Cancer genetic association studies in the genome-wide age.
Ontology highlight
ABSTRACT:
SUBMITTER: Savage SA
PROVIDER: S-EPMC2659339 | biostudies-literature | 2008 Nov
REPOSITORIES: biostudies-literature
Publications
Cancer genetic association studies in the genome-wide age.
Personalized medicine 20081101 6
Genome-wide association studies of hundreds of thousands of SNPs have led to a deluge of studies of genetic variation in cancer and other common diseases. Large case-control and cohort studies have identified novel SNPs as markers of cancer risk. Genome-wide association study SNP data have also advanced understanding of population-specific genetic variation. While studies of risk profiles, combinations of SNPs that may increase cancer risk, are not yet clinically applicable, future, large-scale ...[more]
Similar Datasets
Project description:This SuperSeries is composed of the SubSeries listed below.
2022-03-09 | GSE197678 | GEO
Project description:Fixed-effect meta-analysis has been used to summarize genetic effects on a phenotype across multiple Genome-Wide Association Studies (GWAS) assuming a common underlying genetic effect. Genetic effects may vary with age (or other characteristics), and not allowing for this in a GWAS might lead to bias. Meta-regression models between study heterogeneity and allows effect modification of the genetic effects to be explored. The aim of this study was to explore the use of meta-analysis and meta-regression for estimating age-varying genetic effects on phenotypes. With simulations we compared the performance of meta-regression to fixed-effect and random -effects meta-analyses in estimating (i) main genetic effects and (ii) age-varying genetic effects (SNP by age interactions) from multiple GWAS studies under a range of scenarios. We applied meta-regression on publicly available summary data to estimate the main and age-varying genetic effects of the FTO SNP rs9939609 on Body Mass Index (BMI). Fixed-effect and random-effects meta-analyses accurately estimated genetic effects when these did not change with age. Meta-regression accurately estimated both main genetic effects and age-varying genetic effects. When the number of studies or the age-diversity between studies was low, meta-regression had limited power. In the applied example, each additional minor allele (A) of rs9939609 was inversely associated with BMI at ages 0 to 3, and positively associated at ages 5.5 to 13. Our findings challenge the assumption that genetic effects are consistent across all ages and provide a method for exploring this. GWAS consortia should be encouraged to use meta-regression to explore age-varying genetic effects.
| S-EPMC10995067 | biostudies-literature
Project description:BackgroundIncreased epigenetic age acceleration (EAA) in survivors of childhood cancer is associated with specific treatment exposures, unfavorable health behaviors, and presence of certain chronic health conditions. To better understand inter-individual variability, we investigated the genetic basis underlying EAA.MethodsGenome-wide association studies of EAA based on multiple epigenetic clocks (Hannum, Horvath, PhenoAge, and GrimAge) were performed. MethylationEPIC BeadChip array and whole-genome sequencing data were generated with blood-derived DNA from participants in the St. Jude Lifetime Cohort Study (discovery: 2138 pre-existing and 502 newly generated data, all survivors; exploratory: 282 community controls). Linear regression models were fit for each epigenetic age against the allelic dose of each genetic variant, adjusting for age at sampling, sex, and cancer treatment exposures. Fixed-effects meta-analysis was used to combine summary statistics from two discovery data sets. LD (Linkage disequilibrium) score regression was used to estimate single-nucleotide polymorphism (SNP)-based heritability.ResultsFor EAA-Horvath, a genome-wide significant association was mapped to the SELP gene with the strongest SNP rs732314 (meta-GWAS: β=0.57, P=3.30×10-11). Moreover, the stratified analysis of the association between rs732314 and EAA-Horvath showed a substantial heterogeneity between children and adults (meta-GWAS: β=0.97 vs. 0.51, I2=73.1%) as well as between survivors with and without chest/abdominal/pelvic-RT exposure (β=0.64 vs. 0.31, I2=66.3%). For EAA-Hannum, an association was mapped to the HLA locus with the strongest SNP rs28366133 (meta-GWAS: β=0.78, P=3.78×10-11). There was no genome-wide significant hit for EAA-PhenoAge or EAA-GrimAge. Interestingly, among community controls, rs732314 was associated with EAA-Horvath (β=1.09, P=5.43×10-5), whereas rs28366133 was not associated with EAA-Hannum (β=0.21, P=0.49). The estimated heritability was 0.33 (SE=0.20) for EAA-Horvath and 0.17 (SE=0.23) for EAA-Hannum, but close to zero for EAA-PhenoAge and EAA-GrimAge.ConclusionsWe identified novel genetic variants in the SELP gene and HLA region associated with EAA-Horvath and EAA-Hannum, respectively, among survivors of childhood cancer. The new genetic variants in combination with other replicated known variants can facilitate the identification of survivors at higher risk in developing accelerated aging and potentially inform drug targets for future intervention strategies among vulnerable survivors.
| S-EPMC8939156 | biostudies-literature
Project description:Background: Increased epigenetic age acceleration (EAA) in survivors of childhood cancer is associated with specific treatment exposures, unfavorable health behaviors, and presence of certain chronic health conditions. To better understand inter-individual variability, we investigated the genetic basis underlying EAA. Methods: Genome-wide association studies of EAA based on multiple epigenetic clocks (Hannum, Horvath, PhenoAge, and GrimAge) were performed. MethylationEPIC BeadChip array and whole-genome sequencing data were generated with blood-derived DNA from participants in the St. Jude Lifetime Cohort Study (discovery: 2,138 pre-existing and 502 newly generated data, all survivors; exploratory: 282 community controls). Linear regression models were fit for each epigenetic age against allelic dose of each genetic variant, adjusting for age at sampling, sex, and cancer treatment exposures. Fixed-effects meta-analysis was used to combine summary statistics from two discovery data sets. LD (Linkage disequilibrium) score regression was used to estimate single-nucleotide polymorphism (SNP)-based heritability. Results: For EAA-Horvath, a genome-wide significant association was mapped to SELP gene with the strongest SNP rs732314 (meta-GWAS: β=0.57, P=3.30×10-11). Moreover, the stratified analysis of the association between rs732314 and EAA-Horvath showed substantial heterogeneity between children and adults (meta-GWAS: β=0.97 vs. 0.51, I2=73.1%) as well as between survivors with and without chest/abdominal/pelvic-RT exposure (β=0.64 vs. 0.31, I2=66.3%). For EAA-Hannum, an association was mapped to HLA locus with the strongest SNP rs28366133 (meta-GWAS: β=0.78, P=3.78×10-11). There was no genome-wide significant hit for EAA-PhenoAge or EAA-GrimAge. Interestingly, among community controls, rs732314 was associated with EAA-Horvath (β=1.09, P=5.43×10-5), whereas rs28366133 was not associated with EAA-Hannum (β=0.21, P=0.49). The estimated heritability was 0.33 (SE=0.20) for EAA-Horvath and 0.17 (SE=0.23) for EAA-Hannum, but close to zero for EAA-PhenoAge and EAA-GrimAge. Conclusions: We identified novel genetic variants in SELP gene and HLA region associated with EAA-Horvath and EAA-Hannum, respectively, among survivors of childhood cancer. The new genetic variants in combination with other replicated known variants can facilitate identification of survivors at higher risk in developing accelerated aging, and potentially inform drug targets for future intervention strategies among vulnerable survivors.
2022-03-09 | GSE197674 | GEO
Project description:Background: Increased epigenetic age acceleration (EAA) in survivors of childhood cancer is associated with specific treatment exposures, unfavorable health behaviors, and presence of certain chronic health conditions. To better understand inter-individual variability, we investigated the genetic basis underlying EAA. Methods: Genome-wide association studies of EAA based on multiple epigenetic clocks (Hannum, Horvath, PhenoAge, and GrimAge) were performed. MethylationEPIC BeadChip array and whole-genome sequencing data were generated with blood-derived DNA from participants in the St. Jude Lifetime Cohort Study (discovery: 2,138 pre-existing and 502 newly generated data, all survivors; exploratory: 282 community controls). Linear regression models were fit for each epigenetic age against allelic dose of each genetic variant, adjusting for age at sampling, sex, and cancer treatment exposures. Fixed-effects meta-analysis was used to combine summary statistics from two discovery data sets. LD (Linkage disequilibrium) score regression was used to estimate single-nucleotide polymorphism (SNP)-based heritability. Results: For EAA-Horvath, a genome-wide significant association was mapped to SELP gene with the strongest SNP rs732314 (meta-GWAS: β=0.57, P=3.30×10-11). Moreover, the stratified analysis of the association between rs732314 and EAA-Horvath showed substantial heterogeneity between children and adults (meta-GWAS: β=0.97 vs. 0.51, I2=73.1%) as well as between survivors with and without chest/abdominal/pelvic-RT exposure (β=0.64 vs. 0.31, I2=66.3%). For EAA-Hannum, an association was mapped to HLA locus with the strongest SNP rs28366133 (meta-GWAS: β=0.78, P=3.78×10-11). There was no genome-wide significant hit for EAA-PhenoAge or EAA-GrimAge. Interestingly, among community controls, rs732314 was associated with EAA-Horvath (β=1.09, P=5.43×10-5), whereas rs28366133 was not associated with EAA-Hannum (β=0.21, P=0.49). The estimated heritability was 0.33 (SE=0.20) for EAA-Horvath and 0.17 (SE=0.23) for EAA-Hannum, but close to zero for EAA-PhenoAge and EAA-GrimAge. Conclusions: We identified novel genetic variants in SELP gene and HLA region associated with EAA-Horvath and EAA-Hannum, respectively, among survivors of childhood cancer. The new genetic variants in combination with other replicated known variants can facilitate identification of survivors at higher risk in developing accelerated aging, and potentially inform drug targets for future intervention strategies among vulnerable survivors.
2022-03-09 | GSE197676 | GEO
Project description:Background: Increased epigenetic age acceleration (EAA) in survivors of childhood cancer is associated with specific treatment exposures, unfavorable health behaviors, and presence of certain chronic health conditions. To better understand inter-individual variability, we investigated the genetic basis underlying EAA. Methods: Genome-wide association studies of EAA based on multiple epigenetic clocks (Hannum, Horvath, PhenoAge, and GrimAge) were performed. MethylationEPIC BeadChip array and whole-genome sequencing data were generated with blood-derived DNA from participants in the St. Jude Lifetime Cohort Study (discovery: 2,138 pre-existing and 502 newly generated data, all survivors; exploratory: 282 community controls). Linear regression models were fit for each epigenetic age against allelic dose of each genetic variant, adjusting for age at sampling, sex, and cancer treatment exposures. Fixed-effects meta-analysis was used to combine summary statistics from two discovery data sets. LD (Linkage disequilibrium) score regression was used to estimate single-nucleotide polymorphism (SNP)-based heritability. Results: For EAA-Horvath, a genome-wide significant association was mapped to SELP gene with the strongest SNP rs732314 (meta-GWAS: β=0.57, P=3.30×10-11). Moreover, the stratified analysis of the association between rs732314 and EAA-Horvath showed substantial heterogeneity between children and adults (meta-GWAS: β=0.97 vs. 0.51, I2=73.1%) as well as between survivors with and without chest/abdominal/pelvic-RT exposure (β=0.64 vs. 0.31, I2=66.3%). For EAA-Hannum, an association was mapped to HLA locus with the strongest SNP rs28366133 (meta-GWAS: β=0.78, P=3.78×10-11). There was no genome-wide significant hit for EAA-PhenoAge or EAA-GrimAge. Interestingly, among community controls, rs732314 was associated with EAA-Horvath (β=1.09, P=5.43×10-5), whereas rs28366133 was not associated with EAA-Hannum (β=0.21, P=0.49). The estimated heritability was 0.33 (SE=0.20) for EAA-Horvath and 0.17 (SE=0.23) for EAA-Hannum, but close to zero for EAA-PhenoAge and EAA-GrimAge. Conclusions: We identified novel genetic variants in SELP gene and HLA region associated with EAA-Horvath and EAA-Hannum, respectively, among survivors of childhood cancer. The new genetic variants in combination with other replicated known variants can facilitate identification of survivors at higher risk in developing accelerated aging, and potentially inform drug targets for future intervention strategies among vulnerable survivors.
2022-03-09 | GSE197675 | GEO
Project description:The availability of affordable high throughput technology for parallel genotyping has opened the field of genetics to genome-wide association studies (GWAS), and in the last few years hundreds of articles reporting results of GWAS for a variety of heritable traits have been published. What do these results tell us? Although GWAS have discovered a few hundred reproducible associations, this number is underwhelming in relation to the huge amount of data produced, and challenges the conjecture that common variants may be the genetic causes of common diseases. We argue that the massive amount of genetic data that result from these studies remains largely unexplored and unexploited because of the challenge of mining and modeling enormous data sets, the difficulty of using nontraditional computational techniques and the focus of accepted statistical analyses on controlling the false positive rate rather than limiting the false negative rate. In this article, we will review the common approach to analysis of GWAS data and then discuss options to learn more from these data. We will use examples from our ongoing studies of sickle cell anemia and also GWAS in multigenic traits.
| S-EPMC2895326 | biostudies-other
Project description:Knowledge of the inherited risk for cancer is an important component of preventive oncology. In addition to well-established syndromes of cancer predisposition, much remains to be discovered about the genetic variation underlying susceptibility to common malignancies. Increased knowledge about the human genome and advances in genotyping technology have made possible genome-wide association studies (GWAS) of human diseases. These studies have identified many important regions of genetic variation associated with an increased risk for human traits and diseases including cancer. Understanding the principles, major findings, and limitations of GWAS is becoming increasingly important for oncologists as dissemination of genomic risk tests directly to consumers is already occurring through commercial companies. GWAS have contributed to our understanding of the genetic basis of cancer and will shed light on biologic pathways and possible new strategies for targeted prevention. To date, however, the clinical utility of GWAS-derived risk markers remains limited.
| S-EPMC2953976 | biostudies-literature
Project description:In recent years, genome-wide association studies (GWAS), which are able to analyze the contribution to disease of genetic variations that are common within a population, have attracted considerable investment. Despite identifying genetic variants for many conditions, they have been criticized for yielding data with minimal clinical utility. However, in this regard, age-related macular degeneration (AMD), the most common form of blindness in the Western world, is a striking exception. Through GWAS, common genetic variants at a number of loci have been discovered. Two loci in particular, including genes of the complement cascade on chromosome 1 and the ARMS2/HTRA1 genes on chromosome 10, have been shown to convey significantly increased susceptibility to developing AMD. Today, although it is possible to screen individuals for a genetic predisposition to the disease, effective interventional strategies for those at risk of developing AMD are scarce. Ongoing research in this area is nonetheless promising. After providing brief overviews of AMD and common disease genetics, we outline the main recent advances in the understanding of AMD, particularly those made through GWAS. Finally, the true merit of these findings and their current and potential translational value is examined.Genet Med 18 4, 283-289.
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Project description:Completion of the human genome a decade ago laid the foundation for: using genetic information in assessing risk to identify individuals and populations that are likely to develop cancer, and designing treatments based on a person's genetic profiling (precision medicine). Genome-wide association studies (GWAS) completed during the past few years have identified risk-associated single nucleotide polymorphisms that can be used as screening tools in epidemiologic studies of a variety of tumor types. This led to the conduct of epigenome-wide association studies (EWAS). This article discusses the current status, challenges and research opportunities in GWAS and EWAS. Information gained from GWAS and EWAS has potential applications in cancer control and treatment.
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