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Träfflista för sökning "WFRF:(Eckel Passow Jeanette E.) ;pers:(Yeager Meredith)"

Search: WFRF:(Eckel Passow Jeanette E.) > Yeager Meredith

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1.
  • Johansson, Mattias, et al. (author)
  • The influence of obesity-related factors in the etiology of renal cell carcinoma—A mendelian randomization study
  • 2019
  • In: PLoS Medicine. - : Public Library of Science (PLoS). - 1549-1277 .- 1549-1676. ; 16:1
  • Journal article (peer-reviewed)abstract
    • Background: Several obesity-related factors have been associated with renal cell carcinoma (RCC), but it is unclear which individual factors directly influence risk. We addressed this question using genetic markers as proxies for putative risk factors and evaluated their relation to RCC risk in a mendelian randomization (MR) framework. This methodology limits bias due to confounding and is not affected by reverse causation.Methods and findings: Genetic markers associated with obesity measures, blood pressure, lipids, type 2 diabetes, insulin, and glucose were initially identified as instrumental variables, and their association with RCC risk was subsequently evaluated in a genome-wide association study (GWAS) of 10,784 RCC patients and 20,406 control participants in a 2-sample MR framework. The effect on RCC risk was estimated by calculating odds ratios (ORSD) for a standard deviation (SD) increment in each risk factor. The MR analysis indicated that higher body mass index increases the risk of RCC (ORSD: 1.56, 95% confidence interval [CI] 1.44–1.70), with comparable results for waist-to-hip ratio (ORSD: 1.63, 95% CI 1.40–1.90) and body fat percentage (ORSD: 1.66, 95% CI 1.44–1.90). This analysis further indicated that higher fasting insulin (ORSD: 1.82, 95% CI 1.30–2.55) and diastolic blood pressure (DBP; ORSD: 1.28, 95% CI 1.11–1.47), but not systolic blood pressure (ORSD: 0.98, 95% CI 0.84–1.14), increase the risk for RCC. No association with RCC risk was seen for lipids, overall type 2 diabetes, or fasting glucose.Conclusions: This study provides novel evidence for an etiological role of insulin in RCC, as well as confirmatory evidence that obesity and DBP influence RCC risk.
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2.
  • Scelo, Ghislaine, et al. (author)
  • Genome-wide association study identifies multiple risk loci for renal cell carcinoma.
  • 2017
  • In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 8
  • Journal article (peer-reviewed)abstract
    • Previous genome-wide association studies (GWAS) have identified six risk loci for renal cell carcinoma (RCC). We conducted a meta-analysis of two new scans of 5,198 cases and 7,331 controls together with four existing scans, totalling 10,784 cases and 20,406 controls of European ancestry. Twenty-four loci were tested in an additional 3,182 cases and 6,301 controls. We confirm the six known RCC risk loci and identify seven new loci at 1p32.3 (rs4381241, P=3.1 × 10-10), 3p22.1 (rs67311347, P=2.5 × 10-8), 3q26.2 (rs10936602, P=8.8 × 10-9), 8p21.3 (rs2241261, P=5.8 × 10-9), 10q24.33-q25.1 (rs11813268, P=3.9 × 10-8), 11q22.3 (rs74911261, P=2.1 × 10-10) and 14q24.2 (rs4903064, P=2.2 × 10-24). Expression quantitative trait analyses suggest plausible candidate genes at these regions that may contribute to RCC susceptibility.
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3.
  • Ostrom, Quinn T., et al. (author)
  • Sex-specific glioma genome-wide association study identifies new risk locus at 3p21.31 in females, and finds sex-differences in risk at 8q24.21
  • 2018
  • In: Scientific Reports. - : NATURE PUBLISHING GROUP. - 2045-2322. ; 8
  • Journal article (peer-reviewed)abstract
    • Incidence of glioma is approximately 50% higher in males. Previous analyses have examined exposures related to sex hormones in women as potential protective factors for these tumors, with inconsistent results. Previous glioma genome-wide association studies (GWAS) have not stratified by sex. Potential sex-specific genetic effects were assessed in autosomal SNPs and sex chromosome variants for all glioma, GBM and non-GBM patients using data from four previous glioma GWAS. Datasets were analyzed using sex-stratified logistic regression models and combined using meta-analysis. There were 4,831 male cases, 5,216 male controls, 3,206 female cases and 5,470 female controls. A significant association was detected at rs11979158 (7p11.2) in males only. Association at rs55705857 (8q24.21) was stronger in females than in males. A large region on 3p21.31 was identified with significant association in females only. The identified differences in effect of risk variants do not fully explain the observed incidence difference in glioma by sex.
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4.
  • Melin, Beatrice S., et al. (author)
  • Genome-wide association study of glioma subtypes identifies specific differences in genetic susceptibility to glioblastoma and non-glioblastoma tumors
  • 2017
  • In: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 49:5, s. 789-794
  • Journal article (peer-reviewed)abstract
    • Genome-wide association studies (GWAS) have transformed our understanding of glioma susceptibility, but individual studies have had limited power to identify risk loci. We performed a meta-analysis of existing GWAS and two new GWAS, which totaled 12,496 cases and 18,190 controls. We identified five new loci for glioblastoma (GBM) at 1p31.3 (rs12752552; P = 2.04 x 10(-9), odds ratio (OR) = 1.22), 11q14.1 (rs11233250; P = 9.95 x 10(-10), OR = 1.24), 16p13.3 (rs2562152; P = 1.93 x 10-8, OR = 1.21), 16q12.1 (rs10852606; P = 1.29 x 10(-11), OR = 1.18) and 22q13.1 (rs2235573; P = 1.76 x 10(-10), OR = 1.15), as well as eight loci for non-GBM tumors at 1q32.1 (rs4252707; P = 3.34 x 10(-9), OR = 1.19), 1q44 (rs12076373; P = 2.63 x 10(-10), OR = 1.23), 2q33.3 (rs7572263; P = 2.18 x 10(-10), OR = 1.20), 3p14.1 (rs11706832; P = 7.66 x 10(-9), OR = 1.15), 10q24.33 (rs11598018; P = 3.39 x 10-8, OR = 1.14), 11q21 (rs7107785; P = 3.87 x 10(-10), OR = 1.16), 14q12 (rs10131032; P = 5.07 x 10(-11), OR = 1.33) and 16p13.3 (rs3751667; P = 2.61 x 10(-9), OR = 1.18). These data substantiate that genetic susceptibility to GBM and non-GBM tumors are highly distinct, which likely reflects different etiology.
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5.
  • Ostrom, Quinn T., et al. (author)
  • Age‐specific genome‐wide association study in glioblastoma identifies increased proportion of 'lower grade glioma'‐like features associated with younger age
  • 2018
  • In: International Journal of Cancer. - : WILEY. - 0020-7136 .- 1097-0215. ; 143:10, s. 2359-2366
  • Journal article (peer-reviewed)abstract
    • Glioblastoma (GBM) is the most common malignant brain tumor in the United States. Incidence of GBM increases with age, and younger age‐at‐diagnosis is significantly associated with improved prognosis. While the relationship between candidate GBM risk SNPs and age‐at‐diagnosis has been explored, genome‐wide association studies (GWAS) have not previously been stratified by age. Potential age‐specific genetic effects were assessed in autosomal SNPs for GBM patients using data from four previous GWAS. Using age distribution tertiles (18–53, 54–64, 65+) datasets were analyzed using age‐stratified logistic regression to generate p values, odds ratios (OR), and 95% confidence intervals (95%CI), and then combined using meta‐analysis. There were 4,512 total GBM cases, and 10,582 controls used for analysis. Significant associations were detected at two previously identified SNPs in 7p11.2 (rs723527 [p54–63 = 1.50x10−9, OR54–63 = 1.28, 95%CI54–63 = 1.18–1.39; p64+ = 2.14x10−11, OR64+ = 1.32, 95%CI64+ = 1.21–1.43] and rs11979158 [p54–63 = 6.13x10−8, OR54–63 = 1.35, 95%CI54–63 = 1.21–1.50; p64+ = 2.18x10−10, OR64+ = 1.42, 95%CI64+ = 1.27–1.58]) but only in persons >54. There was also a significant association at the previously identified lower grade glioma (LGG) risk locus at 8q24.21 (rs55705857) in persons ages 18–53 (p18–53 = 9.30 × 10−11, OR18–53 = 1.76, 95%CI18–53 = 1.49–2.10). Within The Cancer Genome Atlas (TCGA) there was higher prevalence of ‘LGG’‐like tumor characteristics in GBM samples in those 18–53, with IDH1/2 mutation frequency of 15%, as compared to 2.1% [54–63] and 0.8% [64+] (p = 0.0005). Age‐specific differences in cancer susceptibility can provide important clues to etiology. The association of a SNP known to confer risk for IDH1/2 mutant glioma and higher prevalence of IDH1/2 mutation within younger individuals 18–53 suggests that more younger individuals may present initially with ‘secondary glioblastoma.’
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