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Sökning: WFRF:(Kwok F) > (2015-2019)

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  • Thomas, HS, et al. (författare)
  • 2019
  • swepub:Mat__t
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  • Cossarizza, A., et al. (författare)
  • Guidelines for the use of flow cytometry and cell sorting in immunological studies (second edition)
  • 2019
  • Ingår i: European Journal of Immunology. - : Wiley. - 0014-2980 .- 1521-4141. ; 49:10, s. 1457-1973
  • Tidskriftsartikel (refereegranskat)abstract
    • These guidelines are a consensus work of a considerable number of members of the immunology and flow cytometry community. They provide the theory and key practical aspects of flow cytometry enabling immunologists to avoid the common errors that often undermine immunological data. Notably, there are comprehensive sections of all major immune cell types with helpful Tables detailing phenotypes in murine and human cells. The latest flow cytometry techniques and applications are also described, featuring examples of the data that can be generated and, importantly, how the data can be analysed. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid, all written and peer-reviewed by leading experts in the field, making this an essential research companion.
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  • Chauhan, G., et al. (författare)
  • Genetic and lifestyle risk factors for MRI-defined brain infarcts in a population-based setting
  • 2019
  • Ingår i: Neurology. - : Ovid Technologies (Wolters Kluwer Health). - 0028-3878 .- 1526-632X. ; 92:5
  • Tidskriftsartikel (refereegranskat)abstract
    • ObjectiveTo explore genetic and lifestyle risk factors of MRI-defined brain infarcts (BI) in large population-based cohorts.MethodsWe performed meta-analyses of genome-wide association studies (GWAS) and examined associations of vascular risk factors and their genetic risk scores (GRS) with MRI-defined BI and a subset of BI, namely, small subcortical BI (SSBI), in 18 population-based cohorts (n = 20,949) from 5 ethnicities (3,726 with BI, 2,021 with SSBI). Top loci were followed up in 7 population-based cohorts (n = 6,862; 1,483 with BI, 630 with SBBI), and we tested associations with related phenotypes including ischemic stroke and pathologically defined BI.ResultsThe mean prevalence was 17.7% for BI and 10.5% for SSBI, steeply rising after age 65. Two loci showed genome-wide significant association with BI: FBN2, p = 1.77 x 10(-8); and LINC00539/ZDHHC20, p = 5.82 x 10(-9). Both have been associated with blood pressure (BP)-related phenotypes, but did not replicate in the smaller follow-up sample or show associations with related phenotypes. Age- and sex-adjusted associations with BI and SSBI were observed for BP traits (p value for BI, p([BI]) = 9.38 x 10(-25); p([SSBI]) = 5.23 x 10(-14) for hypertension), smoking (p([BI]) = 4.4 x 10(-10); p([SSBI]) = 1.2 x 10(-4)), diabetes (p([BI]) = 1.7 x 10(-8); p([SSBI]) = 2.8 x 10(-3)), previous cardiovascular disease (p([BI]) = 1.0 x 10(-18); p([SSBI]) = 2.3 x 10(-7)), stroke (p([BI]) = 3.9 x 10(-69); p([SSBI]) = 3.2 x 10(-24)), and MRI-defined white matter hyperintensity burden (p([BI]) = 1.43 x 10(-157); p([SSBI]) = 3.16 x 10(-106)), but not with body mass index or cholesterol. GRS of BP traits were associated with BI and SSBI (p 0.0022), without indication of directional pleiotropy.ConclusionIn this multiethnic GWAS meta-analysis, including over 20,000 population-based participants, we identified genetic risk loci for BI requiring validation once additional large datasets become available. High BP, including genetically determined, was the most significant modifiable, causal risk factor for BI.
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  • Brito-Zeron, P., et al. (författare)
  • How immunological profile drives clinical phenotype of primary Sjögren's syndrome at diagnosis : analysis of 10,500 patients (Sjögren Big Data Project)
  • 2018
  • Ingår i: Clinical and Experimental Rheumatology. - : CLINICAL & EXPER RHEUMATOLOGY. - 0392-856X .- 1593-098X. ; 36:3, s. S102-S112
  • Tidskriftsartikel (refereegranskat)abstract
    • Objective: To evaluate the influence of the main immunological markers on the disease phenotype at diagnosis in a large international cohort of patients with primary Sjogren's syndrome (SjS).Methods: The Big Data Sjogren Project Consortium is an international, multicentre registry created in 2014. As a first step, baseline clinical information from leading centres on clinical research in SjS of the 5 continents was collected. The centres shared a harmonised data architecture and conducted cooperative online efforts in order to refine collected data under the coordination of a big data statistical team. Inclusion criteria were the fulfillment of the 2002 classification criteria. Immunological tests were carried out using standard commercial assays.Results: By January 2018, the participant centres had included 10,500 valid patients from 22 countries. The cohort included 9,806 (93%) women and 694 (7%) men, with a mean age at diagnosis of primary SjS of 53 years, mainly White (78%) and included from European countries (71%). The frequency of positive immunological markers at diagnosis was 79.3% for ANA, 73.2% for anti-Ro, 48.6% for RF, 45.1% for anti-La, 13.4% for low C3 levels, 14.5% for low C4 levels and 7.3% for cryoglobulins. Positive autoantibodies (ANA, Ro, La) correlated with a positive result in salivary gland biopsy, while hypocomplementaemia and especially cryoglobulinaemia correlated with systemic activity (mean ESSDAI score of 17.7 for ctyoglobulins, 11.3 for low C3 and 9.2 for low C4, in comparison with 3.8 for negative markers). The immunological markers with a great number of statistically-significant associations (p<0.001) in the organ-by-organ ESSDAI evaluation were cryoglobulins (9 domains), low C3 (8 domains), anti-La (7 domains) and low C4 (6 domains).Conclusion: We confirm the strong influence of immunological markers on the phenotype of primary SjS at diagnosis in the largest multi-ethnic international cohort ever analysed, with a greater influence for cryoglobulinaemic-related markers in comparison with Ro/La autoantibodies and ANA. Immunological patterns play a central role in the phenotypic expression of the disease already at the time of diagnosis, and may guide physicians to design a specific personalised management during the follow-up of patients with primary SjS.
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