Jerome I. Rotter, an expert in translational genomics, joins JAMA Statistical Editor Roger J. Lewis to dive into Genome-Wide Association Studies (GWAS). They explore the differences between Mendelian and complex diseases, discussing how single base mutations lead to conditions like sickle cell anemia. The conversation covers polygenic diseases, highlighting the genetic variants behind ailments such as type 2 diabetes. They also tackle advancements in GWAS and the significance of SNPs, emphasizing the importance of diverse ethnic inclusion for reliable findings.
Genome-wide association studies (GWAS) identify genetic variations linked to complex diseases by comparing SNPs between affected individuals and controls.
The findings from GWAS facilitate clinical applications like polygenic risk scores for predicting disease risk and guiding targeted prevention strategies.
Deep dives
Understanding Mendelian vs. Polygenic Diseases
Mendelian genetic diseases are caused by a single change in a DNA base pair, leading to specific phenotypes such as sickle cell anemia and cystic fibrosis. In contrast, common chronic diseases like type 2 diabetes and coronary artery disease arise from the interaction of numerous genetic variants, known as polygenic diseases. These disorders involve complex relationships between hundreds of genetic factors that collectively influence disease susceptibility. The polygenic nature of these diseases complicates the search for genetic causes, as it necessitates examining multiple genetic variations rather than focusing on a single gene.
The Role of Genome-Wide Association Studies (GWAS)
Genome-wide association studies (GWAS) are employed to identify genetic variations associated with complex diseases, leveraging the fact that genes are organized along chromosomes. GWAS utilize single nucleotide polymorphisms (SNPs), which are variations in individual base pairs within the genome, to find potential links between genetic factors and diseases. By comparing genetic variations in affected individuals against those in controls, researchers can pinpoint regions of the genome associated with specific diseases. The approach allows for exploration even when the exact genetic causes are unknown, enabling researchers to identify potential genetic influencers through their physical organization.
Applications and Advances in GWAS Findings
The findings from GWAS are being implemented in clinical settings to both predict disease risk and unravel disease mechanisms. For instance, polygenic risk scores are now utilized to determine the likelihood of developing conditions such as breast cancer and coronary artery disease, allowing for targeted prevention strategies. Moreover, GWAS have led to insights into new biological pathways by identifying genetic factors influencing conditions like Crohn's disease and primary open-angle glaucoma, enhancing the understanding of these diseases. By conducting studies across diverse ethnic groups, researchers can improve the validity of their findings and ensure that genetic risk assessments are relevant and beneficial for a broader population.
Jerome I. Rotter, MD, The Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute, Department of Pediatrics, Harbor-UCLA Medical Center, discusses Genome-Wide Association Studies with JAMA Statistical Editor Roger J. Lewis, MD, PhD. Related Content: