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- Dand, Nick, et al.
(författare)
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Exome-wide association study reveals novel psoriasis susceptibility locus at TNFSF15 and rare protective alleles in genes contributing to type I IFN signalling
- 2017
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Ingår i: Human Molecular Genetics. - : OXFORD UNIV PRESS. - 0964-6906 .- 1460-2083. ; 26:21, s. 4301-4313
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Tidskriftsartikel (refereegranskat)abstract
- Psoriasis is a common inflammatory skin disorder for which multiple genetic susceptibility loci have been identified, but few resolved to specific functional variants. In this study, we sought to identify common and rare psoriasis-associated gene-centric variation. Using exome arrays we genotyped four independent cohorts, totalling 11 861 psoriasis cases and 28 610 controls, aggregating the dataset through statistical meta-analysis. Single variant analysis detected a previously unreported risk locus at TNFSF15 (rs6478108; P = 1.50 x 10(-8), OR = 1.10), and association of common protein-altering variants at 11 loci previously implicated in psoriasis susceptibility. We validate previous reports of protective low-frequency protein-altering variants within IFIH1 (encoding an innate antiviral receptor) and TYK2 (encoding a Janus kinase), in each case establishing a further series of protective rare variants (minor allele frequency amp;lt; 0.01) via gene-wide aggregation testing (IFIH1: p(burden) = 2.53 x 10(-7), OR = 0.707; TYK2: p(burden) = 6.17 x 10(-4), OR = 0.744). Both genes play significant roles in type I interferon (IFN) production and signalling. Several of the protective rare and low-frequency variants in IFIH1 and TYK2 disrupt conserved protein domains, highlighting potential mechanisms through which their effect may be exerted.
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- Norris, Jessica Voorhees, et al.
(författare)
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Acoustic differential extraction for forensic analysis of sexual assault evidence.
- 2009
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Ingår i: Analytical Chemistry. - : American Chemical Society (ACS). - 1520-6882 .- 0003-2700. ; 81:15, s. 6089-6095
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Tidskriftsartikel (refereegranskat)abstract
- Forensic DNA analysis of samples obtained from sexual assault evidence relies on separation of male and female components of the recovered genetic material. The conventional separation method used by crime laboratories, differential extraction (DE), is one of the most time-consuming sample preparation steps, requires extensive sample handling, is difficult to automate, and often results in inefficient separation of female DNA from the male sample components. To circumvent conventional DE, acoustic differential extraction (ADE) analysis was developed on a microfluidic device. The ADE method relies on acoustic trapping of sperm cells in the presence of epithelial cell lysate (which is unretained), and laminar flow valving to direct the male and female fractions to separate outlets. Following the separation of sperm from epithelial cell lysate, DNA extraction, quantitation, amplification, and separation were performed using conventional laboratory methods. The results show that highly purified male and female fractions can be obtained with the ADE microdevice from mock sexual assault samples in 14 min. ADE analysis provides the potential to significantly alter the means by which sexual assault evidence is processed in crime laboratories.
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- Patrick, Matthew T., et al.
(författare)
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Genetic signature to provide robust risk assessment of psoriatic arthritis development in psoriasis patients
- 2018
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Ingår i: Nature Communications. - : NATURE PUBLISHING GROUP. - 2041-1723. ; 9
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Tidskriftsartikel (refereegranskat)abstract
- Psoriatic arthritis (PsA) is a complex chronic musculoskeletal condition that occurs in similar to 30% of psoriasis patients. Currently, no systematic strategy is available that utilizes the differences in genetic architecture between PsA and cutaneous-only psoriasis (PsC) to assess PsA risk before symptoms appear. Here, we introduce a computational pipeline for predicting PsA among psoriasis patients using data from six cohorts with amp;gt;7000 genotyped PsA and PsC patients. We identify 9 new loci for psoriasis or its subtypes and achieve 0.82 area under the receiver operator curve in distinguishing PsA vs. PsC when using 200 genetic markers. Among the top 5% of our PsA prediction we achieve amp;gt;90% precision with 100% specificity and 16% recall for predicting PsA among psoriatic patients, using conditional inference forest or shrinkage discriminant analysis. Combining statistical and machine-learning techniques, we show that the underlying genetic differences between psoriasis subtypes can be used for individualized subtype risk assessment.
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