Genome-wide association studies (GWASs) have revolutionized the identification of genomic regions associated with complex diseases.
GWAS-defined variants typically explain only a small proportion of trait heritability, raising questions about the ultimate applicability of these findings to risk prediction and clinical decision-making.
Criticisms of the GWAS approach include poor assessment of rare and structural variants, small effect sizes and proportion of heritability explained, high proportion of signals in difficult-to-interpret non-coding regions, difficulty in dissecting linkage disequilibrium patterns and poor discriminative ability in predicting disease risk.
Clinically relevant findings are beginning to be applied in four key areas: risk prediction, disease subclassification, drug development and drug toxicity.
Translational potential of GWAS findings may be less driven by the relevant genetic architecture and variants identified by the clinical scenario, such as importance of early detection, availability of alternative treatments, and accessibility of genotyping.
A key component in translating GWAS findings is linking initial genomic discoveries with clinicians who appreciate the clinical dilemmas that the findings could address, such as the importance of early prediction in type 1 diabetes, molecular subtyping of type 2 diabetes or seemingly unpredictable drug side effects.
For potential GWAS-based improvements in care to be actually implemented clinically requires additional capabilities, including: rapid, low-cost genotyping; point-of-care educational information and decision support tools; agreed-on evidence standards and practice guidelines; and institutional willingness to support the infrastructure needed for implementation.
Genome-wide association studies (GWASs) have been heralded as a major advance in biomedical discovery, having identified ~2,000 robust associations with complex diseases since 2005. Despite this success, they have met considerable scepticism regarding their clinical applicability; this scepticism arises from such aspects as the modest effect sizes of associated variants and their unclear functional consequences. There are, however, promising examples of GWAS findings that will or that may soon be translated into clinical care. These examples include variants identified through GWASs that provide strongly predictive or prognostic information or that have important pharmacological implications; these examples may illustrate promising approaches to wider clinical application.
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The author declares no competing financial interests.
The proportion of the total phenotypic variation in a trait that can be attributed to genetic effects.
- Odds ratios
A measure of effect size. Defined as the ratio of the odds (that is, the probability of disease divided by 1 minus the probability) of a disease being observed in one group of genotypes and the odds of a disease being observed in another group.
- Minor allele frequencies
(MAFs). The frequency of the less common allele of a polymorphism. It has a value between 0 and 0.5 and can vary between populations.
- Negative selection
A form of natural selection that suppresses alternative genetic variants in favour of the ancestral type.
- Enhancer elements
A regulatory DNA element that usually binds several transcription factors and can activate transcription from a promoter at great distance and in an orientation-independent manner.
- Linkage disequilibrium
(LD). The nonrandom association of alleles at two or more loci. The pattern of LD in a given genomic region reflects the history of natural selection, mutation, recombination, genetic drift and other demographic and evolutionary forces.
- Expression quantitative trait locus
(eQTL). A locus at which genetic allelic variation is associated with variation in gene expression levels.
The proportion of true positives that are accurately identified as such (for example, the percentage of cases that are diagnosed using a questionnaire). A sensitivity of 100% means that all cases are correctly identified.
The proportion of true negatives that are classified as negatives. For example, a diagnostic test with a specificity of 100% means that all healthy people have been identified as healthy.
- Positive predictive value
(PPV). The probability that an individual who tests positive truly has the condition (true positive). A measure of how well a screening or diagnostic test distinguishes true positives from false positives that do not have the disease.
- Major histocompatibility complex
(MHC). A large complex of tightly linked genes on human chromosome 6, many of which are involved in the immune response. The human leukocyte antigen genes are located within the MHC.
- Missense variant
A variant that results in the substitution of an amino acid in a protein.
- Splice variant
A variant, usually found at the intron–exon boundary, that alters the splicing of an exon to its surrounding exons.
The rapid breakdown of skeletal muscle tissue due to injury, drugs, toxins or metabolic disease. This leads to electrolyte release and high concentrations of myoglobin in plasma and urine that are toxic to the kidneys and can cause renal failure and death.
A folic acid antagonist used as a chemotherapeutic and immunosuppressant drug.
- Decision support tools
Software tools providing intelligently filtered and appropriately timed medical information specific to a given patient to aid in clinical decision making at the point of care. Examples include computerized alerts of potential adverse effects of a proposed treatment or reminders of overdue screening tests.
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Manolio, T. Bringing genome-wide association findings into clinical use. Nat Rev Genet 14, 549–558 (2013). https://doi.org/10.1038/nrg3523
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