Dataset Information

A Weighted Genetic Risk Score of Adult Glioma Susceptibility Loci Associated with Pediatric Brain Tumor Risk.

ABSTRACT: Genetic risk score (GRS) is used to demonstrate the genetic variants contributing to the polygenic architecture of complex diseases. By using a GRS, we have investigated the additive impact of the known adult glioma susceptibility loci on the pediatric brain tumor (PBT) risk and assessed the proportion of PBT heritability attributable to these susceptibility loci. A GRS was generated for PBTs based on the alleles and associated effect sizes derived from a previously published genome-wide association study on adult glioma. The GRS was calculated in CEFALO, a population-based case-control study of brain tumors in children and adolescents including saliva DNA of 245 cases and 489 controls. The unconditional logistic regression model was used to investigate the association between standardized GRS and risk of PBTs. To measure the variance explained by the effect of GRS, Nagelkerke pseudo-R2 was calculated. The GRS for adult brain tumors was associated with an increased risk of PBTs (OR 1.25 [95% CI 1.06-1.49], p?=?0.009) and 0.3% of the variance in PBTs could be explained by the effect of GRS on the liability scale. This study provides evidence that heritable risks of PBTs are in-part attributable to some common genetic variants associated with adult glioma.

SUBMITTER: Adel Fahmideh M

PROVIDER: S-EPMC6889151 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A Weighted Genetic Risk Score of Adult Glioma Susceptibility Loci Associated with Pediatric Brain Tumor Risk.

Adel Fahmideh Maral M Lavebratt Catharina C Tettamanti Giorgio G Schüz Joachim J Röösli Martin M Kjaerheim Kristina K Grotzer Michael A MA Johansen Christoffer C Kuehni Claudia E CE Lannering Birgitta B Schmidt Lisbeth S LS Darabi Hatef H Feychting Maria M

Scientific reports 20191202 1

Genetic risk score (GRS) is used to demonstrate the genetic variants contributing to the polygenic architecture of complex diseases. By using a GRS, we have investigated the additive impact of the known adult glioma susceptibility loci on the pediatric brain tumor (PBT) risk and assessed the proportion of PBT heritability attributable to these susceptibility loci. A GRS was generated for PBTs based on the alleles and associated effect sizes derived from a previously published genome-wide associa ...[more]

PMID: 31792337

Similar Datasets

Project description:OBJECTIVE:Children with childhood-onset rheumatoid arthritis (RA) include those with rheumatoid factor or anti-citrullinated protein antibody-positive juvenile idiopathic arthritis. To test the hypothesis that adult-onset RA-associated variants are also associated with childhood-onset RA, we investigated RA-associated variants at 5 loci in a cohort of patients with childhood-onset RA. We also assessed the cumulative association of these variants in susceptibility to childhood-onset RA using a weighted genetic risk score (wGRS). METHODS:A total of 155 children with childhood-onset RA and 684 healthy controls were genotyped for 5 variants in the PTPN22, TRAF1/C5, STAT4, and TNFAIP3 loci. High-resolution HLA-DRB1 genotypes were available for 149 cases and 373 controls. We tested each locus for association with childhood-onset RA via logistic regression. We also computed a wGRS for each subject, with weights based on the natural log of the published odds ratios (ORs) for the alleles investigated, and used logistic regression to test the wGRS for association with childhood-onset RA. RESULTS:Childhood-onset RA was associated with TNFAIP3 rs10499194 (OR 0.60 [95% confidence interval 0.44-0.83]), PTPN22 rs2476601 (OR 1.61 [95% confidence interval 1.11-2.31]), and STAT4 rs7574865 (OR 1.41 [95% confidence interval 1.06-1.87]) variants. The wGRS was significantly different between cases and controls (P < 2 × 10(-16) ). Individuals in the third to fifth quintiles of wGRS had a significantly increased disease risk compared to baseline (individuals in the first quintile). Higher wGRS was associated with increased risk of childhood-onset RA, especially among males. CONCLUSION:The magnitude and direction of the association between TNFAIP3, STAT4, and PTPN22 variants and childhood-onset RA are similar to those observed in RA, suggesting that adult-onset RA and childhood-onset RA share common genetic risk factors. Using a wGRS, we have demonstrated the cumulative association of RA-associated variants with susceptibility to childhood-onset RA.

Project description:Prediction of susceptibility to multiple sclerosis (MS) might have important clinical applications, either as part of a diagnostic algorithm or as a means to identify high-risk individuals for prospective studies. We investigated the usefulness of an aggregate measure of risk of MS that is based on genetic susceptibility loci. We also assessed the added effect of environmental risk factors that are associated with susceptibility for MS.We created a weighted genetic risk score (wGRS) that includes 16 MS susceptibility loci. We tested our model with data from 2215 individuals with MS and 2189 controls (derivation samples), a validation set of 1340 individuals with MS and 1109 controls taken from several MS therapeutic trials (TT cohort), and a second validation set of 143 individuals with MS and 281 controls from the US Nurses' Health Studies I and II (NHS/NHS II), for whom we also have data on smoking and immune response to Epstein-Barr virus (EBV).Individuals with a wGRS that was more than 1.25 SD from the mean had a significantly higher odds of MS in all datasets. In the derivation sample, the mean (SD) wGRS was 3.5 (0.7) for individuals with MS and 3.0 (0.6) for controls (p<0.0001); in the TT validation sample, the mean wGRS was 3.4 (0.7) for individuals with MS versus 3.1 (0.7) for controls (p<0.0001); and in the NHS/NHS II dataset, the mean wGRS was 3.4 (0.8) for individuals with MS versus 3.0 (0.7) for controls (p<0.0001). In the derivation cohort, the area under the receiver operating characteristic curve (C statistic; a measure of the ability of a model to discriminate between individuals with MS and controls) for the genetic-only model was 0.70 and for the genetics plus sex model was 0.74 (p<0.0001). In the TT and NHS cohorts, the C statistics for the genetic-only model were both 0.64; adding sex to the TT model increased the C statistic to 0.72 (p<0.0001), whereas adding smoking and immune response to EBV to the NHS model increased the C statistic to 0.68 (p=0.02). However, the wGRS does not seem to be correlated with the conversion of clinically isolated syndrome to MS.The inclusion of 16 susceptibility alleles into a wGRS can modestly predict MS risk, shows consistent discriminatory ability in independent samples, and is enhanced by the inclusion of non-genetic risk factors into the algorithm. Future iterations of the wGRS might therefore make a contribution to algorithms that can predict a diagnosis of MS in a clinical or research setting.

Dataset Information

A Weighted Genetic Risk Score of Adult Glioma Susceptibility Loci Associated with Pediatric Brain Tumor Risk.

Publications

A Weighted Genetic Risk Score of Adult Glioma Susceptibility Loci Associated with Pediatric Brain Tumor Risk.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets