SwePub
Tyck till om SwePub Sök här!
Sök i SwePub databas

  Utökad sökning

Träfflista för sökning "WFRF:(Walsh Christine) srt2:(2019)"

Sökning: WFRF:(Walsh Christine) > (2019)

  • Resultat 1-3 av 3
Sortera/gruppera träfflistan
   
NumreringReferensOmslagsbildHitta
1.
  • 2019
  • Tidskriftsartikel (refereegranskat)
  •  
2.
  • Fresard, Laure, et al. (författare)
  • Identification of rare-disease genes using blood transcriptome sequencing and large control cohorts
  • 2019
  • Ingår i: Nature Medicine. - : NATURE PUBLISHING GROUP. - 1078-8956 .- 1546-170X. ; 25:6, s. 911-919
  • Tidskriftsartikel (refereegranskat)abstract
    • It is estimated that 350 million individuals worldwide suffer from rare diseases, which are predominantly caused by mutation in a single gene(1). The current molecular diagnostic rate is estimated at 50%, with whole-exome sequencing (WES) among the most successful approaches(2-5). For patients in whom WES is uninformative, RNA sequencing (RNA-seq) has shown diagnostic utility in specific tissues and diseases(6-8). This includes muscle biopsies from patients with undiagnosed rare muscle disorders(6,9), and cultured fibroblasts from patients with mitochondrial disorders(7). However, for many individuals, biopsies are not performed for clinical care, and tissues are difficult to access. We sought to assess the utility of RNA-seq from blood as a diagnostic tool for rare diseases of different pathophysiologies. We generated whole-blood RNA-seq from 94 individuals with undiagnosed rare diseases spanning 16 diverse disease categories. We developed a robust approach to compare data from these individuals with large sets of RNA-seq data for controls (n = 1,594 unrelated controls and n = 49 family members) and demonstrated the impacts of expression, splicing, gene and variant filtering strategies on disease gene identification. Across our cohort, we observed that RNA-seq yields a 7.5% diagnostic rate, and an additional 16.7% with improved candidate gene resolution.
  •  
3.
  • Walsh, Naomi, et al. (författare)
  • Agnostic Pathway/Gene Set Analysis of Genome-Wide Association Data Identifies Associations for Pancreatic Cancer
  • 2019
  • Ingår i: Journal of the National Cancer Institute. - : Oxford University Press. - 0027-8874 .- 1460-2105. ; 111:6
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Genome-wide association studies (GWAS) identify associations of individual single-nucleotide polymorphisms (SNPs) with cancer risk but usually only explain a fraction of the inherited variability. Pathway analysis of genetic variants is a powerful tool to identify networks of susceptibility genes.Methods: We conducted a large agnostic pathway-based meta-analysis of GWAS data using the summary-based adaptive rank truncated product method to identify gene sets and pathways associated with pancreatic ductal adenocarcinoma (PDAC) in 9040 cases and 12 496 controls. We performed expression quantitative trait loci (eQTL) analysis and functional annotation of the top SNPs in genes contributing to the top associated pathways and gene sets. All statistical tests were two-sided.Results: We identified 14 pathways and gene sets associated with PDAC at a false discovery rate of less than 0.05. After Bonferroni correction (P ≤ 1.3 × 10-5), the strongest associations were detected in five pathways and gene sets, including maturity-onset diabetes of the young, regulation of beta-cell development, role of epidermal growth factor (EGF) receptor transactivation by G protein-coupled receptors in cardiac hypertrophy pathways, and the Nikolsky breast cancer chr17q11-q21 amplicon and Pujana ATM Pearson correlation coefficient (PCC) network gene sets. We identified and validated rs876493 and three correlating SNPs (PGAP3) and rs3124737 (CASP7) from the Pujana ATM PCC gene set as eQTLs in two normal derived pancreas tissue datasets.Conclusion: Our agnostic pathway and gene set analysis integrated with functional annotation and eQTL analysis provides insight into genes and pathways that may be biologically relevant for risk of PDAC, including those not previously identified.
  •  
Skapa referenser, mejla, bekava och länka
  • Resultat 1-3 av 3
Typ av publikation
tidskriftsartikel (3)
Typ av innehåll
refereegranskat (3)
Författare/redaktör
Kelly, Daniel (1)
Bengtsson-Palme, Joh ... (1)
Nilsson, Henrik (1)
Boutron-Ruault, Mari ... (1)
Wareham, Nick (1)
Kelly, Ryan (1)
visa fler...
Li, Ying (1)
Moore, Matthew D. (1)
Mannisto, Satu (1)
Liu, Fang (1)
Zhang, Yao (1)
Jin, Yi (1)
Raza, Ali (1)
Rafiq, Muhammad (1)
Zhang, Kai (1)
Khatlani, T (1)
Kahan, Thomas (1)
Lind, Lars (1)
Sörelius, Karl, 1981 ... (1)
Weiderpass, Elisabet ... (1)
Berndt, Sonja I (1)
Batra, Jyotsna (1)
Albanes, Demetrius (1)
Giles, Graham G (1)
Roobol, Monique J (1)
Backman, Lars (1)
Sund, Malin (1)
Yan, Hong (1)
Lorkowski, Stefan (1)
Thrift, Amanda G. (1)
Zhang, Wei (1)
Hammerschmidt, Sven (1)
Patil, Chandrashekha ... (1)
Gallinger, Steven (1)
Visvanathan, Kala (1)
Wang, Jun (1)
White, Emily (1)
Peters, Ulrike (1)
Severi, Gianluca (1)
Bueno-de-Mesquita, B ... (1)
Pollesello, Piero (1)
Canzian, Federico (1)
Conesa, Ana (1)
Battle, Alexis (1)
Montgomery, Stephen ... (1)
El-Esawi, Mohamed A. (1)
Zhang, Weijia (1)
Milne, Roger L. (1)
Patel, Alpa, V (1)
Zheng, Wei (1)
visa färre...
Lärosäte
Uppsala universitet (2)
Karolinska Institutet (2)
Göteborgs universitet (1)
Umeå universitet (1)
Högskolan i Halmstad (1)
Stockholms universitet (1)
visa fler...
Lunds universitet (1)
Chalmers tekniska högskola (1)
visa färre...
Språk
Engelska (3)
Forskningsämne (UKÄ/SCB)
Medicin och hälsovetenskap (3)
Naturvetenskap (1)
År
2019 (3)Ta bort avgränsningen

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Stäng

Kopiera och spara länken för att återkomma till aktuell vy