| 1. |
- Rajaraman, Preetha, et al.
(författare)
-
Genome-wide association study of glioma and meta-analysis
- 2012
-
Ingår i: Human Genetics. - : SPRINGER. - 0340-6717 .- 1432-1203. ; 131:12, s. 1877-1888
-
Tidskriftsartikel (refereegranskat)abstract
- Gliomas account for approximately 80 % of all primary malignant brain tumors and, despite improvements in clinical care over the last 20 years, remain among the most lethal tumors, underscoring the need for gaining new insights that could translate into clinical advances. Recent genome-wide association studies (GWAS) have identified seven new susceptibility regions. We conducted a new independent GWAS of glioma using 1,856 cases and 4,955 controls (from 14 cohort studies, 3 case-control studies, and 1 population-based case-only study) and found evidence of strong replication for three of the seven previously reported associations at 20q13.33 (RTEL), 5p15.33 (TERT), and 9p21.3 (CDKN2BAS), and consistent association signals for the remaining four at 7p11.2 (EGFR both loci), 8q24.21 (CCDC26) and 11q23.3 (PHLDB1). The direction and magnitude of the signal were consistent for samples from cohort and case-control studies, but the strength of the association was more pronounced for loci rs6010620 (20q,13.33; RTEL) and rs2736100 (5p15.33, TERT) in cohort studies despite the smaller number of cases in this group, likely due to relatively more higher grade tumors being captured in the cohort studies. We further examined the 85 most promising single nucleotide polymorphism (SNP) markers identified in our study in three replication sets (5,015 cases and 11,601 controls), but no new markers reached genome-wide significance. Our findings suggest that larger studies focusing on novel approaches as well as specific tumor subtypes or subgroups will be required to identify additional common susceptibility loci for glioma risk.
|
|
| 2. |
- Sun, Xiangqing, et al.
(författare)
-
A variable age of onset segregation model for linkage analysis, with correction for ascertainment, applied to glioma
- 2012
-
Ingår i: Cancer Epidemiology, Biomarkers and Prevention. - 1055-9965 .- 1538-7755. ; 21:12, s. 2242-2251
-
Tidskriftsartikel (refereegranskat)abstract
- Background: We propose a two-step model-based approach, with correction for ascertainment, to linkage analysis of a binary trait with variable age of onset and apply it to a set of multiplex pedigrees segregating for adult glioma.Methods: First, we fit segregation models by formulating the likelihood for a person to have a bivariate phenotype, affection status and age of onset, along with other covariates, and from these we estimate population trait allele frequencies and penetrance parameters as a function of age (N=281 multiplex glioma pedigrees). Second, the best fitting models are used as trait models in multipoint linkage analysis (N=74 informative multiplex glioma pedigrees). To correct for ascertainment, a prevalence constraint is used in the likelihood of the segregation models for all 281 pedigrees. Then the trait allele frequencies are re-estimated for the pedigree founders of the subset of 74 pedigrees chosen for linkage analysis.Results: Using the best fitting segregation models in model-based multipoint linkage analysis, we identified two separate peaks on chromosome 17; the first agreed with a region identified by Shete et al. (1) who used model-free affected-only linkage analysis, but with a narrowed peak: and the second agreed with a second region they found but had a larger maximum LOD.Conclusions/Impact: Our approach has the advantage of not requiring markers to be in linkage equilibrium unless the minor allele frequency is small (markers which tend to be uninformative for linkage), and of using more of the available information for LOD-based linkage analysis.
|
|
| 3. |
- Liu, Yanhong, et al.
(författare)
-
Insight in glioma susceptibility through an analysis of 6p22.3, 12p13.33-12.1, 17q22-23.2 and 18q23 SNP genotypes in familial and non-familial glioma
- 2012
-
Ingår i: Human Genetics. - : Springer Science and Business Media LLC. - 0340-6717 .- 1432-1203. ; 131:9, s. 1507-1517
-
Tidskriftsartikel (refereegranskat)abstract
- The risk of glioma has consistently been shown to be increased twofold in relatives of patients with primary brain tumors (PBT). A recent genome-wide linkage study of glioma families provided evidence for a disease locus on 17q12-21.32, with the possibility of four additional risk loci at 6p22.3, 12p13.33-12.1, 17q22-23.2, and 18q23. To identify the underlying genetic variants responsible for the linkage signals, we compared the genotype frequencies of 5,122 SNPs mapping to these five regions in 88 glioma cases with and 1,100 cases without a family history of PBT (discovery study). An additional series of 84 familial and 903 non-familial cases were used to replicate associations. In the discovery study, 12 SNPs showed significant associations with family history of PBT (P < 0.001). In the replication study, two of the 12 SNPs were confirmed: 12p13.33-12.1 PRMT8 rs17780102 (P = 0.031) and 17q12-21.32 SPOP rs650461 (P = 0.025). In the combined analysis of discovery and replication studies, the strongest associations were attained at four SNPs: 12p13.33-12.1 PRMT8 rs17780102 (P = 0.0001), SOX5 rs7305773 (P = 0.0001) and STKY1 rs2418087 (P = 0.0003), and 17q12-21.32 SPOP rs6504618 (P = 0.0006). Further, a significant gene-dosage effect was found for increased risk of family history of PBT with these four SNPs in the combined data set (P (trend) <1.0 × 10(-8)). The results support the linkage finding that some loci in the 12p13.33-12.1 and 17q12-q21.32 may contribute to gliomagenesis and suggest potential target genes underscoring linkage signals.
|
|
| 4. |
- Orr, Nick, et al.
(författare)
-
Genome-wide association study identifies a common variant in RAD51B associated with male breast cancer risk
- 2012
-
Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 44:11, s. 1182-1184
-
Tidskriftsartikel (refereegranskat)abstract
- We conducted a genome-wide association study of male breast cancer comprising 823 cases and 2,795 controls of European ancestry, with validation in independent sample sets totaling 438 cases and 474 controls. A SNP in RAD51B at 14q24.1 was significantly associated with male breast cancer risk (P = 3.02 x 10(-13); odds ratio (OR) = 1.57). We also refine association at 16q12.1 to a SNP within TOX3 (P = 3.87 x 10(-15); OR = 1.50).
|
|
| 5. |
- Wibom, Carl, et al.
(författare)
-
DNA-repair gene variants are associated with glioblastoma survival
- 2012
-
Ingår i: Acta Oncologica. - : Informa Healthcare. - 0284-186X .- 1651-226X. ; 51:3, s. 325-332
-
Tidskriftsartikel (refereegranskat)abstract
- Patient outcome from glioma may be influenced by germline variation. Considering the importance of DNA repair in cancer biology as well as in response to treatment, we studied the relationship between 1458 SNPs, which captured the majority of the common genetic variation in 136 DNA repair genes, in 138 glioblastoma samples from Sweden and Denmark. We confirmed our findings in an independent cohort of 121 glioblastoma patients from the UK. Our analysis revealed nine SNPs annotating MSH2, RAD51L1 and RECQL4 that were significantly (p < 0.05) associated with glioblastoma survival.
|
|
| 6. |
- Broderick, Peter, et al.
(författare)
-
Common variation at 3p22.1 and 7p15.3 influences multiple myeloma risk
- 2012
-
Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 44:1, s. 58-83
-
Tidskriftsartikel (refereegranskat)abstract
- To identify risk variants for multiple myeloma, we conducted a genome-wide association study of 1,675 individuals with multiple myeloma and 5,903 control subjects. We identified risk loci for multiple myeloma at 3p22.1 (rs1052501 in ULK4; odds ratio (OR) = 1.32; P = 7.47 x 10(-9)) and 7p15.3 (rs4487645, OR = 1.38; P = 3.33 x 10(-15)). In addition, we observed a promising association at 2p23.3 (rs6746082, OR = 1.29; P = 1.22 x 10(-7)). Our study identifies new genomic regions associated with multiple myeloma risk that may lead to new etiological insights.
|
|
| 7. |
- Dunlop, Malcolm G, et al.
(författare)
-
Cumulative impact of 10 common genetic variants on colorectal cancer risk in 42,333 individuals from eight populations
- 2012
-
Ingår i: Gut. - Stockholm : Karolinska Institutet, Dept of Molecular Medicine and Surgery. - 1468-3288 .- 0017-5749.
-
Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE: Colorectal cancer (CRC) has a substantial heritable component. Common genetic variation has been shown to contribute to CRC risk. A study was conducted in a large multi-population study to assess the feasibility of CRC risk prediction using common genetic variant data combined with other risk factors. A risk prediction model was built and applied to the Scottish population using available data. DESIGN: Nine populations of European descent were studied to develop and validate CRC risk prediction models. Binary logistic regression was used to assess the combined effect of age, gender, family history (FH) and genotypes at 10 susceptibility loci that individually only modestly influence CRC risk. Risk models were generated from case-control data incorporating genotypes alone (n=39 266) and in combination with gender, age and FH (n=11 324). Model discriminatory performance was assessed using 10-fold internal cross-validation and externally using 4187 independent samples. The 10-year absolute risk was estimated by modelling genotype and FH with age- and gender-specific population risks. RESULTS: The median number of risk alleles was greater in cases than controls (10 vs 9, p<2.2×10(-16)), confirmed in external validation sets (Sweden p=1.2×10(-6), Finland p=2×10(-5)). The mean per-allele increase in risk was 9% (OR 1.09; 95% CI 1.05 to 1.13). Discriminative performance was poor across the risk spectrum (area under curve for genotypes alone 0.57; area under curve for genotype/age/gender/FH 0.59). However, modelling genotype data, FH, age and gender with Scottish population data shows the practicalities of identifying a subgroup with >5% predicted 10-year absolute risk. CONCLUSION: Genotype data provide additional information that complements age, gender and FH as risk factors, but individualised genetic risk prediction is not currently feasible. Nonetheless, the modelling exercise suggests public health potential since it is possible to stratify the population into CRC risk categories, thereby informing targeted prevention and surveillance.
|
|
| 8. |
|
|
