Dataset Information

Genome-wide Modeling of Polygenic Risk Score in Colorectal Cancer Risk.

ABSTRACT: Accurate colorectal cancer (CRC) risk prediction models are critical for identifying individuals at low and high risk of developing CRC, as they can then be offered targeted screening and interventions to address their risks of developing disease (if they are in a high-risk group) and avoid unnecessary screening and interventions (if they are in a low-risk group). As it is likely that thousands of genetic variants contribute to CRC risk, it is clinically important to investigate whether these genetic variants can be used jointly for CRC risk prediction. In this paper, we derived and compared different approaches to generating predictive polygenic risk scores (PRS) from genome-wide association studies (GWASs) including 55,105 CRC-affected case subjects and 65,079 control subjects of European ancestry. We built the PRS in three ways, using (1) 140 previously identified and validated CRC loci; (2) SNP selection based on linkage disequilibrium (LD) clumping followed by machine-learning approaches; and (3) LDpred, a Bayesian approach for genome-wide risk prediction. We tested the PRS in an independent cohort of 101,987 individuals with 1,699 CRC-affected case subjects. The discriminatory accuracy, calculated by the age- and sex-adjusted area under the receiver operating characteristics curve (AUC), was highest for the LDpred-derived PRS (AUC = 0.654) including nearly 1.2 M genetic variants (the proportion of causal genetic variants for CRC assumed to be 0.003), whereas the PRS of the 140 known variants identified from GWASs had the lowest AUC (AUC = 0.629). Based on the LDpred-derived PRS, we are able to identify 30% of individuals without a family history as having risk for CRC similar to those with a family history of CRC, whereas the PRS based on known GWAS variants identified only top 10% as having a similar relative risk. About 90% of these individuals have no family history and would have been considered average risk under current screening guidelines, but might benefit from earlier screening. The developed PRS offers a way for risk-stratified CRC screening and other targeted interventions.

SUBMITTER: Thomas M

PROVIDER: S-EPMC7477007 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Genome-wide Modeling of Polygenic Risk Score in Colorectal Cancer Risk.

Thomas Minta M Sakoda Lori C LC Hoffmeister Michael M Rosenthal Elisabeth A EA Lee Jeffrey K JK van Duijnhoven Franzel J B FJB Platz Elizabeth A EA Wu Anna H AH Dampier Christopher H CH de la Chapelle Albert A Wolk Alicja A Joshi Amit D AD Burnett-Hartman Andrea A Gsur Andrea A Lindblom Annika A Castells Antoni A Win Aung Ko AK Namjou Bahram B Van Guelpen Bethany B Tangen Catherine M CM He Qianchuan Q Li Christopher I CI Schafmayer Clemens C Joshu Corinne E CE Ulrich Cornelia M CM Bishop D Timothy DT Buchanan Daniel D DD Schaid Daniel D Drew David A DA Muller David C DC Duggan David D Crosslin David R DR Albanes Demetrius D Giovannucci Edward L EL Larson Eric E Qu Flora F Mentch Frank F Giles Graham G GG Hakonarson Hakon H Hampel Heather H Stanaway Ian B IB Figueiredo Jane C JC Huyghe Jeroen R JR Minnier Jessica J Chang-Claude Jenny J Hampe Jochen J Harley John B JB Visvanathan Kala K Curtis Keith R KR Offit Kenneth K Li Li L Le Marchand Loic L Vodickova Ludmila L Gunter Marc J MJ Jenkins Mark A MA Slattery Martha L ML Lemire Mathieu M Woods Michael O MO Song Mingyang M Murphy Neil N Lindor Noralane M NM Dikilitas Ozan O Pharoah Paul D P PDP Campbell Peter T PT Newcomb Polly A PA Milne Roger L RL MacInnis Robert J RJ Castellví-Bel Sergi S Ogino Shuji S Berndt Sonja I SI Bézieau Stéphane S Thibodeau Stephen N SN Gallinger Steven J SJ Zaidi Syed H SH Harrison Tabitha A TA Keku Temitope O TO Hudson Thomas J TJ Vymetalkova Veronika V Moreno Victor V Martín Vicente V Arndt Volker V Wei Wei-Qi WQ Chung Wendy W Su Yu-Ru YR Hayes Richard B RB White Emily E Vodicka Pavel P Casey Graham G Gruber Stephen B SB Schoen Robert E RE Chan Andrew T AT Potter John D JD Brenner Hermann H Jarvik Gail P GP Corley Douglas A DA Peters Ulrike U Hsu Li L

American journal of human genetics 20200805 3

Accurate colorectal cancer (CRC) risk prediction models are critical for identifying individuals at low and high risk of developing CRC, as they can then be offered targeted screening and interventions to address their risks of developing disease (if they are in a high-risk group) and avoid unnecessary screening and interventions (if they are in a low-risk group). As it is likely that thousands of genetic variants contribute to CRC risk, it is clinically important to investigate whether these ge ...[more]

PMID: 32758450

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Project description:BackgroundAccurately quantifying the risk of osteoporotic fracture is important for directing appropriate clinical interventions. While skeletal measures such as heel quantitative speed of sound (SOS) and dual-energy X-ray absorptiometry bone mineral density are able to predict the risk of osteoporotic fracture, the utility of such measurements is subject to the availability of equipment and human resources. Using data from 341,449 individuals of white British ancestry, we previously developed a genome-wide polygenic risk score (PRS), called gSOS, that captured 25.0% of the total variance in SOS. Here, we test whether gSOS can improve fracture risk prediction.MethodsWe examined the predictive power of gSOS in five genome-wide genotyped cohorts, including 90,172 individuals of European ancestry and 25,034 individuals of Asian ancestry. We calculated gSOS for each individual and tested for the association between gSOS and incident major osteoporotic fracture and hip fracture. We tested whether adding gSOS to the risk prediction models had added value over models using other commonly used clinical risk factors.ResultsA standard deviation decrease in gSOS was associated with an increased odds of incident major osteoporotic fracture in populations of European ancestry, with odds ratios ranging from 1.35 to 1.46 in four cohorts. It was also associated with a 1.26-fold (95% confidence interval (CI) 1.13-1.41) increased odds of incident major osteoporotic fracture in the Asian population. We demonstrated that gSOS was more predictive of incident major osteoporotic fracture (area under the receiver operating characteristic curve (AUROC) = 0.734; 95% CI 0.727-0.740) and incident hip fracture (AUROC = 0.798; 95% CI 0.791-0.805) than most traditional clinical risk factors, including prior fracture, use of corticosteroids, rheumatoid arthritis, and smoking. We also showed that adding gSOS to the Fracture Risk Assessment Tool (FRAX) could refine the risk prediction with a positive net reclassification index ranging from 0.024 to 0.072.ConclusionsWe generated and validated a PRS for SOS which was associated with the risk of fracture. This score was more strongly associated with the risk of fracture than many clinical risk factors and provided an improvement in risk prediction. gSOS should be explored as a tool to improve risk stratification to identify individuals at high risk of fracture.

Project description:BackgroundEvidence is lacking on the impact of alcohol consumption on colorectal cancer (CRC) risk (overall and by age at diagnosis) by polygenic risk score (PRS) levels, and it is unclear how the magnitude of CRC risk associated with alcohol consumption compares to the magnitude of genetically determined risk.MethodsMultiple logistic regression was used to assess the association between alcohol consumption and colorectal cancer (CRC) across PRS levels based on 140 CRC-related loci among 5104 CRC cases and 4131 controls from a large population-based case-control study. We compared the effects for alcohol consumption and PRS on CRC risk using the "Genetic Risk Equivalent (GRE)" for effective risk communication. Specific analyses were conducted for early-onset CRC (EOCRC, <55 years) and late-onset CRC (LOCRC, ≥55 years).FindingsHigh alcohol consumption, and to a lower extent, also alcohol abstinence were associated with increased CRC risk. Compared to low alcohol consumption (0·1-<25 g/d), lifetime average alcohol consumption ≥25 g/d was more strongly associated with EOCRC [odds ratio (OR) 1·8, 95% confidence interval (CI) 1·2-2·8] than with LOCRC risk (OR 1·3, 95% CI 1·1-1·4) (P-value for interaction with age =0·011). Interactions between alcohol consumption and PRS did not reach statistical significance for either EOCRC or LOCRC risk. The estimated impact of high lifetime alcohol consumption on EOCRC was equivalent to the effect of having 47 percentiles higher PRS (GRE 47, 95% CI 12-82), stronger than the impact on LOCRC (GRE 18, 95% CI 8-29).InterpretationExcessive alcohol use was strongly associated with EOCRC risk, independent of PRS levels. Abstaining from heavy drinking could reduce risk for CRC, in particular for EOCRC to an extent that would be equivalent to having a much lower genetically determined risk.FundingThe first author (X.C.) was supported by the Guangzhou Elite Project (GEP). The DACHS study was supported by grants from the German Research Council (BR 1704/6-1, BR1704/6-3, BR 1704/6-4, BR 1704/6-6, CH 117/1-1, BR 1704/17-1, HO 5117/2-1) and the German Federal Ministry of Education and Research (01KH0404, 01ER0814, 01ER0815, 01GL1712).

Dataset Information

Genome-wide Modeling of Polygenic Risk Score in Colorectal Cancer Risk.

Publications

Genome-wide Modeling of Polygenic Risk Score in Colorectal Cancer Risk.

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