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Träfflista för sökning "WFRF:(Houlston Richard S) srt2:(2020)"

Sökning: WFRF:(Houlston Richard S) > (2020)

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1.
  • Ostrom, Quinn T., et al. (författare)
  • Glioma risk associated with extent of estimated European genetic ancestry in African Americans and Hispanics
  • 2020
  • Ingår i: International Journal of Cancer. - John Wiley & Sons. - 0020-7136 .- 1097-0215. ; 146:3, s. 739-748
  • Tidskriftsartikel (refereegranskat)abstract
    • <p>Glioma incidence is highest in non-Hispanic Whites, and to date, glioma genome-wide association studies (GWAS) to date have only included European ancestry (EA) populations. African Americans and Hispanics in the US have varying proportions of EA, African (AA) and Native American ancestries (NAA). It is unknown if identified GWAS loci or increased EA is associated with increased glioma risk. We assessed whether EA was associated with glioma in African Americans and Hispanics. Data were obtained for 832 cases and 675 controls from the Glioma International Case-Control Study and GliomaSE Case-Control Study previously estimated to have &lt;80% EA, or self-identify as non-White. We estimated global and local ancestry using fastStructure and RFMix, respectively, using 1,000 genomes project reference populations. Within groups with &gt;= 40% AA (AFR(&gt;= 0.4)), and &gt;= 15% NAA (AMR(&gt;= 0.15)), genome-wide association between local EA and glioma was evaluated using logistic regression conditioned on global EA for all gliomas. We identified two regions (7q21.11, p = 6.36 x 10(-4); 11p11.12, p = 7.0 x 10-4) associated with increased EA, and one associated with decreased EA (20p12.13, p = 0.0026) in AFR(&gt;= 0.4). In addition, we identified a peak at rs1620291 (p = 4.36 x 10(-6)) in 7q21.3. Among AMR(&gt;= 0.15), we found an association between increased EA in one region (12q24.21, p = 8.38 x 10(-4)), and decreased EA in two regions (8q24.21, p = 0. 0010; 20q13.33, p = 6.36 x 10(-4)). No other significant associations were identified. This analysis identified an association between glioma and two regions previously identified in EA populations (8q24.21, 20q13.33) and four novel regions (7q21.11, 11p11.12, 12q24.21 and 20p12.13). The identifications of novel association with EA suggest regions to target for future genetic association studies. What's new? Glioma is rare in non-White populations, and most glioma genome-wide association studies have included only primarily European ancestry populations. Here, the authors assess whether variation in European ancestry is associated with glioma risk in populations with a combination of European, African and Native American ancestry. Based on African American and Hispanic cases from two large glioma case-control studies, this analysis shows that increased European ancestry in admixed populations may be associated with increased glioma risk. The associations between glioma and two chromosomal regions previously identified in European ancestry populations, and four novel regions, may guide future studies.</p>
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2.
  • Saunders, Charlie N., et al. (författare)
  • Lack of association between modifiable exposures and glioma risk a Mendelian randomization analysis
  • 2020
  • Ingår i: Neuro-Oncology. - OXFORD UNIV PRESS INC. - 1522-8517 .- 1523-5866. ; 22:2, s. 207-215
  • Forskningsöversikt (refereegranskat)abstract
    • <p>Background. The etiological basis of glioma is poorly understood. We have used genetic markers in a Mendelian randomization (MR) framework to examine if lifestyle, cardiometabolic, and inflammatory factors influence the risk of glioma. This methodology reduces bias from confounding and is not affected by reverse causation. Methods. We identified genetic instruments for 37 potentially modifiable risk factors and evaluated their association with glioma risk using data from a genome-wide association study of 12488 glioma patients and 18169 controls. We used the estimated odds ratio of glioma associated with each of the genetically defined traits to infer evidence for a causal relationship with the following exposures: Lifestyle and dietary factors-height, plasma insulin-like growth factor 1, blood carnitine, blood methionine, blood selenium, blood zinc, circulating adiponectin, circulating carotenoids, iron status, serum calcium, vitamins (A1, B12, B6, E, and 25-hydroxyvitamin D), fatty acid levels (monounsaturated, omega-3, and omega-6) and circulating fetuin-A; Cardiometabolic factors-birth weight, high density lipoprotein cholesterol, low density lipoprotein cholesterol, total cholesterol, total triglycerides, basal metabolic rate, body fat percentage, body mass index, fasting glucose, fasting proinsulin, glycated hemoglobin levels, diastolic and systolic blood pressure, waist circumference, waist-to-hip ratio; and Inflammatory factors- C-reactive protein, plasma interleukin-6 receptor subunit alpha and serum immunoglobulin E. Results. After correction for the testing of multiple potential risk factors and excluding associations driven by one single nucleotide polymorphism, no significant association with glioma risk was observed (ie, P-Corrected &gt; 0.05). Conclusions. This study did not provide evidence supporting any of the 37 factors examined as having a significant influence on glioma risk.</p>
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3.
  • Feng, Helian, et al. (författare)
  • Cross-cancer cross-tissue Transcriptome-wide Association Study (TWAS) of 11 cancers identifies 56 novel genes
  • 2020
  • Ingår i: Genetic Epidemiology. - John Wiley & Sons. - 0741-0395 .- 1098-2272. ; 44:5, s. 481-481
  • Tidskriftsartikel (övrigt vetenskapligt)abstract
    • <p>Though heterogeneous, multiple tumor types share hallmark mechanisms. Thus, identifying genes associated with multiple cancer types may shed light on general oncogenic mechanisms and identify genes missed in single‐cancer analyses. TWAS have been successful in testing whether genetically‐predicted tissue‐specific gene expression is associated with cancer risk. Although cross‐cancer genome‐wide association studies (GWAS) analyses have been performed previously, no cross‐cancer TWAS has been conducted to date. Here, we implement a pipeline to perform cross‐cancer, cross‐tissue TWAS analysis. We use newly‐developed multi‐trait TWAS test statistics to integrate the TWAS results for association between 11 separated cancers and predicted gene expression in 43 GTEx tissues, including a “sum” test and a “variance components” test, analogous to fixed‐ and random‐effects meta‐analyses. We then integrated the results across different tissues using the Aggregated Cauchy Association Test (ACAT) combined test.</p><p>A total of 403 genes were significantly associated with at least one cancer type for at least one tissue; 96 additional genes were identified when combining test results across cancers; and 35 additional genes when further combining test results across tissue. Among these significant genes, 70 were not near previously‐published GWAS index variants. 14 of the 70 novel genes were identified from the single‐cancer single‐tissue test; an additional 43 were identified with the cross‐cancer test; and another 13 were identified when further combined across tissues. The newly identified genes, including <em>RBBP8 </em>and <em>TP53BP </em>, are involved in chromatin structure, tumorigenesis, apoptosis, transcriptional regulation, DNA repair, immune system, oxidative damage and cell‐cycle, proliferation, progression, shape, structure, and migration.</p>
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4.
  • Went, Molly, et al. (författare)
  • Search for multiple myeloma risk factors using Mendelian randomization
  • 2020
  • Ingår i: Blood Advances. - American Society of Hematology. - 2473-9529. ; 4:10, s. 2172-2179
  • Tidskriftsartikel (refereegranskat)abstract
    • The etiology of multiple myeloma (MM) is poorly understood. Summary data from genome-wide association studies (GWASs) of multiple phenotypes can be exploited in a Mendelian randomization (MR) phenome-wide association study (PheWAS) to search for factors influencing MM risk. We performed an MR-PheWAS analyzing 249 phenotypes, proxied by 10 225 genetic variants, and summary genetic data from a GWAS of 7717 MM cases and 29 304 controls. Odds ratios (ORs) per 1 standard deviation increase in each phenotype were estimated under an inverse variance weighted random effects model. A Bonferroni-corrected threshold of P 5 2 3 1024 was considered significant, whereas P,.05 was considered suggestive of an association. Although no significant associations with MM risk were observed among the 249 phenotypes, 28 phenotypes showed evidence suggestive of association, including increased levels of serum vitamin B6 and blood carnitine (P 5 1.1 3 1023) with greater MM risk and v-3 fatty acids (P 5 5.4 3 1024) with reduced MM risk. A suggestive association between increased telomere length and reduced MM risk was also noted; however, this association was primarily driven by the previously identified risk variant rs10936599 at 3q26 (TERC). Although not statistically significant, increased body mass index was associated with increased risk (OR, 1.10; 95% confidence interval, 0.99-1.22), supporting findings from a previous meta-analysis of prospective observational studies. Our study did not provide evidence supporting any modifiable factors examined as having a major influence on MM risk; however, it provides insight into factors for which the evidence has previously been mixed.
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