Data from: Genome-wide Polygenic Risk Scores Predict Risk of Glioma and Molecular Subtypes
Creators
- Nakase, Taishi (Data manager)1
- Guerra, Geno (Other)2
- Ostrom, Quinn T. (Other)3
- Ge, Tian (Other)4, 5, 6
- Melin, Beatrice (Other)7
- Wrensch, Margaret (Other)2
- Wiencke, John K. (Other)2
- Jenkins, Robert B. (Other)8
- Eckel-Passow, Jeanette E. (Other)8
- Glioma International Case-Control Study (GICC)
- Bondy, Melissa L. (Other)1
- Francis, Stephen S. (Other)2
- Kachuri, Linda (Contact person)1
-
1.
Stanford University School of Medicine
-
2.
University of California, San Francisco
-
3.
Duke University School of Medicine
-
4.
Massachusetts General Hospital
-
5.
Harvard Medical School
-
6.
Broad Institute
-
7.
Umeå University
-
8.
Mayo Clinic
Description
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, 14,687 controls) and molecular subtype (2,632 cases, 2,445 controls), and validated in two 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 (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 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, P=6.8×10-9).
Conclusions: Genome-wide PRS has potential to enhance the detection of high-risk individuals and help distinguish between prognostic glioma subtypes.
Citation: Nakase T, Guerra GA, Ostrom QT, et al. Genome-wide Polygenic Risk Scores Predict Risk of Glioma and Molecular Subtypes. Neuro-Oncology. Published online June 25, 2024:noae112. doi:10.1093/neuonc/noae112
Files
README.md
Files
(4.6 GB)
| Name | Size | Download all |
|---|---|---|
|
md5:a596982c963bc1555ed3ed64bd2ae36b
|
9.6 MB | Download |
|
md5:17522379db4becbf9862dd92c529c340
|
9.6 MB | Download |
|
md5:1bc0cda4731b5b8cbd4c2fcc2186b902
|
10.7 MB | Download |
|
md5:6678113d9eef77d99872e370f42fa394
|
10.7 MB | Download |
|
md5:2e913347aebc914e5e51c2dec52c1aa5
|
10.7 MB | Download |
|
md5:111cf233446ca9b5d846d7842cb0b09d
|
10.7 MB | Download |
|
md5:4312d4db96a4628cb1e697a6a368ae10
|
4.6 GB | Download |
|
md5:6abdb562cd2f327cd87ec839fbb856c5
|
9.7 MB | Download |
|
md5:8b9a5f24d28944032a2a3763afe49c0e
|
1.4 kB | Preview Download |