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- Thomas, HS, et al.
(author)
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- 2019
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swepub:Mat__t
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- 2019
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Journal article (peer-reviewed)
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- Fresard, Laure, et al.
(author)
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Identification of rare-disease genes using blood transcriptome sequencing and large control cohorts
- 2019
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In: Nature Medicine. - : NATURE PUBLISHING GROUP. - 1078-8956 .- 1546-170X. ; 25:6, s. 911-919
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Journal article (peer-reviewed)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.
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- Laskar, Ruhina S, et al.
(author)
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Sex specific associations in genome wide association analysis of renal cell carcinoma.
- 2019
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In: European Journal of Human Genetics. - : Springer Science and Business Media LLC. - 1018-4813 .- 1476-5438. ; 27:10, s. 1589-1598
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Journal article (peer-reviewed)abstract
- Renal cell carcinoma (RCC) has an undisputed genetic component and a stable 2:1 male to female sex ratio in its incidence across populations, suggesting possible sexual dimorphism in its genetic susceptibility. We conducted the first sex-specific genome-wide association analysis of RCC for men (3227 cases, 4916 controls) and women (1992 cases, 3095 controls) of European ancestry from two RCC genome-wide scans and replicated the top findings using an additional series of men (2261 cases, 5852 controls) and women (1399 cases, 1575 controls) from two independent cohorts of European origin. Our study confirmed sex-specific associations for two known RCC risk loci at 14q24.2 (DPF3) and 2p21(EPAS1). We also identified two additional suggestive male-specific loci at 6q24.3 (SAMD5, male odds ratio (ORmale) = 0.83 [95% CI = 0.78-0.89], Pmale = 1.71 × 10-8 compared with female odds ratio (ORfemale) = 0.98 [95% CI = 0.90-1.07], Pfemale = 0.68) and 12q23.3 (intergenic, ORmale = 0.75 [95% CI = 0.68-0.83], Pmale = 1.59 × 10-8 compared with ORfemale = 0.93 [95% CI = 0.82-1.06], Pfemale = 0.21) that attained genome-wide significance in the joint meta-analysis. Herein, we provide evidence of sex-specific associations in RCC genetic susceptibility and advocate the necessity of larger genetic and genomic studies to unravel the endogenous causes of sex bias in sexually dimorphic traits and diseases like RCC.
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- Juszczak, Edmund, et al.
(author)
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Introducing the CONsolidated Standards of Reporting Trials (CONSORT) statement for randomised controlled trials (RCTs) using cohorts and routinely collected health data
- 2019
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In: Trials. - : BMC. - 1745-6215. ; 20:Suppl. 1, s. 131-131
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Journal article (other academic/artistic)abstract
- Background: Randomised controlled trials (RCTs) are increasingly being conducted using existing sources of data, such as cohorts, administrative databases, disease registries and electronic health records. RCTs conducted using existing data sources require additional information to be reported. This reporting guideline is an extension of the 2010 version of the Consolidated Standards of Reporting Trials (CONSORT) Statement for RCTs using cohorts and routinely collected health data.Methods: A long-list of potential items for the checklist was identified through two methods: firstly, modifications to the current CONSORT checklist were generated using existing reporting guidelines, including the Reporting of Observational Studies in Epidemiology (STROBE) and REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) statements. Secondly, ascoping review of RCTs conducted in the last decade using cohorts and routinely collected health data facilitated the modification and identification of other potential items. Using the long-list, a three-stage Delphi exercise was conducted to assess the importance of each item for inclusion in the final extension checklist, which was finalised at a face-to-face meeting of experts.Results: A long-list of 27 items was created and 125 experts registered for the three-round Delphi exercise (92, 77 and 62 experts participated in each round respectively). Consensus was reached on 21 out of 27 items. The results of the Delphi exercise informed a face-to-face consensus meeting in May 2019; core items to be included in the extension checklist were finalised at this meeting. Corresponding explanations of extensions and new items with examples of good reporting were developed subsequently.Conclusion: The guideline checklist can facilitate transparent reporting of RCTs using cohorts and routinely collected health data, to assist evaluations of rigour and reproducibility, enhance understanding of the methodology, and make the results more useful for clinicians, journal editors, reviewers, guideline authors, and funders.
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