Genome-wide scan of everyone possible for Etiologic, Prevention, and Clinical Outcome Research
With declining genotyping costs, we are now able to efficiently genotype the entire cohort of participants without a recent genome-wide scan (n~85,000) on the new Illumina Global Screening Array (GSA) chip. The resulting dataset (n~110,000 participants with harmonized and imputed GWAS data) will accelerate research in PLCO as all bona fide investigators will have access to the genotyping results, enabling them to pursue diverse scientific hypotheses. The genotyped data will only become more valuable overtime, as disease endpoints increase with continued follow-up and researchers from the scientific community complete ongoing projects and deposit their data back into the study.
In addition to contributing towards discovering common disease loci, a fully genotyped cohort will also generate countless new opportunities, such as genetic risk stratification using polygenic risk scores and risk prediction models that integrate genetic and environmental risk factors.
As this cohort-wide effort provides a unique opportunity to generate a resource of DNA samples extracted by the same platform at the same time, which will be useful for future investigations of markers sensitive to DNA extraction method (e.g., telomere length, methylation, microbiome), we will also extract eligible DNA samples for about 11,000 participants with valid GWAS data who will not be re-genotyped.
1. Genotype all participants in PLCO with genetic consent, an available source of DNA, and who don’t have a recent GWAS scan
2. Discover common susceptibility alleles related to cancer, other diseases, phenotypes, and biochemical measures
3. Examine gene-environment interactions and perform Mendelian randomization studies
4. Identify and characterize participants with genetic mosaicism
5. Create a harmonized and imputed genomic dataset that can be leveraged by the scientific community
6. Evaluate the impact of genetic risk stratification using polygenic risk scores on screening trial results
7. Generate risk prediction models that integrate information on genetic and environmental risk factors
Neal Freedman (NCI)
Stephen Chanock (NCI)
Wen-Yi Huang (NCI)
- Genotyping participants in PLCO who now have a DNA source because of the additional buccal collection.
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GWAS Explorer: an open-source tool to explore, visualize, and access GWAS summary statistics in the PLCO Atlas.
Machiela MJ, Huang WY, Wong W, Berndt SI, Sampson J, De Almeida J, Abubakar M, Hislop J, Chen KL, Dagnall C, Diaz-Mayoral N, Ferrell M, Furr M, Gonzalez A, Hicks B, Hubbard AK, Hutchinson A, Jiang K, Jones K, Liu J, ...show more Loftfield E, Loukissas J, Mabie J, Merkle S, Miller E, Minasian LM, Nordgren E, Park B, Pinsky P, Riley T, Sandoval L, Saxena N, Vogt A, Wang J, Williams C, Wright P, Yeager M, Zhu B, Zhu C, Chanock SJ, Garcia-Closas M, Freedman ND
Sci Data. 2023 Jan 12; Volume 10 (Issue 1): Pages 25 PUBMED -
PLCOjs, a FAIR GWAS web SDK for the NCI Prostate, Lung, Colorectal and Ovarian Cancer Genetic Atlas project.
Ruan E , Nemeth E , Moffitt R , Sandoval L , Machiela MJ , Freedman ND , Huang WY , Wong W , Chen KL , Park B , Jiang K , Hicks B , Liu J , Russ D , Minasian L , Pinsky P , Chanock SJ , Garcia-Closas M , Almeida JS
Bioinformatics. 2022 Jul 28 PUBMED