is crucial as these factors act in concert in such chronic illnesses as diabetes that, for example, are likely to require adoption of an appropriate lifestyle change. Also, it is becoming increasingly evident that epigenetic factors can modulate the interplay between genes and environment. Consequently, throughout the life of an individual nature and nurture interact in a complex manner in the development of diabetes. This review addresses the question of the contribution of gene and environment and their interactions in the development of diabetes.

Training Texas Public Health Professionals and Professionals-In-Training in Genomics

PURPOSE

The purpose of this study is to evaluate the effects of genomics training workshops for public health professionals and professionals-in-training.

DESIGN

A pre- and post-test evaluation design with 3-month follow-up.

SETTING AND PARTICIPANTS

Thirteen genomics training workshops were delivered across Texas to 377 public health professionals and professionals-in-training (66.7% were ethnic minorities).

INTERVENTION

Three-hour theory-based, face-to-face genomics training workshops focusing on family health history practice were delivered.

METHODS

We administered surveys prior to the workshops, immediately post-workshops, and at 3-month follow-up to examine the changes in participants' knowledge, attitudes, intention, self-efficacy, and behavior in adopting genomics into public health practice. Linear mixed modeling analyses were used to analyze the quantitative survey data. A content analysis was also conducted for qualitative survey data analysis.

RESULTS

Genomics practice significantly improved among public health professionals at 3-month follow-up (P < .01). For all participants, knowledge, attitudes, intention, and self-efficacy scores increased significantly immediately post-workshop compared to the pre-workshop scores (all Ps < .01). Knowledge and attitudes scores at the 3-month follow-up remained significantly higher than those scores at the pre-workshop (all Ps < .01). The feedback from workshop participants was positive.

CONCLUSION

Our genomics training workshop is an effective program that can be disseminated at a national level to establish genomic competencies among public health professionals and professionals-in-training in the United States.

On the relationship between the heritability and the attributable fraction

Heritability is the most commonly used measure of genetic contribution to disease outcomes. Being the fraction of the variance of latent trait liability attributable to genetic factors, heritability of binary traits is a difficult technical concept that is sometimes misinterpreted as the more-easily understandable concept of attributable fraction. In this paper we use the liability threshold model to describe the analytical relationship between heritability and attributable fraction. Towards this end, we consider a hypothetical intervention that is aimed to reduce the genetic risk of the disease for a specified target group of the population. We show how the relation between the heritability and the attributable fraction depends on the disease prevalence, the intervention effect and the size of the target group. We use two real examples to illustrate the practical implications of our theoretical results.

Association between Family History of Cancer and Lung Cancer Risk among Japanese Men and Women

Although cigarette smoking is a major risk factor for lung cancer, genetic susceptibility may also affect lung cancer risk. To explore the role of genetic risk, this case-control study investigated the association between family history of cancer at several sites and lung cancer risk. A total of 1,733 lung cancer cases and 6,643 controls were selected from patients aged 30 years and over admitted to a single hospital in Japan between 1997 and 2009. Information on family history of cancer was collected using a self-administered questionnaire and odds ratios (ORs) were estimated by unconditional logistic regression. Family history of lung cancer in first-degree relatives was associated with an increased risk of lung cancer among both sexes. According to histology and type of relatives, a parental history of lung cancer was significantly associated with an increased risk of female adenocarcinoma (OR = 1.72). Stratification by smoking status revealed that this significant positive association in women was limited to ever-smokers (OR = 4.13). In men, a history of lung cancer in siblings was significantly associated with an increased risk of small cell carcinoma (OR = 2.28) and adenocarcinoma (OR = 2.25). Otherwise, positive associations between history of breast (OR = 1.99) and total (OR = 1.71) cancers in siblings and the risk of male adenocarcinoma were observed. These results suggest that inherited genetic susceptibility may contribute to the development of lung cancer. In men, shared exposure to environmental factors among siblings may also be responsible for the increase in lung cancer risk.

Gene-nutrient interactions and susceptibility to human obesity

A large number of genome-wide association studies, transferability studies, and candidate gene studies performed in diverse populations around the world have identified gene variants that are associated with common human obesity. The mounting evidence suggests that these obesity gene variants interact with multiple environmental factors and increase susceptibility to this complex metabolic disease. The objective of this review article is to provide concise and updated information on energy balance, heritability of body weight, origins of gene variants, and gene-nutrient interactions in relation to human obesity. It is proposed that knowledge of these related topics will provide valuable insight for future preventative lifestyle intervention using targeted nutritional and medicinal therapies.

The Ethics of Translational Science: Imagining Public Benefit in Gene-Environment Interaction Research

Biomedical research is increasingly informed by expectations of "translation," which call for the production of scientific knowledge that can be used to create services and products that improve health outcomes. In this paper, we ask how translation, in particular the idea of social responsibility, is understood and enacted in the post-genomic life sciences. Drawing on theories examining what constitutes "good science," and interviews with 35 investigators who study the role of gene-environment interactions in the etiology of cancer, diabetes, and cardiovascular disease, we describe the dynamic and unsettled ethics of translational science through which the expected social value of scientific knowledge about complex disease causation is negotiated. To describe how this ethics is formed, we first discuss the politics of knowledge production in interdisciplinary research collectives. Researchers described a commitment to working across disciplines to examine a wide range of possible causes of disease, but they also pointed to persistent disciplinary and ontological divisions that rest on the dominance of molecular conceptions of disease risk. The privileging of molecular-level causation shapes and constrains the kinds of knowledge that can be created about gene-environment interactions. We then turn to scientists' ideas about how this knowledge should be used, including personalized prevention strategies, targeted therapeutics, and public policy interventions. Consensus about the relative value of these anticipated translations was elusive, and many scientists agreed that gene-environment interaction research is part of a shift in biomedical research away from considering important social, economic, political and historical causes of disease and disease disparities. We conclude by urging more explicit engagement with questions about the ethics of translational science in the post-genomic life sciences. This would include a consideration of who will benefit from emerging scientific knowledge, how benefits will accrue, and the ways in which normative assumptions about the public good come to be embedded in scientific objects and procedures.

Accounting for Complexity: Gene-environment Interaction Research and the Moral Economy of Quantification

Scientists now agree that common diseases arise through interactions of genetic and environmental factors, but there is less agreement about how scientific research should account for these interactions. This paper examines the politics of quantification in gene-environment interaction (GEI) research. Drawing on interviews and observations with GEI researchers who study common, complex diseases, we describe quantification as an unfolding moral economy of science, in which researchers collectively enact competing ''virtues.'' Dominant virtues include molecular precision, in which behavioral and social risk factors are moved into the body, and ''harmonization,'' in which scientists create large data sets and common interests in multisited consortia. We describe the negotiations and trade-offs scientists enact in order to produce credible knowledge and the forms of (self-)discipline that shape researchers, their practices, and objects of study. We describe how prevailing techniques of quantification are premised on the shrinking of the environment in the interest of producing harmonized data and harmonious scientists, leading some scientists to argue that social, economic, and political influences on disease patterns are sidelined in postgenomic research. We consider how a variety of GEI researchers navigate quantification's productive and limiting effects on the science of etiological complexity.

Genomic research in Zambia: confronting the ethics, policy and regulatory frontiers in the 21st Century

Genomic research has the potential to increase knowledge in health sciences, but the process has to ensure the safety, integrity and well-being of research participants. A legal framework for the conduct of health research in Zambia is available. However, the ethical, policy and regulatory framework to operationalise genomic research requires a paradigm shift. This paper outlines the current legal and policy framework as well as the ethics environment, and suggests recommendations for Zambia to fully benefit from the opportunity that genomic research presents. This will entail creating national research interest, improving knowledge levels, and building community trust among researchers, policymakers, donors, regulators and, most importantly, patients and research participants. A real balancing act of the risk and benefits will need to be objectively undertaken.

Environmental exposures to metals in Native communities and implications for child development: basis for the Navajo birth cohort study

Two disparate statistics often cited for the Western United States raise concern about risks for developmental disabilities in Native American children. First, 13 of the states with the highest percentage of Native American population are located in the Western United States (U.S. Census Bureau, 2012 ). Second, more than 161,000 abandoned hard-rock mines are located in 12 Western states (General Accounting Office, 2014 ). Moreover, numerous studies have linked low-level metals exposure with birth defects and developmental delays. Concern has emerged among tribal populations that metals exposure from abandoned mines might threaten development of future generations.

Living long and ageing well: is epigenomics the missing link between nature and nurture?

Human longevity is a complex trait and increasingly we understand that both genes and lifestyle interact in the longevity phenotype. Non-genetic factors, including diet, physical activity, health habits, and psychosocial factors contribute approximately 50% of the variability in human lifespan with another 25% explained by genetic differences. Family clusters of nonagenarian and centenarian siblings, who show both exceptional age-span and health-span, are likely to have inherited facilitatory gene groups, but also have nine decades of life experiences and behaviours which have interacted with their genetic profiles. Identification of their shared genes is just one small step in the link from genes to their physical and psychological profiles. Behavioural genomics is beginning to demonstrate links to biological mechanisms through regulation of gene expression, which directs the proteome and influences the personal phenotype. Epigenetics has been considered the missing link between nature and nurture. Although there is much that remains to be discovered, this article will discuss some of genetic and environmental factors which appear important in good quality longevity and link known epigenetic mechanisms to themes identified by nonagenarians themselves related to their longevity. Here we suggest that exceptional 90-year old siblings have adopted a range of behaviours and life-styles which have contributed to their ageing-well-phenotype and which link with important public health messages.

Intrinsic and extrinsic mortality reunited

Intrinsic and extrinsic mortality are often separated in order to understand and measure aging. Intrinsic mortality is assumed to be a result of aging and to increase over age, whereas extrinsic mortality is assumed to be a result of environmental hazards and be constant over age. However, allegedly intrinsic and extrinsic mortality have an exponentially increasing age pattern in common. Theories of aging assert that a combination of intrinsic and extrinsic stressors underlies the increasing risk of death. Epidemiological and biological data support that the control of intrinsic as well as extrinsic stressors can alleviate the aging process. We argue that aging and death can be better explained by the interaction of intrinsic and extrinsic stressors than by classifying mortality itself as being either intrinsic or extrinsic. Recognition of the tight interaction between intrinsic and extrinsic stressors in the causation of aging leads to the recognition that aging is not inevitable, but malleable through the environment.

Mechanisms of action for arsenic in cardiovascular toxicity and implications for risk assessment

The possibility of an association between inorganic arsenic (iAs) exposure and cardiovascular outcomes has received increasing attention in the literature over the past decade. The United States Environmental Protection Agency (US EPA) is currently revising its Integrated Risk Assessment System (IRIS) review of iAs, and one of the non-cancer endpoints of interest is cardiovascular disease (CVD). Despite the increased interest in this area, substantial gaps remain in the available information, particularly regarding the mechanism of action (MOA) by which iAs could cause or exacerbate CVD. Few studies specifically address the plausibility of an association between iAs and CVD at the low exposure levels which are typical in the United States (i.e., below 100 μg As/L in drinking water). We have conducted a review and evaluation of the animal, mechanistic, and human data relevant to the potential MOAs of iAs and CVD. Specifically, we evaluated the most common proposed MOAs, which include disturbance of endothelial function and hepatic dysfunction. Our analysis of the available evidence indicates that there is not a well-established MOA for iAs in the development or progression of CVD. Few human studies of the potential MOAs have addressed plausibility at low doses and the applicability of extrapolation from animal studies to humans is questionable. However, the available evidence indicates that regardless of the specific MOA, the effects of iAs on physiological processes at the cellular level appear to operate via a threshold mechanism. This finding is consistent with the lack of association of CVD with iAs exposure in humans at levels below 100 μg/L, particularly when considering important exposure and risk modifiers such as nutrition and genetics. Based on this analysis, we conclude that there are no data supporting a linear dose-response relationship between iAs and CVD, indicating this relationship has a threshold.

Comparing alternative design options for chronic disease prevention interventions

BACKGROUND

While the randomized clinical trial is considered to provide the highest level of evidence in clinical medicine, its superiority to other study designs in the context of prevention studies is debated. The purpose of this review was (i) to gather evidence about challenges facing both randomized controlled trials and observational designs for the conduct of population-based chronic disease prevention interventions and (ii) to consider the suitability of recently proposed hybrid designs for population-based prevention intervention studies.

METHODS

Rapid review methods were employed for this study. Articles published within 2007-2012, were included if they: (i) discussed challenges or benefits related to any intervention study design, (ii) compared randomized controlled trials (RCT) and observational designs or (iii) introduced a new study design potentially applicable to population-based interventions. After initial screening, papers retained for inclusion were subjected to content analysis and synthesis.

RESULTS

A total of 35 included articles were reviewed and used for synthesis. Both RCTs and observational studies are subject to multiple challenges, the main being external and internal validity for RCTs and observational designs, respectively. Four new hybrid designs identified.

CONCLUSION

Although any high quality design can produce high level of evidence, multiple challenges with prevention intervention RCTs or observational studies identified. New hybrid designs that carry benefits of randomized and observational methods may be the road ahead for to assess the effects of population-based interventions.

Effectiveness of individual-focused interventions to prevent chronic disease

BACKGROUND

The burden of chronic disease is projected to assume crisis proportions in most parts of the world by the middle of the century, focusing attention on the need for preventive interventions. We identify and review published research on primary prevention individual-level interventions in current practice and describe and discuss the limitations of the current evidence. The report facilitates prioritizing a research agenda for potential interventions that might be investigated within cohort studies.

MATERIALS AND METHODS

This study is a rapid review. Computerized database searches (PubMed and EMBASE) were performed in October 2012 to identify articles on primary prevention interventions that are directed at the individual level. Potentially, relevant International Agency of Research on Cancer handbooks and monographs were also reviewed. The review includes articles reported in English on the efficacy or effectiveness of a preventive intervention in an adult population. It excludes articles on alcohol or tobacco smoking.

RESULTS

Many chronic disease interventions directed at individuals report a protective effect in the short term and some evidence for the efficacy of chemoprevention in chronic disease prevention exists. Evidence these effects persist in the longer term is inconsistent.

CONCLUSIONS

There are currently only limited evidence-based preventions for most chronic diseases, for which a summary is available in Table A1 (see Appendix B). Most individual-level intervention research studies have been conducted using case-control designs and some small, randomized studies. There are fewer impediments to lifestyle modifications when compared to prevention using chemoprevention and vaccination or other methods of prevention of persistent infection.

Challenges of SNP genotyping and genetic variation: its future role in diagnosis and treatment of cancer

Thorough annotation of common germline genetic variation in the human genome has generated a foundation for the investigation of the contribution of genetics to the etiology and pathogenesis of cancer. For many malignancies, it has become increasingly apparent that numerous alleles, with small-to-moderate effects, additively contribute to cancer susceptibility. The most common genetic variant in the genome, the single nucleotide polymorphism, is of special interest for the study of susceptibility to and protection from cancer. Similarly, intense effort has focused on genetic variants that can predict either response or toxicity to therapeutic interventions. This review discusses the challenges and prospects of genetic association studies in cancer research. On the basis of recent changes in genomics and high-throughput genotyping platforms, future genetic findings of association studies could impact clinical care and public health screening.

The genetics of childhood obesity and interaction with dietary macronutrients

The genes contributing to childhood obesity are categorized into three different types based on distinct genetic and phenotypic characteristics. These types of childhood obesity are represented by rare monogenic forms of syndromic or non-syndromic childhood obesity, and common polygenic childhood obesity. In some cases, genetic susceptibility to these forms of childhood obesity may result from different variations of the same gene. Although the prevalence for rare monogenic forms of childhood obesity has not increased in recent times, the prevalence of common childhood obesity has increased in the United States and developing countries throughout the world during the past few decades. A number of recent genome-wide association studies and mouse model studies have established the identification of susceptibility genes contributing to common childhood obesity. Accumulating evidence suggests that this type of childhood obesity represents a complex metabolic disease resulting from an interaction with environmental factors, including dietary macronutrients. The objective of this article is to provide a review on the origins, mechanisms, and health consequences of obesity susceptibility genes and interaction with dietary macronutrients that predispose to childhood obesity. It is proposed that increased knowledge of these obesity susceptibility genes and interaction with dietary macronutrients will provide valuable insight for individual, family, and community preventative lifestyle intervention, and eventually targeted nutritional and medicinal therapies.

Assessment of systematic effects of methodological characteristics on candidate genetic associations

Candidate genetic association studies have been found to have a low replication rate in the past. Here, we aimed to assess whether aspects of reported methodological characteristics in genetic association studies may be related to the magnitude of effects observed. An observational, literature-based investigation of 511 case-control studies of genetic association studies indexed in 2007, was undertaken. Meta-regression analyses were used to assess the relationship between 23 reported methodological characteristics and the magnitude of genetic associations. The 511 studies had been conducted in 52 countries and were published in 220 journals (median impact factor 5.1). The multivariate meta-regression model of methodological characteristics plus disease category accounted for 17.2 % of the between-study variance in the magnitude of the reported genetic associations. Our findings are consistent with the view that better conducted and better reported genetic association research may lead to less inflated results.

Advancing the science of environmental exposures during pregnancy and the gene-environment through the National Children's Study

In this article we provide nurses with information on the importance of studying environmental exposures during fetal, infant, and childhood development in the National Children's Study. Nurses should be aware of this study to aid in mitigating the complex health problems that arise from environment-health interactions. Nurses may help to educate the public, patients, and caregivers and are in an ideal position to be strong advocates for policy change and regulatory monitoring and enforcement.

Genetic aspects of skeletal muscle strength and mass with relevance to sarcopenia

Skeletal muscle is a highly heritable quantitative trait, with heritability estimates ranging 30-85% for muscle strength and 50-80% for lean mass. That strong genetic contribution indicates the possibility of using genetic information to individualize treatments for sarcopenia or even aid in prevention strategies through the use of genetic screening prior to the functional limitations. Though these possibilities provide the rationale for genetic studies of skeletal muscle traits, few genes have been identified that appear to contribute to variation in either skeletal muscle strength or mass phenotypes, and sarcopenia per se is remarkably understudied as a trait in this regard. This review examines the heritability of skeletal muscle traits, findings of linkage and genome-wide association analyses and impact of specific genes and gene-sequence variants on these traits as relevant to sarcopenia. Despite considerable work in the area, the genetic underpinnings of skeletal muscle traits remain largely unknown and the genetic aspects of sarcopenia are even less clear. Large-scale longitudinal clinical studies relying on advanced genome-wide association and other techniques are needed to provide further insights into the genes and gene variants that contribute to skeletal muscle strength and mass, and ultimately to susceptibility to sarcopenia.

Stitching together multiple data dimensions reveals interacting metabolomic and transcriptomic networks that modulate cell regulation

DNA variation can be used as a systematic source of perturbation in segregating populations as a way to infer regulatory networks via the integration of large-scale, high-dimensional molecular profiling data.

Cells employ multiple levels of regulation, including transcriptional and translational regulation, that drive core biological processes and enable cells to respond to genetic and environmental changes. Small-molecule metabolites are one category of critical cellular intermediates that can influence as well as be a target of cellular regulations. Because metabolites represent the direct output of protein-mediated cellular processes, endogenous metabolite concentrations can closely reflect cellular physiological states, especially when integrated with other molecular-profiling data. Here we develop and apply a network reconstruction approach that simultaneously integrates six different types of data: endogenous metabolite concentration, RNA expression, DNA variation, DNA–protein binding, protein–metabolite interaction, and protein–protein interaction data, to construct probabilistic causal networks that elucidate the complexity of cell regulation in a segregating yeast population. Because many of the metabolites are found to be under strong genetic control, we were able to employ a causal regulator detection algorithm to identify causal regulators of the resulting network that elucidated the mechanisms by which variations in their sequence affect gene expression and metabolite concentrations. We examined all four expression quantitative trait loci (eQTL) hot spots with colocalized metabolite QTLs, two of which recapitulated known biological processes, while the other two elucidated novel putative biological mechanisms for the eQTL hot spots.

It is now possible to score variations in DNA across whole genomes, RNA levels and alternative isoforms, metabolite levels, protein levels and protein state information, protein–protein interactions, and protein–DNA interactions, in a comprehensive fashion in populations of individuals. Interactions among these molecular entities define the complex web of biological processes that give rise to all higher order phenotypes, including disease. The development of analytical approaches that simultaneously integrate different dimensions of data is essential if we are to extract the meaning from large-scale data to elucidate the complexity of living systems. Here, we use a novel Bayesian network reconstruction algorithm that simultaneously integrates DNA variation, RNA levels, metabolite levels, protein–protein interaction data, protein–DNA binding data, and protein–small-molecule interaction data to construct molecular networks in yeast. We demonstrate that these networks can be used to infer causal relationships among genes, enabling the identification of novel genes that modulate cellular regulation. We show that our network predictions either recapitulate known biology or can be prospectively validated, demonstrating a high degree of accuracy in the predicted network.

A new public health genomics model for common complex diseases, with an application to common behavioral disorders

AIM

In the light of common forms of gene-environment interplay, particularly epigenomics and ecogenetics, the incorporation of envirome data into public health genomics models becomes necessary. Developing and restructuring public health genomics models is essential within the context of common complex diseases.

MATERIALS & METHODS

We developed a novel theoretical model integrating a gene-environment interaction paradigm into public health genomics, which integrates four main sources of data: personal genome data, personal envirome data, molecular genetic/genomic evidence and environmental factors implicated in gene-environment interactions underlying common complex disease phenotypes. Collectively, this knowledge is fed into public health policy development.

RESULTS

This model is the first public health genomics model that incorporates gene-environment interactions within the context of common complex disorders, and is applied to behavioral conditions.

CONCLUSION

Our model proposes, for the first time, an understanding of behavioral disorders from the genomic perspective, combining it with known environmental factors within the framework of public health. Application of this model will enable evidence-based behavioral interventions at the public health level and facilitate genome-based public health policy development for behavioral conditions.

Methylmercury: a potential environmental risk factor contributing to epileptogenesis

Epilepsy or seizure disorder is one of the most common neurological diseases in humans. Although genetic mutations in ion channels and receptors and some other risk factors such as brain injury are linked to epileptogenesis, the underlying cause for the majority of epilepsy cases remains unknown. Gene-environment interactions are thought to play a critical role in the etiology of epilepsy. Exposure to environmental chemicals is an important risk factor. Methylmercury (MeHg) is a prominent environmental neurotoxicant, which targets primarily the central nervous system (CNS). Patients or animals with acute or chronic MeHg poisoning often display epileptic seizures or show increased susceptibility to seizures, suggesting that MeHg exposure may be associated with epileptogenesis. This mini-review highlights the effects of MeHg exposure, especially developmental exposure, on the susceptibility of humans and animals to seizures, and discusses the potential role of low level MeHg exposure in epileptogenesis. This review also proposes that a preferential effect of MeHg on the inhibitory GABAergic system, leading to disinhibition of excitatory glutamatergic function, may be one of the potential mechanisms underlying MeHg-induced changes in seizure susceptibility.

On the very idea of genetic justice. Why Farrelly’s pluralistic prioritarianism cannot tackle genetic complexity

Innovations in science and technology are often the source of public concern, but few have generated debates as intense and at the same time with such a popular fascination as those surrounding genetic technologies. Unequal access to preimplantation diagnosis could give some individuals the opportunity to select children with more advantageous predispositions.

Research review: gene-environment interaction research in youth depression - a systematic review with recommendations for future research

BACKGROUND

Depression is a major public health problem among youth, currently estimated to affect as many as 9% of US children and adolescents. The recognition that both genes (nature) and environments (nurture) are important for understanding the etiology of depression has led to a rapid growth in research exploring gene-environment interactions (GxE). However, there has been no systematic review of GxE in youth depression to date.

METHODS

The goal of this article was to systematically review evidence on the contribution of GxE to the risk of child and adolescent depression. Through a search of PubMed and PsycINFO databases to 1 April 2010, we identified 20 candidate gene-environment interaction studies focused on depression in youth (up to age 26) and compared each study in terms of the following characteristics: research design and sample studied; measure of depression and environment used; genes explored; and GxE findings in relation to these factors.

RESULTS

In total, 80% of studies (n = 16) found at least one significant GxE association. However, there was wide variation in methods and analyses adopted across studies, especially with respect to environmental measures used and tests conducted to estimate GxE. This heterogeneity made it difficult to compare findings and evaluate the strength of the evidence for GxE.

CONCLUSIONS

The existing body of GxE research on depression in youth contains studies that are conceptually and methodologically quite different, which contributes to mixed findings and makes it difficult to assess the current state of the evidence. To decrease this heterogeneity, we offer 20 recommendations that are focused on: (a) reporting GxE research; (b) testing and reporting GxE effects; (c) conceptualizing, measuring and analyzing depression; (d) conceptualizing, measuring and analyzing environment; (e) increasing power to test for GxE; and (f) improving the quality of genetic data used. Although targeted to GxE research on depression, these recommendations can be adopted by GxE researchers focusing on other mental health outcomes.

Beyond base pairs to bedside: a population perspective on how genomics can improve health

A decade after the sequencing of the human genome, the National Human Genome Research Institute announced a strategic plan for genomic medicine. It calls for evaluating the structure and biology of genomes, understanding the biology of disease, advancing the science of medicine, and improving the effectiveness of health care. Fulfilling the promise of genomics urgently requires a population perspective to complement the bench-to-bedside model of translation. A population approach should assess the contribution of genomics to health in the context of social and environmental determinants of disease; evaluate genomic applications that may improve health care; design strategies for integrating genomics into practice; address ethical, legal, and social issues; and measure the population health impact of new technologies.

Gene-diet interactions in childhood obesity

Childhood overweight and obesity have reached epidemic proportions worldwide, and the increase in weight-associated co-morbidities including premature type 2 diabetes mellitus (T2DM) and atherosclerotic cardiovascular disease will soon become major healthcare and economic problems. A number of studies now indicate that the childhood obesity epidemic which has emerged during the past 30 years is a complex multi-factorial disease resulting from interaction of susceptibility genes with an obesogenic environment. This review will focus on gene-diet interactions suspected of having a prominent role in promoting childhood obesity. In particular, the specific genes that will be presented (FTO, MC4R, and NPC1) have recently been associated with childhood obesity through a genome-wide association study (GWAS) and were shown to interact with nutritional components to increase weight gain. Although a fourth gene (APOA2) has not yet been associated with childhood obesity, this review will also present information on what now represents the best characterized gene-diet interaction in promoting weight gain.

Human genetics and islam: scientific and medical aspects

Objective:

To relate diverse aspects of genetics and its applications to concepts in the Glorious Qur’an and the ḥadīth.

Study Design:

The author compared passages from the Glorious Qur’an and ḥadīth with modern concepts in genetics, such as recessive inheritance, genetic counseling, genetic variation, cytoplasmic inheritance, sex chromosomes, genetics-environment interactions, gender determination, and the hypothesis of “pairing in the universe.”

Conclusions:

A fresh understanding of Islamic scripture reveals references to principles of genetics that predate contemporary discoveries. This highlights the need for further exploration of possible links between science and religion.

Current priorities for public health practice in addressing the role of human genomics in improving population health

In spite of accelerating human genome discoveries in a wide variety of diseases of public health significance, the promise of personalized health care and disease prevention based on genomics has lagged behind. In a time of limited resources, public health agencies must continue to focus on implementing programs that can improve health and prevent disease now. Nevertheless, public health has an important and assertive leadership role in addressing the promise and pitfalls of human genomics for population health. Such efforts are needed not only to implement what is known in genomics to improve health but also to reduce potential harm and create the infrastructure needed to derive health benefits in the future.

Inter-generational continuity in periodontal health: findings from the Dunedin family history study

OBJECTIVE

To determine whether parental periodontal disease history is a risk factor for periodontal disease in adult offspring.

METHODS

Proband periodontal examination [combined attachment loss (CAL) at age 32, and incidence of CAL from ages 26 to 32] and interview data were collected during the age-32 assessments in the Dunedin Study. Parental data were also collected. The sample was divided into two familial-risk groups for periodontal disease (high- and low-risk) based on parents' self-reported periodontal disease.

RESULTS

Periodontal risk analysis involved 625 proband-parent(s) groups. After controlling for confounding factors, the high-familial-risk periodontal group was more likely to have 1+ sites with 4+mm CAL [relative risk (RR) 1.45; 95% confidence interval (CI) 1.11-1.88], 2+ sites with 4+mm CAL (RR 1.45; 95% CI 1.03-2.05), 1+ sites with 5+mm CAL (RR 1.60; 95% CI 1.02-2.50), and 1+ sites with 3+mm incident CAL (RR 1.64; 95% CI 1.01-2.66) than the low-familial-risk group. Predictive validity was enhanced when information was available from both parents.

CONCLUSIONS

Parents with poor periodontal health tend to have offspring with poor periodontal health. Family/parental history of oral health is a valid representation of the shared genetic and environmental factors that contribute to an individual's periodontal status, and may help to predict patient prognosis and preventive treatment need.

Intergenerational continuity in oral health: a review

Life course research considers not only the influences on health which act during the lifespan but it is also concerned with factors that act across generations. Rarely are genetics or environment solely responsible for producing individual variation; virtually all characteristics are the result of gene-environment interaction. An increasing interest in life course research and gene-environment interactions is reflected in greater awareness of the role of family history and intergenerational continuity in oral health as a practical, inexpensive approach to categorizing genetic risk for many common, preventable disorders of adulthood (including oral disease). Does the health status of one generation have an effect on that of the next? While researchers in recent years have begun to investigate the inter-generational associations between exposures and disease, little research has been carried out (to date) on the long-term biological, behavioural, psychological, social and environmental mechanisms that link oral health and oral disease risk to exposures acting across generations. This narrative review identifies studies which have contributed to highlighting some of the intergenerational factors influencing oral health. However, there is a need for a wider perspective on intergenerational continuity in oral health, along with a careful evaluation of the factors which contribute to the effect. A comprehensive investigation into the nature and extent of intergenerational transmission of oral health is required.

APOA5 gene variation interacts with dietary fat intake to modulate obesity and circulating triglycerides in a Mediterranean population

APOA5 is one of the strongest regulators of plasma TG concentrations; nevertheless, its mechanisms of action are poorly characterized. Genetic variability at the APOA5 locus has also been associated with increased cardiovascular disease risk; however, this predisposition could be attenuated in the context of a prudent diet as traditionally consumed in the Mediterranean countries. We have investigated the interaction between a single nucleotide polymorphism (SNP) at the APOA5 gene (-1131T > C) and dietary fat that may modulate TG-rich lipoprotein concentrations and anthropometric measures in overweight and obese participants. We recruited 1465 participants from a Spanish population (20-65 y old; BMI 25-40 kg/m(2)) attending outpatient obesity clinics. Consistent with previous reports, we found an association between the APOA5-1131T > C SNP and TG-rich lipoprotein concentrations that were higher in carriers of the minor allele than in noncarriers (P < 0.001). Moreover, we found a significant genotype-dietary fat interaction for obesity traits. Participants homozygous for the -1131T major allele had a positive association between fat intake and obesity, whereas in those carrying the APOA5-1131C minor allele, higher fat intakes were not associated with higher BMI. Likewise, we found genotype-dietary fat interactions for TG-rich lipoproteins (P < 0.001). In conclusion, we have replicated previous gene-diet interactions between APOA5 -1131T > C SNP and fat intake for obesity traits and detected a novel interaction for TG-rich lipoprotein concentrations. Our data support the hypothesis that the minor C-allele may protect those consuming a high-fat diet from obesity and elevated concentrations of TG-rich lipoproteins.

The Development of a Spanish Language Instrument to Measure Genetic Knowledge of Diabetes Mellitus Type 2

Purpose: The purpose of this study was to develop a Spanish-language measure of genetic knowledge relevant to type 2 diabetes for use with members of the ethnically heterogeneous U.S. Latino community. Design: Review of the literature and expert content analysis guided initial instrument development. The instrument was pretested in three cognitive interview waves with 36 Latinos representative of Mexican, Central and South American, and Cuban heritage. Interview analysis indicated potential sources of response error and guided an iterative process of instrument refinement. Results: Difficulties associated with item interpretation, grammatical structure, and comprehension were identified. Analysis indicated that revisions improved item quality and enhanced cultural and linguistic appropriateness of the instrument. Conclusions: Field testing suggested initial validity of a Spanish-language instrument to measure genetic knowledge relative to type 2 diabetes. Implications for Practice: A Spanish-language measure of genetic knowledge can guide nursing interventions that support culturally appropriate integration of genetics into health care.

Nature versus nurture: death of a dogma, and the road ahead

Interaction between the genome and the environment has been widely discussed in the literature, but has the importance ascribed to understanding these interactions been overstated? In this opinion piece, we critically discuss gene-environment interactions and attempt to answer three key questions. First, is it likely that gene-environment interactions actually exist? Second, what is the realistic value of trying to unravel these interactions, both in terms of understanding disease pathogenesis and as a means of ameliorating disease? Finally, and most importantly, do the technologies and methodologies exist to facilitate an unbiased search for gene-environment interactions? Addressing these questions highlights key areas of feasibility that must be considered in this area of research.

Future health applications of genomics: priorities for communication, behavioral, and social sciences research

Despite the quickening momentum of genomic discovery, the communication, behavioral, and social sciences research needed for translating this discovery into public health applications has lagged behind. The National Human Genome Research Institute held a 2-day workshop in October 2008 convening an interdisciplinary group of scientists to recommend forward-looking priorities for translational research. This research agenda would be designed to redress the top three risk factors (tobacco use, poor diet, and physical inactivity) that contribute to the four major chronic diseases (heart disease, type 2 diabetes, lung disease, and many cancers) and account for half of all deaths worldwide. Three priority research areas were identified: (1) improving the public's genetic literacy in order to enhance consumer skills; (2) gauging whether genomic information improves risk communication and adoption of healthier behaviors more than current approaches; and (3) exploring whether genomic discovery in concert with emerging technologies can elucidate new behavioral intervention targets. Important crosscutting themes also were identified, including the need to: (1) anticipate directions of genomic discovery; (2) take an agnostic scientific perspective in framing research questions asking whether genomic discovery adds value to other health promotion efforts; and (3) consider multiple levels of influence and systems that contribute to important public health problems. The priorities and themes offer a framework for a variety of stakeholders, including those who develop priorities for research funding, interdisciplinary teams engaged in genomics research, and policymakers grappling with how to use the products born of genomics research to address public health challenges.

Approaches to advancing quantitative human health risk assessment of environmental chemicals in the post-genomic era

The contribution of genomics and associated technologies to human health risk assessment for environmental chemicals has focused largely on elucidating mechanisms of toxicity, as discussed in other articles in this issue. However, there is interest in moving beyond hazard characterization to making more direct impacts on quantitative risk assessment (QRA)--i.e., the determination of toxicity values for setting exposure standards and cleanup values. We propose that the evolution of QRA of environmental chemicals in the post-genomic era will involve three, somewhat overlapping phases in which different types of approaches begin to mature. The initial focus (in Phase I) has been and continues to be on "augmentation" of weight of evidence--using genomic and related technologies qualitatively to increase the confidence in and scientific basis of the results of QRA. Efforts aimed towards "integration" of these data with traditional animal-based approaches, in particular quantitative predictors, or surrogates, for the in vivo toxicity data to which they have been anchored are just beginning to be explored now (in Phase II). In parallel, there is a recognized need for "expansion" of the use of established biomarkers of susceptibility or risk of human diseases and disorders for QRA, particularly for addressing the issues of cumulative assessment and population risk. Ultimately (in Phase III), substantial further advances could be realized by the development of novel molecular and pathway-based biomarkers and statistical and in silico models that build on anticipated progress in understanding the pathways of human diseases and disorders. Such efforts would facilitate a gradual "reorientation" of QRA towards approaches that more directly link environmental exposures to human outcomes.