Gene-Environment Interactions and Health

Study Notes

GEIs occur when environmental factors (diet, exposure) interact with genes, affecting disease risk.
GEIs are important in understanding disease mechanisms and predicting disease risk.
GEI studies analyze the interplay of genetics and environment to understand disease development.
Lifestyle factors, like diet, alone don't determine health outcomes; genetics also play a role.
GEI studies consider how exposures across a lifespan influence disease risk.

Incorporates both genetic and environmental factors, which influences complex traits.
Expands understanding of disease mechanisms and individual variations.
Addresses "missing heritability."
Replicated GEIs, like air pollution and cardiovascular disease, smoking and lung cancer, alcohol and liver disease, are included; diet and obesity and pesticide exposure and Parkinson's disease are also included.
Improved prediction of disease risk by analyzing more phenotypic variance using exposome framework to capture additive and non-additive effects.
Increased statistical power in health phenotype studies due to environmental exposures.
GEI analysis enhances PGS predictive power, particularly in diverse populations.
Accounts for how environmental exposures influence people.

Environmental exposures have impacts beyond cellular levels; they also affect behaviors and systemic processes.
Exposome includes all environmental exposures (pollution, social factors, microbiome, oxidative stress). This broadens the scope of risk factors compared to traditional healthcare models.
Exposure measurement techniques like mass spectrometry can detect pollutants, food additives, and internal metabolites.
Additional techniques include sensors and machine learning, and wearable devices to track exposure and response.
Questionnaires collect data on lifestyle, exposures, and social factors but have drawbacks like standardization issues and recall bias. Ideally, combine questionnaires with biomonitoring and sensor data to improve accuracy.

Accurately measuring environmental impact on disease risk is challenging.
The exposome lacks standardized measurement methods and comprehensive data-sharing systems.
Environmental factors impact disease risk more than previously understood. This is further complicated by overlapping risk estimates from multiple studies.
The complexity inherent to how genes and environment interact, makes accurate estimation of GEI contributions challenging.

Studies investigate the interplay of genetic variations and environmental factors.
Specific examples of interactions include CYP2D6 and pesticides (likely in relation to Parkinson's disease,) NAT2 and smoking (bladder cancer,) ALDH2 and alcohol (esophageal cancer,) and AS3MT and arsenic (skin lesions.)
GEI research can guide personalized medical interventions, such as better dosing for medications like warfarin, using blood testing to identify specific risks associated with medications (e.g., abacavir), and targeted therapy based on genetic information for certain cancers.

Understanding how genes and environmental influences act together to create health outcomes.
Using genetic susceptibility to environmental factors to help in preventive measures.
GEI studies help to better understand disease risks.
Environmental exposures can vary across diverse populations; thus, the analysis should reflect these differences.

Epigenetics involves non-sequence DNA modifications that affect gene accessibility.
Epigenetic modifications are impacted by the environment.
Key epigenetic modification is DNA CpG methylation, which is easiest to measure.
Epigenome-wide association studies are valuable in understanding GEI mechanisms.

Epidemiology in GEI studies is crucial because of its standardized data collection methods, allowing better understanding of disease outcomes and exposures.
Standardization is crucial in GEI research, but it can be challenging due to issues with standardization, recall bias, and cultural differences, but advancements are being made through combined approaches of questionnaires and biomonitoring.

Understanding GEIs helps healthcare professionals predict disease risks more accurately and create more precise interventions.
Future GEI research is likely to focus on more accurate measures of environmental exposures.