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Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations.

ABSTRACT: A key public health need is to identify individuals at high risk for a given disease to enable enhanced screening or preventive therapies. Because most common diseases have a genetic component, one important approach is to stratify individuals based on inherited DNA variation1. Proposed clinical applications have largely focused on finding carriers of rare monogenic mutations at several-fold increased risk. Although most disease risk is polygenic in nature2-5, it has not yet been possible to use polygenic predictors to identify individuals at risk comparable to monogenic mutations. Here, we develop and validate genome-wide polygenic scores for five common diseases. The approach identifies 8.0, 6.1, 3.5, 3.2, and 1.5% of the population at greater than threefold increased risk for coronary artery disease, atrial fibrillation, type 2 diabetes, inflammatory bowel disease, and breast cancer, respectively. For coronary artery disease, this prevalence is 20-fold higher than the carrier frequency of rare monogenic mutations conferring comparable risk6. We propose that it is time to contemplate the inclusion of polygenic risk prediction in clinical care, and discuss relevant issues.

SUBMITTER: Khera AV

PROVIDER: S-EPMC6128408 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations.

Khera Amit V AV Chaffin Mark M Aragam Krishna G KG Haas Mary E ME Roselli Carolina C Choi Seung Hoan SH Natarajan Pradeep P Lander Eric S ES Lubitz Steven A SA Ellinor Patrick T PT Kathiresan Sekar S

Nature genetics 20180813 9

A key public health need is to identify individuals at high risk for a given disease to enable enhanced screening or preventive therapies. Because most common diseases have a genetic component, one important approach is to stratify individuals based on inherited DNA variation<sup>1</sup>. Proposed clinical applications have largely focused on finding carriers of rare monogenic mutations at several-fold increased risk. Although most disease risk is polygenic in nature<sup>2-5</sup>, it has not ye ...[more]

PMID: 30104762

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Project description:The genetic protective factors for cognitive decline in aging remain unknown. Predicting an individual's rate of cognitive decline-or with better cognitive resilience-using genetics will allow personalized intervention for cognitive enhancement and the optimal selection of target samples in clinical trials. Here, using genome-wide polygenic scores (GPS) of cognitive capacity as the genomic indicators for variations of human intelligence, we analyzed the 18-year records of cognitive and behavioral data of 8511 European-ancestry adults from the Wisconsin Longitudinal Study (WLS), specifically focusing on the cognitive assessments that were repeatedly administered to the participants with their average ages of 64.5 and 71.5. We identified a significant interaction effect between age and cognitive capacity GPS, which indicated that a higher cognitive capacity GPS significantly correlated with a slower cognitive decline in the domain of immediate memory recall (β = 1.86 × 10-1, p-value = 1.79 × 10-3). The additional phenome-wide analyses identified several associations between cognitive capacity GPSs and cognitive/behavioral phenotypes, such as similarities task (β = 1.36, 95% CI = (1.22, 1.51), p-value = 3.59 × 10-74), number series task (β = 0.94, 95% CI = (0.85, 1.04), p-value = 2.55 × 10-78), IQ scores (β = 1.42, 95% CI = (1.32, 1.51), p-value = 7.74 × 10-179), high school classrank (β = 1.86, 95% CI = (1.69, 2.02), p-value = 3.07 × 10-101), Openness from the BIG 5 personality factor (p-value = 2.19 × 10-14, β = 0.57, 95% CI = (0.42, 0.71)), and leisure activity of reading books (β = 0.50, 95% CI = (0.40, 0.60), p-value = 2.03 × 10-21), attending cultural events, such as concerts, plays, or museums (β = 0.60, 95% CI = (0.49, 0.72), p-value = 2.06 × 10-23), and watching TV (β = -0.48, 95% CI = (-0.59, -0.37), p-value = 4.16 × 10-18). As the first phenome-wide analysis of cognitive and behavioral phenotypes, this study presents the novel genetic protective effects of cognitive ability on the decline of memory recall in an aging population.

Project description:A surprising and well-replicated result in genetic studies of human longevity is that centenarians appear to carry disease-associated variants in numbers similar to the general population. With the proliferation of large genome-wide association studies (GWAS) in recent years, investigators have turned to polygenic scores to leverage GWAS results into a measure of genetic risk that can better predict the risk of disease than individual significant variants alone. We selected 54 polygenic risk scores (PRSs) developed for a variety of outcomes, and we calculated their values in individuals from the New England Centenarian Study (NECS, N = 4886) and the Long Life Family Study (LLFS, N = 4577). We compared the distribution of these PRSs among exceptionally long-lived individuals (ELLI), their offspring, and controls, and we also examined their predictive values, using t-tests and regression models adjusting for sex and principal components reflecting the ancestral background of the individuals (PCs). In our analyses, we controlled for multiple testing using a Bonferroni-adjusted threshold for 54 traits. We found that only 4 of the 54 PRSs differed between ELLIs and controls in both cohorts. ELLIs had significantly lower mean PRSs for Alzheimer's disease (AD) and coronary artery disease (CAD) than controls, suggesting a genetic predisposition to extreme longevity may be mediated by reduced susceptibility to these traits. ELLIs also had significantly higher mean PRSs for improved cognitive function and parental extreme longevity. In addition, the PRS for AD was associated with a higher risk of dementia among controls but not ELLIs (p = 0.003, 0.3 in NECS, p = 0.03, 0.9 in LLFS, respectively). ELLIs have a similar burden of genetic disease risk as the general population for most traits but have a significantly lower genetic risk of AD and CAD. The lack of association between AD PRS and dementia among ELLIs suggests that the genetic risk for AD that they do have is somehow counteracted by protective genetic or environmental factors.

Project description:BACKGROUND:Inherited susceptibility to common, complex diseases may be caused by rare, pathogenic variants ("monogenic") or by the cumulative effect of numerous common variants ("polygenic"). Comprehensive genome interpretation should enable assessment for both monogenic and polygenic components of inherited risk. The traditional approach requires two distinct genetic testing technologies-high coverage sequencing of known genes to detect monogenic variants and a genome-wide genotyping array followed by imputation to calculate genome-wide polygenic scores (GPSs). We assessed the feasibility and accuracy of using low coverage whole genome sequencing (lcWGS) as an alternative to genotyping arrays to calculate GPSs. METHODS:First, we performed downsampling and imputation of WGS data from ten individuals to assess concordance with known genotypes. Second, we assessed the correlation between GPSs for 3 common diseases-coronary artery disease (CAD), breast cancer (BC), and atrial fibrillation (AF)-calculated using lcWGS and genotyping array in 184 samples. Third, we assessed concordance of lcWGS-based genotype calls and GPS calculation in 120 individuals with known genotypes, selected to reflect diverse ancestral backgrounds. Fourth, we assessed the relationship between GPSs calculated using lcWGS and disease phenotypes in a cohort of 11,502 individuals of European ancestry. RESULTS:We found imputation accuracy r2 values of greater than 0.90 for all ten samples-including those of African and Ashkenazi Jewish ancestry-with lcWGS data at 0.5×. GPSs calculated using lcWGS and genotyping array followed by imputation in 184 individuals were highly correlated for each of the 3 common diseases (r2?=?0.93-0.97) with similar score distributions. Using lcWGS data from 120 individuals of diverse ancestral backgrounds, we found similar results with respect to imputation accuracy and GPS correlations. Finally, we calculated GPSs for CAD, BC, and AF using lcWGS in 11,502 individuals of European ancestry, confirming odds ratios per standard deviation increment ranging 1.28 to 1.59, consistent with previous studies. CONCLUSIONS:lcWGS is an alternative technology to genotyping arrays for common genetic variant assessment and GPS calculation. lcWGS provides comparable imputation accuracy while also overcoming the ascertainment bias inherent to variant selection in genotyping array design.

Project description:ObjectivesTo evaluate and compare the lifetime costs associated with strategies to identify individuals with monogenic diabetes and change their treatment to more appropriate therapy.DesignA decision analytical model from the perspective of the National Health Service (NHS) in England and Wales was developed and analysed. The model was informed by the literature, routinely collected data and a clinical study conducted in parallel with the modelling.SettingSecondary care in the UK.ParticipantsSimulations based on characteristics of patients diagnosed with diabetes <30 years old.InterventionsFour test-treatment strategies to identify individuals with monogenic diabetes in a prevalent cohort of diabetics diagnosed under the age of 30 years were modelled: clinician-based genetic test referral, targeted genetic testing based on clinical prediction models, targeted genetic testing based on biomarkers, and blanket genetic testing. The results of the test-treatment strategies were compared with a strategy of no genetic testing.Primary and secondary outcome measuresDiscounted lifetime costs, proportion of cases of monogenic diabetes identified.ResultsBased on current evidence, strategies using clinical characteristics or biomarkers were estimated to save approximately £100-£200 per person with diabetes over a lifetime compared with no testing. Sensitivity analyses indicated that the prevalence of monogenic diabetes, the uptake of testing, and the frequency of home blood glucose monitoring had the largest impact on the results (ranging from savings of £400-£50 per person), but did not change the overall findings. The model is limited by many model inputs being based on very few individuals, and some long-term data informed by clinical opinion.ConclusionsCosts to the NHS could be saved with targeted genetic testing based on clinical characteristics or biomarkers. More research should focus on the economic case for the use of such strategies closer to the time of diabetes diagnosis.Trial registration numberNCT01238380.

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Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations.

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Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations.

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