ArticleCancer informatics2018
A Bayesian Gene-Based Genome-Wide Association Study Analysis of Osteosarcoma Trio Data Using a Hierarchically Structured Prior.
Article in Cancer informatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
12 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- A Bayesian hierarchically structured prior for gene-based association testing with multiple traits in genome-wide association studies.Genetic epidemiology · 2022Pooled it
- Pooled it
- Genetic variation near GRB10 associated with bone growth and osteosarcoma risk in canine and human populations.Cancer epidemiology · 2024Article
- Cellular Transcriptomics of Carboplatin Resistance in a Metastatic Canine Osteosarcoma Cell Line.Genes · 2023Article
- Gene-based association tests using GWAS summary statistics and incorporating eQTL.Scientific reports · 2022Article
- A Bayesian hierarchically structured prior for rare-variant association testing.Genetic epidemiology · 2021Article
- Multi-trait multi-locus SEM model discriminates SNPs of different effects.BMC genomics · 2020Article
- Pharmacogenomics and Pharmacogenetics in Osteosarcoma: Translational Studies and Clinical Impact.International journal of molecular sciences · 2020Review
- Cancer Progress and Priorities: Childhood Cancer.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2020Article
- A Bayesian hierarchical variable selection prior for pathway-based GWAS using summary statistics.Statistics in medicine · 2020Article
- Provocative questions in osteosarcoma basic and translational biology: A report from the Children's Oncology Group.Cancer · 2019Review
- Risk Factors for Development of Canine and Human Osteosarcoma: A Comparative Review.Veterinary sciences · 2019Review
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Osteosarcoma is considered to be the most common primary malignant bone cancer among children and young adults. Previous studies suggest growth spurts and height to be risk factors for osteosarcoma. However, studies on the genetic cause are still limited given the rare occurrence of the disease. In this study, we investigated in a family trio data set that is composed of 209 patients and their unaffected parents and conducted a genome-wide association study (GWAS) to identify genetic risk factors for osteosarcoma. We performed a Bayesian gene-based GWAS based on the single-nucleotide polymorphism (SNP)-level summary statistics obtained from a likelihood ratio test of the trio data, which uses a hierarchically structured prior that incorporates the SNP-gene hierarchical structure. The Bayesian approach has higher power than SNP-level GWAS analysis due to the reduced number of tests and is robust by accounting for the correlations between SNPs so that it borrows information across SNPs within a gene. We identified 217 genes that achieved genome-wide significance. Ingenuity pathway analysis of the gene set indicated that osteosarcoma is potentially related to TP53, estrogen receptor signaling, xenobiotic metabolism signaling, and RANK signaling in osteoclasts.
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Registered trials
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