Principles and Practices of Returning Individual Research Results to Participants in Large Studies of Pregnancy and Childhood.

Investigators conducting human subject research have typically conveyed only clinically actionable results back to individual participants. Shifting scientific culture around viewing participants as partners in research, however, is prompting investigators to consider returning as much data or results as the participant would like, even if they are not clearly actionable. Expanding return of individual results may add value for individual participants and their communities, refine future research questions and methods, build trust, and enhance retention of participants. Yet, gaps remain in understanding the implications of these changes for groups of 'vulnerable' participants, including pregnant and pediatric participants. We present the findings of a National Institutes of Health workshop on returning individual research results, particularly as applicable to pregnant and pediatric participants. Research participants who were panelists at the workshop agreed that they desire to receive their results. Workshop findings and current literature indicate that participants have differing preferences for what results they receive. One way to address the limits of current practice is to develop flexible digital platforms that convey individual results along with researchers' availability to answer questions, and to provide as much information as possible about actionable steps to control environmental exposures associated with disease risk.

Lessons Learned From Past Gene-Environment Interaction Successes.

Genetic and environmental factors are both known to contribute to susceptibility to complex diseases. Therefore, the study of gene-environment interaction (G×E) has been a focus of research for several years. In this article, select examples of G×E from the literature are described to highlight different approaches and underlying principles related to the success of these studies. These examples can be broadly categorized as studies of single metabolism genes, genes in complex metabolism pathways, ranges of exposure levels, functional approaches and model systems, and pharmacogenomics. Some studies illustrated the success of studying exposure metabolism for which candidate genes can be identified. Moreover, some G×E successes depended on the availability of high-quality exposure assessment and longitudinal measures, study populations with a wide range of exposure levels, and the inclusion of ethnically and geographically diverse populations. In several examples, large population sizes were required to detect G×Es. Other examples illustrated the impact of accurately defining scale of the interactions (i.e., additive or multiplicative). Last, model systems and functional approaches provided insights into G×E in several examples. Future studies may benefit from these lessons learned.

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

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

Genetic simulation tools for post-genome wide association studies of complex diseases.

Genetic simulation programs are used to model data under specified assumptions to facilitate the understanding and study of complex genetic systems. Standardized data sets generated using genetic simulation are essential for the development and application of novel analytical tools in genetic epidemiology studies. With continuing advances in high-throughput genomic technologies and generation and analysis of larger, more complex data sets, there is a need for updating current approaches in genetic simulation modeling. To provide a forum to address current and emerging challenges in this area, the National Cancer Institute (NCI) sponsored a workshop, entitled "Genetic Simulation Tools for Post-Genome Wide Association Studies of Complex Diseases" at the National Institutes of Health (NIH) in Bethesda, Maryland on March 11-12, 2014. The goals of the workshop were to (1) identify opportunities, challenges, and resource needs for the development and application of genetic simulation models; (2) improve the integration of tools for modeling and analysis of simulated data; and (3) foster collaborations to facilitate development and applications of genetic simulation. During the course of the meeting, the group identified challenges and opportunities for the science of simulation, software and methods development, and collaboration. This paper summarizes key discussions at the meeting, and highlights important challenges and opportunities to advance the field of genetic simulation.

Leveraging data science and machine learning for urban climate adaptation in two major African cities: a HE2AT Center study protocol.

INTRODUCTION: African cities, particularly Abidjan and Johannesburg, face challenges of rapid urban growth, informality and strained health services, compounded by increasing temperatures due to climate change. This study aims to understand the complexities of heat-related health impacts in these cities. The objectives are: (1) mapping intraurban heat risk and exposure using health, socioeconomic, climate and satellite imagery data; (2) creating a stratified heat-health forecast model to predict adverse health outcomes; and (3) establishing an early warning system for timely heatwave alerts. The ultimate goal is to foster climate-resilient African cities, protecting disproportionately affected populations from heat hazards. METHODS AND ANALYSIS: The research will acquire health-related datasets from eligible adult clinical trials or cohort studies conducted in Johannesburg and Abidjan between 2000 and 2022. Additional data will be collected, including socioeconomic, climate datasets and satellite imagery. These resources will aid in mapping heat hazards and quantifying heat-health exposure, the extent of elevated risk and morbidity. Outcomes will be determined using advanced data analysis methods, including statistical evaluation, machine learning and deep learning techniques. ETHICS AND DISSEMINATION: The study has been approved by the Wits Human Research Ethics Committee (reference no: 220606). Data management will follow approved procedures. The results will be disseminated through workshops, community forums, conferences and publications. Data deposition and curation plans will be established in line with ethical and safety considerations.

Protocol of an individual participant data meta-analysis to quantify the impact of high ambient temperatures on maternal and child health in Africa (HE2AT IPD).

INTRODUCTION: Globally, recognition is growing of the harmful impacts of high ambient temperatures (heat) on health in pregnant women and children. There remain, however, major evidence gaps on the extent to which heat increases the risks for adverse health outcomes, and how this varies between settings. Evidence gaps are especially large in Africa. We will conduct an individual participant data (IPD) meta-analysis to quantify the impacts of heat on maternal and child health in sub-Saharan Africa. A detailed understanding and quantification of linkages between heat, and maternal and child health is essential for developing solutions to this critical research and policy area. METHODS AND ANALYSIS: We will use IPD from existing, large, longitudinal trial and cohort studies, on pregnant women and children from sub-Saharan Africa. We will systematically identify eligible studies through a mapping review, searching data repositories, and suggestions from experts. IPD will be acquired from data repositories, or through collaboration with data providers. Existing satellite imagery, climate reanalysis data, and station-based weather observations will be used to quantify weather and environmental exposures. IPD will be recoded and harmonised before being linked with climate, environmental, and socioeconomic data by location and time. Adopting a one-stage and two-stage meta-analysis method, analytical models such as time-to-event analysis, generalised additive models, and machine learning approaches will be employed to quantify associations between exposure to heat and adverse maternal and child health outcomes. ETHICS AND DISSEMINATION: The study has been approved by ethics committees. There is minimal risk to study participants. Participant privacy is protected through the anonymisation of data for analysis, secure data transfer and restricted access. Findings will be disseminated through conferences, journal publications, related policy and research fora, and data may be shared in accordance with data sharing policies of the National Institutes of Health. PROSPERO REGISTRATION NUMBER: CRD42022346068.

Gene-environment interactions within a precision environmental health framework.

Understanding the complex interplay of genetic and environmental factors in disease etiology and the role of gene-environment interactions (GEIs) across human development stages is important. We review the state of GEI research, including challenges in measuring environmental factors and advantages of GEI analysis in understanding disease mechanisms. We discuss the evolution of GEI studies from candidate gene-environment studies to genome-wide interaction studies (GWISs) and the role of multi-omics in mediating GEI effects. We review advancements in GEI analysis methods and the importance of large-scale datasets. We also address the translation of GEI findings into precision environmental health (PEH), showcasing real-world applications in healthcare and disease prevention. Additionally, we highlight societal considerations in GEI research, including environmental justice, the return of results to participants, and data privacy. Overall, we underscore the significance of GEI for disease prediction and prevention and advocate for integrating the exposome into PEH omics studies.

Next generation analytic tools for large scale genetic epidemiology studies of complex diseases.

Over the past several years, genome-wide association studies (GWAS) have succeeded in identifying hundreds of genetic markers associated with common diseases. However, most of these markers confer relatively small increments of risk and explain only a small proportion of familial clustering. To identify obstacles to future progress in genetic epidemiology research and provide recommendations to NIH for overcoming these barriers, the National Cancer Institute sponsored a workshop entitled "Next Generation Analytic Tools for Large-Scale Genetic Epidemiology Studies of Complex Diseases" on September 15-16, 2010. The goal of the workshop was to facilitate discussions on (1) statistical strategies and methods to efficiently identify genetic and environmental factors contributing to the risk of complex disease; and (2) how to develop, apply, and evaluate these strategies for the design, analysis, and interpretation of large-scale complex disease association studies in order to guide NIH in setting the future agenda in this area of research. The workshop was organized as a series of short presentations covering scientific (gene-gene and gene-environment interaction, complex phenotypes, and rare variants and next generation sequencing) and methodological (simulation modeling and computational resources and data management) topic areas. Specific needs to advance the field were identified during each session and are summarized.

Seminar: Extracellular Vesicles as Mediators of Environmental Stress in Human Disease.

BACKGROUND: Extracellular vesicles (EVs), membrane-bound particles containing a variety of RNA types, DNA, proteins, and other macromolecules, are now appreciated as an important means of communication between cells and tissues, both in normal cellular physiology and as a potential indicator of cellular stress, environmental exposures, and early disease pathogenesis. Extracellular signaling through EVs is a growing field of research for understanding fundamental mechanisms of health and disease and for the potential for biomarker discovery and therapy development. EVs are also known to play important roles in mediating the effects of exposure to environmental stress. OBJECTIVES: This seminar addresses the application of new tools and approaches for EV research, developed in part through the National Institutes of Health (NIH) Extracellular RNA Communication Program, and reflects presentations and discussions from a workshop held 27-28 September 2021 by the National Institute of Environmental Health Sciences (NIEHS) and the National Center for Advancing Translational Sciences (NCATS) on "Extracellular Vesicles, Exosomes, and Cell-Cell Signaling in Response to Environmental Stress." The panel of experts discussed current research on EVs and environmental exposures, highlighted recent advances in EV isolation and characterization, and considered research gaps and opportunities toward identifying and characterizing the roles for EVs in environmentally related diseases, as well as the current challenges and opportunities in this field. DISCUSSION: The authors discuss the application of new experimental models, particularly organ-on-chip (OOC) systems and in vitro approaches and how these have the potential to extend findings in population-based studies of EVs in exposure-related diseases. Given the complex challenges of identifying cell-specific EVs related to environmental exposures, as well as the general heterogeneity and variability in EVs in blood and other accessible biological samples, there is a critical need for rigorous reporting of experimental methods and validation studies. The authors note that these efforts, combined with cross-disciplinary approaches, would ensure that future research efforts in environmental health studies on EV biomarkers are rigorous and reproducible. https://doi.org/10.1289/EHP12980.

Gene-environment interplay in common complex diseases: forging an integrative model­recommendations from an NIH workshop.

Although it is recognized that many common complex diseases are a result of multiple genetic and environmental risk factors, studies of gene-environment interaction remain a challenge and have had limited success to date. Given the current state-of-the-science, NIH sought input on ways to accelerate investigations of gene-environment interplay in health and disease by inviting experts from a variety of disciplines to give advice about the future direction of gene-environment interaction studies. Participants of the NIH Gene-Environment Interplay Workshop agreed that there is a need for continued emphasis on studies of the interplay between genetic and environmental factors in disease and that studies need to be designed around a multifaceted approach to reflect differences in diseases, exposure attributes, and pertinent stages of human development. The participants indicated that both targeted and agnostic approaches have strengths and weaknesses for evaluating main effects of genetic and environmental factors and their interactions. The unique perspectives represented at the workshop allowed the exploration of diverse study designs and analytical strategies, and conveyed the need for an interdisciplinary approach including data sharing, and data harmonization to fully explore gene-environment interactions. Further, participants also emphasized the continued need for high-quality measures of environmental exposures and new genomic technologies in ongoing and new studies.

What about the environment? Leveraging multi-omic datasets to characterize the environment's role in human health.

The environment plays an important role in mediating human health. In this session we consider research addressing ways to overcome the challenges associated with studying the multifaceted and ever-changing environment. Environmental health research has a need for technological and methodological advances which will further our knowledge of how exposures precipitate complex phenotypes and exacerbate disease.

The Impact of Environmental Factors on Monogenic Mendelian Diseases.

Environmental factors and gene-environment interactions modify the variable expressivity, progression, severity, and onset of some classic (monogenic) Mendelian-inherited genetic diseases. Cystic fibrosis, Huntington disease, Parkinson's disease, and sickle cell disease are examples of well-known Mendelian disorders that are influenced by exogenous exposures. Environmental factors may act by direct or indirect mechanisms to modify disease severity, timing, and presentation, including through epigenomic influences, protein misfolding, miRNA alterations, transporter activity, and mitochondrial effects. Because pathological features of early-onset Mendelian diseases can mimic later onset complex diseases, we propose that studies of environmental exposure vulnerabilities using monogenic model systems of rare Mendelian diseases have high potential to provide insight into complex disease phenotypes arising from multi-genetic/multi-toxicant interactions. Mendelian disorders can be modeled by homologous mutations in animal model systems with strong recapitulation of human disease etiology and natural history, providing an important advantage for study of these diseases. Monogenic high penetrant mutations are ideal for toxicant challenge studies with a wide variety of environmental stressors, because background genetic variability may be less able to alter the relatively strong phenotype driving disease-causing mutations. These models promote mechanistic understandings of gene-environment interactions and biological pathways relevant to both Mendelian and related sporadic complex disease outcomes by creating a sensitized background for relevant environmental risk factors. Additionally, rare disease communities are motivated research participants, creating the potential of strong research allies among rare Mendelian disease advocacy groups and disease registries and providing a variety of translational opportunities that are under-utilized in genetic or environmental health science.

Beyond the looking glass: recent advances in understanding the impact of environmental exposures on neuropsychiatric disease.

The etiologic pathways leading to neuropsychiatric diseases remain poorly defined. As genomic technologies have advanced over the past several decades, considerable progress has been made linking neuropsychiatric disorders to genetic underpinnings. Interest and consideration of nongenetic risk factors (e.g., lead exposure and schizophrenia) have, in contrast, lagged behind heritable frameworks of explanation. Thus, the association of neuropsychiatric illness to environmental chemical exposure, and their potential interactions with genetic susceptibility, are largely unexplored. In this review, we describe emerging approaches for considering the impact of chemical risk factors acting alone and in concert with genetic risk, and point to the potential role of epigenetics in mediating exposure effects on transcription of genes implicated in mental disorders. We highlight recent examples of research in nongenetic risk factors in psychiatric disorders that point to potential shared biological mechanisms-synaptic dysfunction, immune alterations, and gut-brain interactions. We outline new tools and resources that can be harnessed for the study of environmental factors in psychiatric disorders. These tools, combined with emerging experimental evidence, suggest that there is a need to broadly incorporate environmental exposures in psychiatric research, with the ultimate goal of identifying modifiable risk factors and informing new treatment strategies for neuropsychiatric disease.

Environmental Health Research in Africa: Important Progress and Promising Opportunities.

The World Health Organization in 2016 estimated that over 20% of the global disease burden and deaths were attributed to modifiable environmental factors. However, data clearly characterizing the impact of environmental exposures and health endpoints in African populations is limited. To describe recent progress and identify important research gaps, we reviewed literature on environmental health research in African populations over the last decade, as well as research incorporating both genomic and environmental factors. We queried PubMed for peer-reviewed research articles, reviews, or books examining environmental exposures and health outcomes in human populations in Africa. Searches utilized medical subheading (MeSH) terms for environmental exposure categories listed in the March 2018 US National Report on Human Exposure to Environmental Chemicals, which includes chemicals with worldwide distributions. Our search strategy retrieved 540 relevant publications, with studies evaluating health impacts of ambient air pollution (n=105), indoor air pollution (n = 166), heavy metals (n = 130), pesticides (n = 95), dietary mold (n = 61), indoor mold (n = 9), per- and polyfluoroalkyl substances (PFASs, n = 0), electronic waste (n = 9), environmental phenols (n = 4), flame retardants (n = 8), and phthalates (n = 3), where publications could belong to more than one exposure category. Only 23 publications characterized both environmental and genomic risk factors. Cardiovascular and respiratory health endpoints impacted by air pollution were comparable to observations in other countries. Air pollution exposures unique to Africa and some other resource limited settings were dust and specific occupational exposures. Literature describing harmful health effects of metals, pesticides, and dietary mold represented a context unique to Africa. Studies of exposures to phthalates, PFASs, phenols, and flame retardants were very limited. These results underscore the need for further focus on current and emerging environmental and chemical health risks as well as better integration of genomic and environmental factors in African research studies. Environmental exposures with distinct routes of exposure, unique co-exposures and co-morbidities, combined with the extensive genomic diversity in Africa may lead to the identification of novel mechanisms underlying complex disease and promising potential for translation to global public health.

Integrating environmental health and genomics research in Africa: challenges and opportunities identified during a Human Heredity and Health in Africa (H3Africa) Consortium workshop.

Individuals with African ancestry have extensive genomic diversity but have been underrepresented in genomic research. There is also extensive global diversity in the exposome (the totality of human environmental exposures from conception onwards) which should be considered for integrative genomic and environmental health research in Africa. To address current research gaps, we organized a workshop on environmental health research in Africa in conjunction with the H3Africa Consortium and the African Society of Human Genetics meetings in Kigali, Rwanda. The workshop was open to all researchers with an interest in environmental health in Africa and involved presentations from experts within and outside of the Consortium. This workshop highlighted innovative research occurring on the African continent related to environmental health and the interplay between the environment and the human genome. Stories of success, challenges, and collaborative opportunities were discussed through presentations, breakout sessions, poster presentations, and a panel discussion. The workshop informed participants about environmental risk factors that can be incorporated into current or future epidemiology studies and addressed research design considerations, biospecimen collection and storage, biomarkers for measuring chemical exposures, laboratory strategies, and statistical methodologies. Inclusion of environmental exposure measurements with genomic data, including but not limited to H3Africa projects, can offer a strong platform for building gene-environment (G x E) research in Africa. Opportunities to leverage existing resources and add environmental exposure data for ongoing and planned studies were discussed. Future directions include expanding the measurement of both genomic and exposomic risk factors and incorporating sophisticated statistical approaches for analyzing high dimensional G x E data. A better understanding of how environmental and genomic factors interact with nutrition and infection is also needed. Considering that the environment represents many modifiable risk factors, these research findings can inform intervention and prevention efforts towards improving global health.

Expanding the Concept of Translational Research: Making a Place for Environmental Health Sciences.

SUMMARY: The National Institute of Environmental Health Sciences (NIEHS) introduces a new translational research framework that builds upon previous biomedical models to create a more comprehensive and integrated environmental health paradigm. The framework was developed as a graphical construct that illustrates the complexity of designing, implementing, and tracking translational research in environmental health. We conceptualize translational research as a series of concentric rings and nodes, defining "translation" as movement either from one ring to another or between nodes on a ring. A "Fundamental Questions" ring expands upon the research described in other frameworks as "basic" to include three interrelated concepts critical to basic science research: research questions, experimental settings, and organisms. This feature enables us to capture more granularity and thus facilitates an approach for categorizing translational research and its growth over time. We anticipate that the framework will help researchers develop compelling long-term translational research stories and accelerate public health impacts by clearly mapping out opportunities for collaborations. By using this paradigm, researchers everywhere will be better positioned to design research programs, identify research partners based on cross-disciplinary research needs, identify stakeholders who are likely to use the research for environmental decision-making and intervention, and track progress toward common goals. https://doi.org/10.1289/EHP3657.

New Rodent Population Models May Inform Human Health Risk Assessment and Identification of Genetic Susceptibility to Environmental Exposures.

BACKGROUND: This paper provides an introduction for environmental health scientists to emerging population-based rodent resources. Mouse reference populations provide an opportunity to model environmental exposures and gene-environment interactions in human disease and to inform human health risk assessment. OBJECTIVES: This review will describe several mouse populations for toxicity assessment, including older models such as the Mouse Diversity Panel (MDP), and newer models that include the Collaborative Cross (CC) and Diversity Outbred (DO) models. METHODS: This review will outline the features of the MDP, CC, and DO mouse models and will discuss published case studies investigating the use of these mouse population resources in each step of the risk assessment paradigm. DISCUSSION: These unique resources have the potential to be powerful tools for generating hypotheses related to gene-environment interplay in human disease, performing controlled exposure studies to understand the differential responses in humans for susceptibility or resistance to environmental exposures, and identifying gene variants that influence sensitivity to toxicity and disease states. CONCLUSIONS: These new resources offer substantial advances to classical toxicity testing paradigms by including genetically sensitive individuals that may inform toxicity risks for sensitive subpopulations. Both in vivo and complementary in vitro resources provide platforms with which to reduce uncertainty by providing population-level data around biological variability. https://doi.org/10.1289/EHP1274.

Towards precision prevention: Technologies for identifying healthy individuals with high risk of disease.

The rise of advanced technologies for characterizing human populations at the molecular level, from sequence to function, is shifting disease prevention paradigms toward personalized strategies. Because minimization of adverse outcomes is a key driver for treatment decisions for diseased populations, developing personalized therapy strategies represent an important dimension of both precision medicine and personalized prevention. In this commentary, we highlight recently developed enabling technologies in the field of DNA damage, DNA repair, and mutagenesis. We propose that omics approaches and functional assays can be integrated into population studies that fuse basic, translational and clinical research with commercial expertise in order to accelerate personalized prevention and treatment of cancer and other diseases linked to aberrant responses to DNA damage. This collaborative approach is generally applicable to efforts to develop data-driven, individualized prevention and treatment strategies for other diseases. We also recommend strategies for maximizing the use of biological samples for epidemiological studies, and for applying emerging technologies to clinical applications.

Opportunities and Challenges for Environmental Exposure Assessment in Population-Based Studies.

A growing number and increasing diversity of factors are available for epidemiological studies. These measures provide new avenues for discovery and prevention, yet they also raise many challenges for adoption in epidemiological investigations. Here, we evaluate 1) designs to investigate diseases that consider heterogeneous and multidimensional indicators of exposure and behavior, 2) the implementation of numerous methods to capture indicators of exposure, and 3) the analytical methods required for discovery and validation. We find that case-control studies have provided insights into genetic susceptibility but are insufficient for characterizing complex effects of environmental factors on disease development. Prospective and two-phase designs are required but must balance extended data collection with follow-up of study participants. We discuss innovations in assessments including the microbiome; mass spectrometry and metabolomics; behavioral assessment; dietary, physical activity, and occupational exposure assessment; air pollution monitoring; and global positioning and individual sensors. We claim the the availability of extensive correlated data raises new challenges in disentangling specific exposures that influence cancer risk from among extensive and often correlated exposures. In conclusion, new high-dimensional exposure assessments offer many new opportunities for environmental assessment in cancer development. Cancer Epidemiol Biomarkers Prev; 26(9); 1370-80. ©2017 AACR.