Large uncertainty in individual polygenic risk score estimation impacts PRS-based risk stratification

2021 ◽  
Author(s):  
Yi Ding ◽  
Kangcheng Hou ◽  
Kathryn S. Burch ◽  
Sandra Lapinska ◽  
Florian Privé ◽  
...  
2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Itziar de Rojas ◽  
Sonia Moreno-Grau ◽  
Niccolo Tesi ◽  
Benjamin Grenier-Boley ◽  
Victor Andrade ◽  
...  

AbstractGenetic discoveries of Alzheimer’s disease are the drivers of our understanding, and together with polygenetic risk stratification can contribute towards planning of feasible and efficient preventive and curative clinical trials. We first perform a large genetic association study by merging all available case-control datasets and by-proxy study results (discovery n = 409,435 and validation size n = 58,190). Here, we add six variants associated with Alzheimer’s disease risk (near APP, CHRNE, PRKD3/NDUFAF7, PLCG2 and two exonic variants in the SHARPIN gene). Assessment of the polygenic risk score and stratifying by APOE reveal a 4 to 5.5 years difference in median age at onset of Alzheimer’s disease patients in APOE ɛ4 carriers. Because of this study, the underlying mechanisms of APP can be studied to refine the amyloid cascade and the polygenic risk score provides a tool to select individuals at high risk of Alzheimer’s disease.


2020 ◽  
Vol 73 ◽  
pp. S13-S14
Author(s):  
Cristiana Bianco ◽  
Serena Pelusi ◽  
Guido Alessandro Baselli ◽  
Irene Zanoni ◽  
Alice Taliento ◽  
...  

2018 ◽  
Vol 4 (Supplement 2) ◽  
pp. 44s-44s
Author(s):  
M. Wolfson

Background: Breast cancer (BC) screening, primarily age-based, is a major public health program in many wealthy countries. At the same time, there is a dramatic increase in using genetics to support personalized medicine. These two approaches would seem antithetical. However, they can join powerfully with the possibility of using genetic information as the basis for a major shift from age-based to a risk-based BC screening programs. Aim: To assess the prospective cost-effectiveness of such a shift to risk-based BC screening requires representative population data on the relationships among a woman's age when a risk assessment is done, her family history of cancer in the context of pedigree data, and specific features of her genotype - comprising both the presence of rare genetic mutations like BRCA1/2 and recently derived polygenic risk scores. We use our newly developed Genetic Mixing Model (GMM) to estimate this joint distribution as the initial step in assessing the prospective cost-effectiveness of risk stratified BC screening in Canada. Methods: BOADICEA is a BC risk stratification algorithm already in wide use around the world, and in particular in Ontario, for high risk screening. A new version of BOADICEA incorporating a polygenic risk score has recently (will have) been published. We embedded the new core BOADICEA algorithm into the GMM. GMM thus provides the empirical foundation for assessing risk stratification for a representative population by constructing an estimate of the multivariate joint distribution of family history, presence of rare genetic mutations including BRCA1/2, and a polygenic risk score, derived from genome-wide association studies. Results: Using a polygenic risk score (PRS) would be far more useful for stratifying women according to their risk of breast cancer than the two most commonly used indicators at present: family history and rare genetic mutations. We have assessed a variety of combinations of these genetic indicators, in combination with offering universal risk assessment to women in Canada at various ages, and using different thresholds for categorizing women as being at high risk. The optimal age for risk assessment is in the 35 to 40 range. And the PRS is substantially more useful than family history or rare mutations for stratifying women for screening intensity by their risk of BC. Conclusion: Shifting from the current public health approach of primarily age-based screening for breast cancer, to one based on risk stratification, especially making use of recent advances in assessing polygenic risk, offers major potential benefits.


Neurology ◽  
2021 ◽  
pp. 10.1212/WNL.0000000000012263
Author(s):  
Xiangfeng Lu ◽  
Xiaoge Niu ◽  
Chong Shen ◽  
Fangchao Liu ◽  
Zhongying Liu ◽  
...  

Objective:To construct a polygenic risk score (PRS) for stroke and evaluate its utility in risk stratification and primary prevention for stroke.Methods:Using meta-analytic approach and large genome-wide association results for stroke and stroke-related traits in East Asians, we generated a combined PRS (metaPRS) by incorporating 534 genetic variants in a training set of 2,872 patients with stroke and 2,494 controls. We then validated its association with incident stroke using Cox regression models in large Chinese population-based prospective cohorts comprising 41,006 individuals.Results:During a total of 367,750 person-years (mean follow-up 9.0 years), 1,227 participants developed stroke before age of 80 years. Individuals with high polygenic risk had an about 2-fold higher risk of incident stroke compared with those with low polygenic risk (HR: 1.99, 95% CI: 1.66-2.38), with the lifetime risk of stroke being 25.2% (95% CI: 22.5%-27.7%) and 13.6% (95% CI: 11.6%-15.5%), respectively. Individuals with both high polygenic risk and family history displayed the lifetime risk as high as 41.1% (95% CI: 31.4%-49.5%). Moreover, individuals with high polygenic risk achieved greater benefits in terms of absolute risk reductions from adherence to ideal fasting blood glucose and total cholesterol than those with low polygenic risk. Maintaining favorable cardiovascular health (CVH) profile could substantially mitigate the increased risk conferred by high polygenic risk to the level of the low polygenic risk (from 34.6 % to 13.2%).Conclusions:Our metaPRS has great potential for risk stratification of stroke and identification of individuals who may benefit more from maintaining ideal CVH.Classification of Evidence:This study provides Class I evidence that a meta-polygenic risk score is predictive of stroke risk.


Author(s):  
Antonio De Vincentis ◽  
Federica Tavaglione ◽  
Oveis Jamialahmadi ◽  
Antonio Picardi ◽  
Raffaele Antonelli-Incalzi ◽  
...  

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