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| 12. |
- Naumov, V., et al.
(författare)
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COVIDomic: A multi-modal cloud-based platform for identification of risk factors associated with COVID-19 severity
- 2021
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Ingår i: Plos Computational Biology. - : Public Library of Science (PLoS). - 1553-734X .- 1553-7358. ; 17:7
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Tidskriftsartikel (refereegranskat)abstract
- Author summary This article introduces COVIDomic, a new integrative multi-omics online platform designed to facilitate the analysis of the large amount of health data collected from COVID-19 patients. The COVIDomic platform includes a user-friendly interface and provides a set of bioinformatics tools for the analysis of multi-modal metatranscriptomic data to determine the origin of the coronavirus strain and the expected severity of the disease. An analytical workflow includes microbial pathogens community analysis, COVID-19 genetic epidemiology and patient stratification. These features allow studying the presence of common microbial organisms, their antibiotic resistance and the severity of the infection, as well as obtaining insights on the geographical locations from which the strain could have originated. Such openly distributed multi-modal platform will greatly accelerate the ongoing COVID-19 research and improve our readiness to respond to other infectious outbreaks. Coronavirus disease 2019 (COVID-19) is an acute infection of the respiratory tract that emerged in December 2019 in Wuhan, China. It was quickly established that both the symptoms and the disease severity may vary from one case to another and several strains of SARS-CoV-2 have been identified. To gain a better understanding of the wide variety of SARS-CoV-2 strains and their associated symptoms, thousands of SARS-CoV-2 genomes have been sequenced in dozens of countries. In this article, we introduce COVIDomic, a multi-omics online platform designed to facilitate the analysis and interpretation of the large amount of health data collected from patients with COVID-19. The COVIDomic platform provides a comprehensive set of bioinformatic tools for the multi-modal metatranscriptomic data analysis of COVID-19 patients to determine the origin of the coronavirus strain and the expected severity of the disease. An integrative analytical workflow, which includes microbial pathogens community analysis, COVID-19 genetic epidemiology and patient stratification, allows to analyze the presence of the most common microbial organisms, their antibiotic resistance, the severity of the infection and the set of the most probable geographical locations from which the studied strain could have originated. The online platform integrates a user friendly interface which allows easy visualization of the results. We envision this tool will not only have immediate implications for management of the ongoing COVID-19 pandemic, but will also improve our readiness to respond to other infectious outbreaks.
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| 13. |
- Uy, G. L., et al.
(författare)
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Contribution of chemotherapy mobilization to disease control in multiple myeloma treated with autologous hematopoietic cell transplantation
- 2015
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Ingår i: Bone Marrow Transplantation. - : Springer Science and Business Media LLC. - 0268-3369 .- 1476-5365. ; 50:12, s. 1513-1518
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Tidskriftsartikel (refereegranskat)abstract
- In patients with multiple myeloma (MM) undergoing autologous hematopoietic cell transplantation (auto-HCT), peripheral blood progenitor cells may be collected following mobilization with growth factor alone (GF) or cytotoxic chemotherapy plus GF (CC+GF). It is uncertain whether the method of mobilization affects post-transplant outcomes. We compared these mobilization strategies in a retrospective analysis of 968 patients with MM from the Center for International Blood and Marrow Transplant Research database who received an auto-Ha in the US and Canada between 2007 and 2012. The kinetics of neutrophil engraftment (>= 0.5 x 10(9)/L) was similar between groups (13 vs 13 days, P=0.69) while platelet engraftment (>= 20 x 10(9)/L) was slightly faster with CC+GF (19 vs 18 days, P=0.006). Adjusted 3-year PFS was 43% (95% confidence interval (CI) 38-48) in GF and 40% (95% CI 35-45) in CC+GF, P=0.33. Adjusted 3-year OS was 82% (95% CI 78-86) vs 80% (95% CI 75-84), P=0.43 and adjusted 5-year OS was 62% (95% CI 54-68) vs 60% (95% CI 52-67), P=0.76, for GF and CC+GF, respectively. We conclude that MM patients undergoing auto-Ha have similar outcomes irrespective of the method of mobilization and found no evidence that the addition of chemotherapy to mobilization contributes to disease control.
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| 19. |
- Ogishi, M, et al.
(författare)
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Impaired IL-23-dependent induction of IFN-γ underlies mycobacterial disease in patients with inherited TYK2 deficiency
- 2022
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Ingår i: The Journal of experimental medicine. - : Rockefeller University Press. - 1540-9538 .- 0022-1007. ; 219:10
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Tidskriftsartikel (refereegranskat)abstract
- Human cells homozygous for rare loss-of-expression (LOE) TYK2 alleles have impaired, but not abolished, cellular responses to IFN-α/β (underlying viral diseases in the patients) and to IL-12 and IL-23 (underlying mycobacterial diseases). Cells homozygous for the common P1104A TYK2 allele have selectively impaired responses to IL-23 (underlying isolated mycobacterial disease). We report three new forms of TYK2 deficiency in six patients from five families homozygous for rare TYK2 alleles (R864C, G996R, G634E, or G1010D) or compound heterozygous for P1104A and a rare allele (A928V). All these missense alleles encode detectable proteins. The R864C and G1010D alleles are hypomorphic and loss-of-function (LOF), respectively, across signaling pathways. By contrast, hypomorphic G996R, G634E, and A928V mutations selectively impair responses to IL-23, like P1104A. Impairment of the IL-23–dependent induction of IFN-γ is the only mechanism of mycobacterial disease common to patients with complete TYK2 deficiency with or without TYK2 expression, partial TYK2 deficiency across signaling pathways, or rare or common partial TYK2 deficiency specific for IL-23 signaling.
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| 20. |
- Porsbjerg, Celeste M., et al.
(författare)
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Association between pre-biologic T2-biomarker combinations and response to biologics in patients with severe asthma
- 2024
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Ingår i: Frontiers in Immunology. - : Frontiers Media S.A.. - 1664-3224. ; 15
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Tidskriftsartikel (refereegranskat)abstract
- Background: To date, studies investigating the association between pre-biologic biomarker levels and post-biologic outcomes have been limited to single biomarkers and assessment of biologic efficacy from structured clinical trials.Aim: To elucidate the associations of pre-biologic individual biomarker levels or their combinations with pre-to-post biologic changes in asthma outcomes in real-life.Methods: This was a registry-based, cohort study using data from 23 countries, which shared data with the International Severe Asthma Registry (May 2017-February 2023). The investigated biomarkers (highest pre-biologic levels) were immunoglobulin E (IgE), blood eosinophil count (BEC) and fractional exhaled nitric oxide (FeNO). Pre- to approximately 12-month post-biologic change for each of three asthma outcome domains (i.e. exacerbation rate, symptom control and lung function), and the association of this change with pre-biologic biomarkers was investigated for individual and combined biomarkers.Results: Overall, 3751 patients initiated biologics and were included in the analysis. No association was found between pre-biologic BEC and pre-to-post biologic change in exacerbation rate for any biologic class. However, higher pre-biologic BEC and FeNO were both associated with greater post-biologic improvement in FEV1 for both anti-IgE and anti-IL5/5R, with a trend for antiI-IL4R alpha. Mean FEV1 improved by 27-178 mL post-anti-IgE as pre-biologic BEC increased (250 to 1000 cells/mu L), and by 43-216 mL and 129-250 mL post-anti-IL5/5R and - anti- IL4R alpha, respectively along the same BEC gradient. Corresponding improvements along a FeNO gradient (25-100 ppb) were 41-274 mL, 69-207 mL and 148-224 mL for anti-IgE, anti-IL5/5R, and anti-IL4R alpha, respectively. Higher baseline BEC was also associated with lower probability of uncontrolled asthma (OR 0.392; p=0.001) post-biologic for anti-IL5/5R. Pre-biologic IgE was a poor predictor of subsequent pre-to-post-biologic change for all outcomes assessed for all biologics. The combination of BEC + FeNO marginally improved the prediction of post-biologic FEV1 increase (adjusted R-2: 0.751), compared to BEC (adjusted R-2: 0.747) or FeNO alone (adjusted R-2: 0.743) (p=0.005 and <0.001, respectively); however, this prediction was not improved by the addition of IgE.Conclusions: The ability of higher baseline BEC, FeNO and their combination to predict biologic-associated lung function improvement may encourage earlier intervention in patients with impaired lung function or at risk of accelerated lung function decline.
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