BACKGROUNDThere is considerable variation in disease behavior among patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 . Genomewide association analysis may allow for the identification of potential genetic factors involved in the development of Covid-19. METHODSWe conducted a genomewide association study involving 1980 patients with Covid-19 and severe disease (defined as respiratory failure) at seven hospitals in the Italian and Spanish epicenters of the SARS-CoV-2 pandemic in Europe. After quality control and the exclusion of population outliers, 835 patients and 1255 control participants from Italy and 775 patients and 950 control participants from Spain were included in the final analysis. In total, we analyzed 8,582,968 single-nucleotide polymorphisms and conducted a meta-analysis of the two case-control panels. RESULTSWe detected cross-replicating associations with rs11385942 at locus 3p21.31 and with rs657152 at locus 9q34.2, which were significant at the genomewide level (P<5×10 −8 ) in the meta-analysis of the two case-control panels (odds ratio, 1.77; 95% confidence interval [CI], 1.48 to 2.11; P = 1.15×10 −10 ; and odds ratio, 1.32; 95% CI, 1.20 to 1.47; P = 4.95×10 −8 , respectively). At locus 3p21.31, the association signal spanned the genes SLC6A20, LZTFL1, CCR9, FYCO1, CXCR6 and XCR1. The association signal at locus 9q34.2 coincided with the ABO blood group locus; in this cohort, a blood-group-specific analysis showed a higher risk in blood group A than in other blood groups (odds ratio, 1.45; 95% CI, 1.20 to 1.75; P = 1.48×10 −4 ) and a protective effect in blood group O as compared with other blood groups (odds ratio, 0.65; 95% CI, 0.53 to 0.79; P = 1.06×10 −5 ). CONCLUSIONSWe identified a 3p21.31 gene cluster as a genetic susceptibility locus in patients with Covid-19 with respiratory failure and confirmed a potential involvement of the ABO blood-group system. (Funded by Stein Erik Hagen and others.
Dimethyl fumarate is a cytoprotective and immunomodulatory drug used in the treatment of multiple sclerosis. We performed a bibliometric study examining the characteristics and trends of the top 100 cited articles that include dimethyl fumarate in the title. On 21 September 2020 we carried out an electronic search in the Web of Science (WOS), seeking articles that include the following terms within the title: dimethyl fumarate, BG-12, or Tecfidera. To focus our investigation on original research, we refined the search to include only articles, early access, others, case report, and clinical trials. We obtained a total of 1115 items, which were cited 7169 times, had a citation density of 6.43 citations/item, and an h-index of 40. Around 2010, there was a jump in the number of published articles per year, rising from 5 articles/year up to 12 articles/year. We sorted all the items by the number of citations and selected the top 100 most cited (T100). The T100 had 4164 citations, with a density of 37 citations/year and contained 16 classic research articles. They were published between 1961 and 2018; the years 2010–2018 amassed nearly 80% of the T100. We noted 17 research areas with articles in the T100. Of these, the number one ranking went to neurosciences/neurology with 39 articles, and chemistry ranked second on the T100 list with 14 items. We noticed that the percentage of articles belonging to different journals changed depending on the time period. Chemistry held the highest number of papers during 1961–2000, while pharmacology andneurosciences/neurology led the 2001–2018 interval. A total of 478 authors from 145 institutions and 25 countries were included in the T100 ranking. The paper by Gold R et al. was the most successful with 14 articles, 1.823 citations and a density of 140.23 citations/year. The biotechnological company Biogen led the T100 list with 20 articles. With 59 published articles, the USA was the leading country in publications. We concluded that this study analyzed the use of and research on dimethyl fumarate from a different perspective, which will allow the readership (expert or not) to understand the relevance of classic and recent literature on this topic.
Objectives The aim of this study was to harmonize the criteria for the Bhattacharya indirect method Microsoft Excel Spreadsheet for reference intervals calculation to reduce between-user variability and use these criteria to calculate and evaluate reference intervals for eight analytes in two different years. Methods Anonymized laboratory test results from outpatients were extracted from January 1st 2018 to December 31st 2019. To assure data quality, we examined the monthly results from an external quality control program. Reference intervals were determined by the Bhattacharya method with the St Vincent’s hospital Spreadsheet firstly using original criteria and then using additional harmonized criteria defined in this study. Consensus reference intervals using the additional harmonized criteria were calculated as the mean of four users’ lower and upper reference interval results. To further test the operation criteria and robustness of the obtained reference intervals, an external user validated the Spreadsheet procedure. Results The extracted test results for all selected laboratory tests fulfilled the quality criteria and were included in the present study. Differences between users in calculated reference intervals were frequent when using the Spreadsheet. Therefore, additional criteria for the Spreadsheet were proposed and applied by independent users, such as: to set central bin as the mean of all the data, bin size as small as possible, at least three consecutive bins and a high proportion of bins within the curve. Conclusions The proposed criteria contributed to the harmonization of reference interval calculation between users of the Bhattacharya indirect method Spreadsheet.
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