Complex genetic conditions or so called polygenic conditions are influenced by multiple genetic factors, often in combination with environmental factors. Unlike single-gene disorders, where one mutation leads to a disease, complex conditions or traits involve numerous genes, each contributing a small effect.
This complexity makes prediction and treatment more challenging, as the specific genetic contributions can vary widely among individuals. Examples include heart disease, diabetes, and many mental health disorders. Understanding these conditions requires considering the intricate interplay of various genetic and environmental influences.
Aspect | Single Gene Conditions | Polygenic Conditions/Traits |
Genetic Cause | Caused by mutations in a single gene | Result from variants in multiple genes |
Inheritance Pattern | Often follow clear Mendelian patterns (dominant, recessive) | Do not follow simple Mendelian patterns |
Predictability | Easier to predict based on family history | Harder to predict due to complex gene-gene, gene-environment interactions, and influence of other factors |
Examples | Cystic Fibrosis, Sickle Cell Anemia, Hemophilia | Diabetes, Heart Disease, Habitual Snoring, Acne, Appetite, Carbohydrate Metabolism |
Several wellness and lifestyle traits in the LifeDNA reports are polygenic in nature and take into account genetic influences from various gene variants to arrive at the summarized genetic risk. It is important to note that genetic risk or predisposition to a condition or a trait is not the same as the overall risk which is influenced by lifestyle and other factors.
The study of the genetics of complex conditions and traits has several challenges:
Genetic Heterogeneity: Several genetic variations can influence a condition, each contributing a small effect. This diversity makes it hard to pinpoint specific genetic factors.
Environmental Interactions: Environmental factors often interact with genetic factors, complicating how we can determine the genetic basis of a condition.
Polygenic Nature: Complex conditions often result from the combined effect of many genes (polygenic effect), as opposed to single-gene disorders, making their study more complicated.
Population Diversity: Genetic studies often lack diversity in their samples, limiting the applicability of findings across different populations.
Technological and Methodological Limitations: Current technologies and methodologies may not always be sufficient to understand the complex genetic architectures of these conditions.
A polygenic risk score (PRS) is a numerical value that quantifies an individual’s genetic predisposition to a specific trait or disease. It is calculated based on the sum of an individual’s genetic variants, each weighted by the effect size (risk) associated with the variant. These genetic variants are usually single nucleotide polymorphisms (SNPs) identified through genome-wide association studies (GWAS) linked to specific traits or diseases.Â
A PRS can provide insights into the likelihood of developing conditions such as heart disease, diabetes, or what is your ability to metabolize caffeine, alcohol, or carbohydrates. PRS is also widely used in personalized medicine to tailor healthcare strategies.
Calculating a polygenic risk score involves several steps. First, GWAS data is used to identify SNPs associated with the trait or disease of interest. Each identified SNP is assigned a weight based on its effect size for the trait. Using the individual’s genotype data for each SNP, we multiply the number of risk alleles (0, 1, or 2) the individual has by the weight of that SNP. Summing these pieces of data for all trait-associated SNPs gives the polygenic risk score. This process requires a large, well-characterized dataset for both the discovery of SNP associations and the application of the score.
Performing polygenic risk score analyses involves a few key steps:Â
Important considerations include the choice of population for GWAS data, as genetic associations can vary across different ethnic groups, and the inclusion of a sufficient number of variants to capture the polygenic nature of the trait. Researchers must also decide on the method for summing risk across variants, which can impact the score’s predictive power.
Interpreting a polygenic risk score requires understanding its context and limitations. A higher PRS indicates a greater genetic predisposition to the trait or disease but does not guarantee its development. The score should be considered alongside environmental factors, lifestyle, and family history.Â
Moreover, the predictive power of PRS varies greatly depending on the trait or disease, with some scores being highly predictive and others less so. It is also crucial to recognize that many PRS are currently more accurate in populations of European descent due to the predominance of these groups in genetic studies, which may limit their applicability to other ethnic groups.
PRS have become an increasingly important tool in genetic research and personalized medicine. Their ability to aggregate the effects of numerous genetic variants, each contributing a small amount to the overall risk of developing a trait or disease, provides valuable insights that single-gene studies can not.Â
PRS are invaluable in predicting an individual’s genetic predisposition to various conditions, particularly those with a complex genetic background like heart disease and diabetes. This predictive power enables the early identification of at-risk individuals, paving the way for preventive healthcare strategies.Â
Additionally, PRS plays a crucial role in other aspects of personalized medicine. By understanding an individual’s genetic risk, healthcare providers can tailor prevention and treatment strategies more effectively, improving health outcomes. Beyond individual risk assessment, PRS also aids in deciphering the complex genetic interplay underlying disease development, enhancing our understanding of disease mechanisms. This insight is crucial for developing new therapeutic approaches and understanding how different genetic components contribute to diseases.Â
Furthermore, PRS facilitates targeted interventions and screenings, enabling healthcare systems to allocate resources more efficiently and potentially reduce healthcare costs. PRS can identify higher-risk population segments in public health research, guiding public health policies and interventions.Â
Despite these advantages, it is essential to approach PRSs with an understanding of their limitations, such as their current higher accuracy in populations of European descent due to larger genetic study samples from these groups. As genetic research becomes more inclusive, the applicability and accuracy of PRS might improve across diverse populations.
A 2021 cohort study explored the potential advantage of adding information on polygenic risk scores to conventional risk factors in primary prevention of cardiovascular diseases. Using data from the UK Biobank, the study found that adding PRS to conventional risk factors modestly enhanced the prediction of first-onset cardiovascular diseases and could translate into population health benefits if used at scale​​.
In the field of breast cancer, a research study published in May this year (2023) aimed to develop a polygenic risk score for the risk of recurrence score weighted on proliferation (ROR-P), an established prognostic indicator. The study used SNPs for breast cancer susceptibility and found that higher ROR-P PRS was associated with worse survival. It indicates that the ROR-P PRS could potentially enhance risk stratification for breast cancer screening and prevention​​.
A 2018 study analyzed polygenic risk scores in a large pedigree where a significant portion of family members suffered from major depressive disorder or bipolar disorder. The study highlighted that affected individuals who married into the family contributed to increased polygenic risk, suggesting a pattern of increasing genetic risk over generations. This research provides insights into the familial genetics of psychiatric disorders, demonstrating the importance of both common and rare genetic variations​​.
A recent study highlighted the use of PRS in understanding and managing bipolar disorder (BD), a highly heritable and heterogeneous psychiatric disorder. PRS, derived from GWAS, is increasingly used in genetic studies of complex diseases like BD.
PRS offers insights into genetic susceptibility, phenotypic associations, and correlations with other psychiatric conditions. This approach contributes to early prevention and individualized treatment strategies for BD, demonstrating the growing application of PRS in complex mental health conditions.
A 2022 study conducted among 35,759 adults from three cohorts examined the joint associations of genetic risk and diet quality with type 2 diabetes. The study used both global and pathway-specific polygenic scores to characterize genetic risk. It assessed the diet quality using the Alternate Healthy Eating Index (AHEI). They found that both low diet quality and increased genetic risk were independently associated with a higher risk of type 2 diabetes.
The study concluded that a healthy diet is associated with lower diabetes risk across all levels of genetic risk, highlighting the importance of genetic risk assessment in disease prevention​​.
Improved Accuracy and Predictive Power: As genetic research advances and more data become available, especially from diverse populations, we can expect the accuracy and predictive power of PRSs to improve. It will enhance their utility in predicting the risk of various diseases.
Personalized Medicine: PRSs will likely play a crucial role in advancing personalized medicine. They can tailor prevention and treatment strategies based on an individual’s genetic risk profile, leading to more effective and efficient healthcare.
Expansion in Healthcare Systems: There will likely be an increased integration of PRS in routine healthcare practices. It includes using PRS for early detection of diseases, risk stratification in clinical settings, and guiding lifestyle and medical interventions.
Ethical and Regulatory Developments: As the use of PRS expands, there will be a growing need for ethical guidelines and regulatory frameworks to manage issues related to privacy, data security, and the potential for genetic discrimination.
Broader Disease Coverage: Currently, PRSs are more effective for certain diseases. Future developments may expand their applicability to various conditions, including complex diseases with environmental components.
Public Health Applications: PRS could be used in public health initiatives to identify at-risk populations and develop targeted prevention strategies, potentially reducing the incidence and burden of certain diseases.
Technological Advancements: Advancements in bioinformatics and computational methods will enhance the analysis and interpretation of genetic data, further boosting the efficacy of PRS.
Increased Awareness and Education: As PRS becomes more common, there will likely be an increase in public awareness and education about genetic risk and its implications, which is crucial for informed decision-making.
* LifeDNA is not associated with the above company.Â
*Understanding your genetics can offer valuable insights into your well-being, but it is not deterministic. Your traits can be influenced by the complex interplay involving nature, lifestyle, family history, and others.
Our reports and suggestions do not diagnose or treat any health conditions or provide any medical advice. Consult with a healthcare professional before making any major lifestyle changes or if you have any other concerns about your results.
