| 1. |
- Berndt, Sonja I., et al.
(författare)
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Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture
- 2013
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 45:5, s. 501-U69
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Tidskriftsartikel (refereegranskat)abstract
- Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.
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| 2. |
- Berndt, Sonja I., et al.
(författare)
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Genome-wide association study identifies multiple risk loci for chronic lymphocytic leukemia
- 2013
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 45:8, s. 868-U202
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Tidskriftsartikel (refereegranskat)abstract
- Genome-wide association studies (GWAS) have previously identified 13 loci associated with risk of chronic lymphocytic leukemia or small lymphocytic lymphoma (CLL). To identify additional CLL susceptibility loci, we conducted the largest meta-analysis for CLL thus far, including four GWAS with a total of 3,100 individuals with CLL (cases) and 7,667 controls. In the meta-analysis, we identified ten independent associated SNPs in nine new loci at 10q23.31 (ACTA2 or FAS (ACTA2/FAS), P = 1.22 x 10(-14)), 18q21.33 (BCL2, P = 7.76 x 10(-11)), 11p15.5 (C11orf21, P = 2.15 x 10(-10)), 4q25 (LEF1, P = 4.24 x 10(-10)), 2q33.1 (CASP10 or CASP8 (CASP10/CASP8), P = 2.50 x 10(-9)), 9p21.3 (CDKN2B-AS1, P = 1.27 x 10(-8)), 18q21.32 (PMAIP1, P = 2.51 x 10(-8)), 15q15.1 (BMF, P = 2.71 x 10(-10)) and 2p22.2 (QPCT, P = 1.68 x 10(-8)), as well as an independent signal at an established locus (2q13, ACOXL, P = 2.08 x 10(-18)). We also found evidence for two additional promising loci below genome-wide significance at 8q22.3 (ODF1, P = 5.40 x 10(-8)) and 5p15.33 (TERT, P = 1.92 x 10(-7)). Although further studies are required, the proximity of several of these loci to genes involved in apoptosis suggests a plausible underlying biological mechanism.
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| 3. |
- Hu, Yi-Juan, et al.
(författare)
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Meta-analysis of Gene-Level Associations for Rare Variants Based on Single-Variant Statistics
- 2013
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Ingår i: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297 .- 1537-6605. ; 93:2, s. 236-248
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Tidskriftsartikel (refereegranskat)abstract
- Meta-analysis of genome-wide association studies (GWASs) has led to the discoveries of many common variants associated with complex human diseases. There is a growing recognition that identifying "causal" rare variants also requires large-scale meta-analysis. The fact that association tests with rare variants are performed at the gene level rather than at the variant level poses unprecedented challenges in the meta-analysis. First, different studies may adopt different gene-level tests, so the results are not compatible. Second, gene-level tests require multivariate statistics (i.e., components of the test statistic and their covariance matrix), which are difficult to obtain. To overcome these challenges, we propose to perform gene-level tests for rare variants by combining the results of single-variant analysis (i.e., p values of association tests and effect estimates) from participating studies. This simple strategy is possible because of an insight that multivariate statistics can be recoVered from single-variant statistics, together with the correlation matrix of the single-variant test statistics, which can be estimated from one of the participating studies or from a publicly available database. We show both theoretically and numerically that the proposed meta-analysis approach provides accurate control of the type I error and is as powerful as joint analysis of individual participant data. This approach accommodates any disease phenotype and any study design and produces all commonly used gene-level tests. An application to the GWAS summary results of the Genetic Investigation of ANthropometric Traits (GIANT) consortium reveals rare and low-frequency variants associated with human height. The relevant software is freely available.
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| 4. |
- Tsilidis, Konstantinos K., et al.
(författare)
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Insulin-like growth factor pathway genes and blood concentrations, dietary protein and risk of prostate cancer in the NCI Breast and Prostate Cancer Cohort Consortium (BPC3)
- 2013
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Ingår i: International Journal of Cancer. - Hoboken, NJ, USA : Wiley-Blackwell. - 0020-7136 .- 1097-0215. ; 133:2, s. 495-504
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Tidskriftsartikel (refereegranskat)abstract
- It has been hypothesized that a high intake of dairy protein may increase prostate cancer risk by increasing the production of insulin-like growth factor 1 (IGF-1). Several single nucleotide polymorphisms (SNPs) have been weakly associated with circulating concentrations of IGF-1 and IGF binding protein 3 (IGFBP-3), but none of these SNPs was associated with risk of prostate cancer. We examined whether an association between 16 SNPs associated with circulating IGF-1 or IGFBP-3 concentrations and prostate cancer exists within subgroups defined by dietary protein intake in 5,253 cases and 4,963 controls of European ancestry within the NCI Breast and Prostate Cancer Cohort Consortium (BPC3). The BPC3 includes nested casecontrol studies within large North-American and European cohorts. Per-allele odds ratios for prostate cancer for the SNPs were compared across tertiles of protein intake, which was expressed as the percentage of energy derived from total, animal, dairy or plant protein sources, using conditional logistic regression models. Total, animal, dairy and plant protein intakes were significantly positively associated with blood IGF-1 (p<0.01), but not with IGFBP-3 concentrations (p>0.10) or with risk of prostate cancer (p>0.20). After adjusting for multiple testing, the SNP-prostate cancer associations did not differ by intakes of protein, although two interactions by intake of plant protein were of marginal statistical significance [SSTR5 (somatostatin receptor 5)-rs197056 (uncorrected p for interaction, 0.001); SSTR5-rs197057 (uncorrected p for interaction, 0.002)]. We found no strong evidence that the associations between 16 IGF pathway SNPs and prostate cancer differed by intakes of dietary protein.
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