Genome-wide polygenic risk scores predict risk of glioma and molecular subtypes

全基因组关联研究 多基因风险评分 遗传关联 生物 胶质瘤 计算生物学 遗传学 基因型 单核苷酸多态性 基因
作者
Taishi Nakase,Geno Guerra,Quinn T. Ostrom,Tian Ge,Beatrice Melin,Margaret Wrensch,John K. Wiencke,Robert B. Jenkins,Jeanette E. Eckel‐Passow,Melissa L. Bondy,Stephen Francis,Linda Kachuri
出处
期刊:Neuro-oncology [Oxford University Press]
卷期号:26 (10): 1933-1944 被引量:3
标识
DOI:10.1093/neuonc/noae112
摘要

Abstract Background Polygenic risk scores (PRS) aggregate the contribution of many risk variants to provide a personalized genetic susceptibility profile. Since sample sizes of glioma genome-wide association studies (GWAS) remain modest, there is a need to efficiently capture genetic risk using available data. Methods We applied a method based on continuous shrinkage priors (PRS-CS) to model the joint effects of over 1 million common variants on disease risk and compared this to an approach (PRS-CT) that only selects a limited set of independent variants that reach genome-wide significance (P < 5 × 10–8). PRS models were trained using GWAS stratified by histological (10 346 cases and 14 687 controls) and molecular subtype (2632 cases and 2445 controls), and validated in 2 independent cohorts. Results PRS-CS was generally more predictive than PRS-CT with a median increase in explained variance (R2) of 24% (interquartile range = 11–30%) across glioma subtypes. Improvements were pronounced for glioblastoma (GBM), with PRS-CS yielding larger odds ratios (OR) per standard deviation (SD) (OR = 1.93, P = 2.0 × 10–54 vs. OR = 1.83, P = 9.4 × 10–50) and higher explained variance (R2 = 2.82% vs. R2 = 2.56%). Individuals in the 80th percentile of the PRS-CS distribution had a significantly higher risk of GBM (0.107%) at age 60 compared to those with average PRS (0.046%, P = 2.4 × 10–12). Lifetime absolute risk reached 1.18% for glioma and 0.76% for IDH wildtype tumors for individuals in the 95th PRS percentile. PRS-CS augmented the classification of IDH mutation status in cases when added to demographic factors (AUC = 0.839 vs. AUC = 0.895, PΔAUC = 6.8 × 10–9). Conclusions Genome-wide PRS has the potential to enhance the detection of high-risk individuals and help distinguish between prognostic glioma subtypes.
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