Gene-Environment Interactions Overview

Gene-Environment Interactions (GEIs)

• GEIs occur when environmental factors (diet, air, etc.) interact with genes, impacting disease risk
• GEIs are crucial in disease etiology, significantly influencing disease development
• Development-stage exposures strongly impact gene regulation and disease risk (prenatal, early childhood)
• A major benefit of GEI analysis is that it includes environmental factors, which impact health and influence complex traits
• Important for creating more accurate disease risk predictions and developing better treatments
• GEI research helps investigate disease mechanisms and individual heterogeneity
• Addresses "missing heritability" in disease studies

Lecture Outline

• Introduction to GEIs
• Advantages and Challenges in GEI Analysis
• Integration of Multi-omics Data
• Clinical Applications of GEI Research
• Social Impacts of GEI Research
• GEI within the Precision Environmental Health (PEH) Framework

Precision Environmental Health (PEH)

• PEH integrates genetic and environmental data to predict disease and tailor healthcare
• Incorporates omics data (genomics, epigenomics) with environmental exposures to optimize individualized health strategies
• Uses detailed omics data across a lifespan to better understand risk identification and prevention for improved health interventions

What are Gene-Environment Interactions (GEIs)?

• GEIs describe an interaction between your genes and environment (diet, air quality, etc.) influencing disease risk
• Exposure to pollution can increase asthma risk although genetics determine the extent of the effect.

Gene-Environment Interactions (GEI) Overview

• Definition: GEI occurs when exposure to environmental factors affects disease risk, which is based on genetic makeup
• Examples: BRCA-1 mutation and asbestos exposure (mesothelioma), DRD4 gene and parenting style (ADHD)

Precision Environmental Health (PEH) - Data Use

• Omics and exposures retrospectively used to characterize risk factors for disease
• Omic data includes genomics, epigenomics, metabolomics, and transcriptomics
• Exposure data includes medications, exercise, stress, diet, domicile, occupation, social determinants of health, and environmental factors (air/water)
• Feature selection uses statistical learning, elastic net, ridge regression, neural nets, and clinical significance to analyze the data

Gene-Environment Interactions (GEIs) - Key Study Focus

• Primarily studies the interaction between genetic factors and environmental exposures impacting health
• Excludes approaches that solely focus on how genetics or environmental factors independently influence health
• Excludes approaches that focus on lifestyle factors or solely or genetic influences

Developmental Stages & GEIs

• GEIs show varied impacts across different life stages (prenatal to early childhood)
• Developmental stages significantly affect gene regulation and disease risk

How the Environment Affects Genes

• Precision Environmental Health (PEH) uses genetic and environmental data to better predict disease and customize healthcare
• PEH focuses on integrating omics data (genomics, epigenomics) with environmental exposures to enhance personalized health strategies
• Examples include how pollution, stress, and diet interact with genes to impact health

GEI Analysis Advantages

• Incorporates both genetic and environmental complex traits
• Enhances understanding of disease mechanisms and individual heterogeneity
• Addresses "missing heritability" in disease studies
• Replicated GEI associations include air pollution and CVD, alcohol and liver disease, smoking and lung cancer, pesticide exposure and Parkinson's disease, diet, and obesity

GEI Analysis Advantages - Improved Prediction

• GEI analyses explain more phenotypic variance compared to genome-only models
• The exposome framework captures additive and non-additive effects
• Increased statistical power is achieved by accounting for environmental exposures, enhancing health phenotype studies
• Improved polygenic scores (PGS) predictive power across diverse populations, especially those that vary through genetic ancestry and socioeconomic status

Why GEIs Are Important

• GEI research helps understand disease mechanisms
• Helps improve disease prediction
• Enables better strategies for prevention and public health intervention
• Relevant for examining drug efficacy and safety.

GEI Analysis and Understanding Disease

• Research helps understand underlying disease mechanisms by analyzing combined effects of genes and environment
• This is different from simply studying single-gene causes or environmental factors alone

Behavioral and Systemic Consequences

• Environmental exposures impact health conditions beyond the cellular level
• Influences include behavioral and systemic consequences
• Toxic exposures may affect cellular function
• Lifestyle factors might modify phenotypes by altering brain networks and hormone levels

Exposure Measurement

• Exposome Definition: encompasses all environmental exposures throughout the lifespan (external = pollution, social etc.; internal = microbiome, oxidative stress)

Measurement Techniques

• Mass Spectrometry (MS) High-throughput, untargeted MS can detect and identify pollutants, food additives, and internal metabolites that yield complex data needing specialized analysis
• Sensors and machine learning: Advanced technologies to enhance understanding of GEIs
• Wearable devices: Tools that track exposure and body responses to pollution
• Questionnaires Collect data on lifestyle, exposures, and social factors; can suffer biases from standardization, recall, or cultural differences (these are improved with biomonitoring and sensor data)

Challenges with Standardizing the Exposome

• Difficulty in precisely measuring environmental factors' role in disease risk (contribute significantly to 70%–90% of diseases).
• The exposome lacks standardized measurement methods and lacks comprehensive systems for data sharing.
• This leads to an underestimation of the environmental factors' real impact on diseases.
• Overlapping risk estimates from genetic and environmental studies highlighting interactions between genes and environment, often referred to as Gene-Environment Interactions (GEIs)
• Difficulty in accurately determining the combined effects of genes and environment on disease

Disease and Environmental Considerations (Examples)

• Environmental factors play a substantial role in a variety of diseases: cardiovascular disease, type 2 diabetes, asthma and respiratory illnesses, cancer, neurodegenerative, and other diseases

GEI Analysis Advantages - Practical Utility

• Understanding GEIs helps predict disease risks more accurately and to create better treatments.
• Future research will need more accurate measures for environmental exposures to better study diverse populations.

Epidemiology and GEI Studies

• Epidemiology contributes to GEIs primarily by collecting standardized data on disease outcomes and environmental exposures
• This process avoids biases that may cause misinterpretations of the relationship between genes and the environment

Epigenetics Overview

• Study of non-sequence modifications to DNA and chromatin altering gene accessibility and regulation
• Epigenetics connect genetic makeup to environmental exposures (GEIs)
• Environmental elements impact epigenetic markers influencing cell communication and growth

Important Epigenetic Modifications

• DNA CpG Methylation is one of easiest elements to assess—it's a fundamental epigenetic marker.
• Other modifications (e.g. heterochromatic histone modifications) have technological challenges

Epigenetic Research and Relevance to Disease

• Epigenome-Wide Association Studies (EWASS) help understand GEI mechanisms
• Large-scale genomic analyses are needed for more efficient implementation across diverse populations.

Which Epigenetic Modification is used in GEI Research?

• DNA CpG Methylation is easiest to assess and often used in GEI research

GEI Translation in Personalized and Preventive Healthcare

• Research identifies interactions between genetic variations and environmental exposures, enabling tailored interventions in various health areas.
• Examples include specific adjustments for drug dosage, tailored nutrition plans, and disease screenings (targeted prevention strategies)

Genetic Susceptibility/Exposure - Health Impacts (1)

• Personalized air quality alerts: Managing respiratory issues via pollution reduction
• Lead exposure: Preventing cognitive and developmental issues in susceptible children

Genetic Susceptibility/Exposure - Health Impacts (2)

• UV exposure and skin cancer risk: Personalized sun protection measures
• Personalized nutrition plans: Managing chronic conditions and diet-related diseases (type 2 diabetes, cardiovascular disease) through dietary modifications or protective measures
• Pesticide exposure and Parkinson's disease: Early detection strategies for individuals at high risk.

Social and Societal Considerations

• Environmental Justice: Personalized Environmental Health (PEH) integrates environmental data with individual/community data creating tailored strategies to address health disparities
• Helps to identify genetic vulnerabilities to pollutants enabling targeted interventions (especially for climate change impacts)
• Addresses gaps and focuses on unequal exposures to pollutants, particularly impacting low-income or marginalized communities

Return of Results in GEI Research

• Ethical Considerations: Returning study findings to participants requires careful attention to ethical, legal, and social considerations (especially with uncertain implications and risk factors).
• Participants want to know about exposures and genetic risks – even with unclear implications.
• Community-Guided Report-Back: Tailoring communication to participant concerns (especially for high exposures) creates more actionable health steps/reducing exposures
• Supportive resources: Clear communication, resources, education, and training/tools are crucial for effective outcomes.

Data Privacy Considerations in GEI Research

• Data privacy is a key concern in environmental exposure (especially geospatial data) research
• Robust policies and protections for environmental exposure data are needed (comparing these to well-established genetic data policies)
• Security (geospatial data in PEH), encryption, access controls, and informed consent are essential

GEI Research - Conclusion

• Understanding GEIs allows for more accurate disease risk prediction and better treatment strategies
• Future research should focus on more precise methods of measuring environmental exposures and better evaluate and analyze data in diversely represented populations.