Related Experiment Video
Updated: Jul 31, 2026
14:56
Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies
Published on: May 6, 2022
Covariates and confounding in epidemiologic studies using metabolic gene polymorphisms.
Emanuela Taioli1, Seymour Garte
1Molecular and Genetic Epidemiology Unit, Ospedale Policlinico IRCCS, University of Milano, Milano, Italy. sget@iol.it
International Journal of Cancer
|July 13, 2002
Summary
Biomarkers in epidemiologic studies change how we understand exposure and disease relationships. Careful management of confounding factors is crucial when biologic markers are involved in the exposure-disease pathway.
Area of Science:
- Epidemiology
- Molecular Epidemiology
- Biostatistics
Background:
- Biologic measurements (biomarkers) are integral to molecular epidemiology.
- Biomarkers indicate exposure, disease status, or susceptibility.
- The introduction of biomarkers can alter the traditional management of confounding factors.
Purpose of the Study:
- To explore and summarize the relationship between exposure and disease when biomarkers are included in epidemiologic studies.
- To review the concept of confounders in the context of biomarkers.
- To present models of exposure-disease association incorporating biomarkers.
Main Methods:
- Conceptual review of confounding in molecular epidemiology.
- Presentation of statistical models for exposure-disease associations with biomarkers.
- Analysis of the role of biomarkers in the causal pathway between exposure and disease.
Main Results:
- Biomarkers can be intermediate variables, not always confounders.
- The relationship between exposure and biomarkers requires careful consideration.
- Traditional confounding definitions may need modification when biomarkers are present.
Conclusions:
- Biomarkers significantly impact the interpretation of exposure-disease relationships in epidemiology.
- Understanding the role of biomarkers as potential mediators is key.
- Revised approaches to confounding are necessary for accurate molecular epidemiologic research.
Related Concept Videos
01:27Principles of Pharmacogenetics: Types of Genetic Variants
The human genome is over 99.9% identical between individuals, yet genetic differences exist at millions of bases. The human genome contains approximately 3 million variant positions per individual, many of which are heterozygous, contributing to genetic diversity and individual traits. Genetic variations include single-nucleotide polymorphisms (SNPs), insertions, deletions, and copy number variations (CNVs).SNPs, the most common variation, involve single-base changes in DNA. These can be...
01:29Pharmacogenetic Phenotypes: Alterations in Pharmacokinetics, Drug Targets and Biologic Milieu
Genetic variations significantly influence drug response through pharmacokinetics, receptor interactions, and biologic milieu modifications. Pharmacokinetic alterations impact drug metabolism and clearance, affecting efficacy and toxicity. Variants in drug-metabolizing enzymes, such as CYP2C9 and CYP2C19, alter drug activation and elimination. For example, CYP2C9 loss-of-function variants require lower warfarin doses to prevent excessive bleeding, while CYP2C19 variants reduce clopidogrel...
01:27Pharmacogenetics of Drug Metabolism: Overview
Genetic polymorphism in drug metabolism is crucial to the inter-individual variability observed in drug responses. Drug metabolism primarily involves the chemical modification of drugs and other xenobiotics to enhance their elimination by increasing their polarity. Two main classes of enzymes mediate this biotransformation process: Phase I enzymes, primarily cytochrome P450s, catalyze oxidation and reduction reactions, while other enzymes, such as esterases, mediate hydrolysis, and Phase II...
01:29Pharmacogenomics: Identification of New Drug Targets
Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...
01:27Confounding in Epidemiological Studies
Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This phenomenon...
01:25Strategies for Assessing and Addressing Confounding
Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
Confounding can be addressed at both the design phase of a study and through analytical methods after data...