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BackgroundSince the beginning of the coronavirus disease 2019 (COVID-19) pandemic, there has been increasing urgency to identify pathophysiological characteristics leading to severe clinical course in patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Human leukocyte antigen alleles (HLA) have been suggested as potential genetic host factors that affect individual immune response to SARS-CoV-2. We sought to evaluate this hypothesis by conducting a multicenter study using HLA sequencing.MethodsWe analyzed the association between COVID-19 severity and HLAs in 435 individuals from Germany (n = 135), Spain (n = 133), Switzerland (n = 20) and the United States (n = 147), who had been enrolled from March 2020 to August 2020. This study included patients older than 18 years, diagnosed with COVID-19 and representing the full spectrum of the disease. Finally, we tested our results by meta-analysing data from prior genome-wide association studies (GWAS).FindingsWe describe a potential association of HLA-C*04:01 with severe clinical course of COVID-19. Carriers of HLA-C*04:01 had twice the risk of intubation when infected with SARS-CoV-2 (risk ratio 1.5 [95% CI 1.1-2.1], odds ratio 3.5 [95% CI 1.9-6.6], adjusted p-value = 0.0074). These findings are based on data from four countries and corroborated by independent results from GWAS. Our findings are biologically plausible, as HLA-C*04:01 has fewer predicted bindings sites for relevant SARS-CoV-2 peptides compared to other HLA alleles.InterpretationHLA-C*04:01 carrier state is associated with severe clinical course in SARS-CoV-2. Our findings suggest that HLA class I alleles have a relevant role in immune defense against SARS-CoV-2.FundingFunded by Roche Sequencing Solutions, Inc.

Radiomics is an emerging approach to support the diagnosis of pulmonary nodules detected via low-dose computed tomography lung cancer screening. Serum metabolome is a promising source of auxiliary biomarkers that could help enhance the precision of lung cancer diagnosis in CT-based screening. Thus, we aimed to verify whether the combination of these two techniques, which provides local/morphological and systemic/molecular features of disease at the same time, increases the performance of lung cancer classification models. The collected cohort consists of 1086 patients with radiomic and 246 patients with serum metabolomic evaluations. Different machine learning techniques, i.e., random forest and logistic regression were applied for each omics. Next, model predictions were combined with various integration methods to create a final model. The best single omics models were characterized by an AUC of 83% in radiomics and 60% in serum metabolomics. The model integration only slightly increased the performance of the combined model (AUC equal to 85%), which was not statistically significant. We concluded that radiomics itself has a good ability to discriminate lung cancer from benign lesions. However, additional research is needed to test whether its combination with other molecular assessments would further improve the diagnosis of screening-detected lung nodules. [ABSTRACT FROM AUTHOR]

Rationale: Suboptimal vaccine immunogenicity and antigenic mismatch, compounded by poor uptake, means that influenza remains a major global disease. T cells recognizing peptides derived from conserved viral proteins could enhance vaccine-induced cross-strain protection. Objectives: To investigate the kinetics, phenotypes, and function of influenza virus-specific CD8+ resident memory T (Trm) cells in the lower airway and infer the molecular pathways associated with their response to infection in vivo. Methods: Healthy volunteers, aged 18-55, were inoculated intranasally with influenza A/California/4/09(H1N1). Blood, upper airway, and (in a subgroup) lower airway samples were obtained throughout infection. Symptoms were assessed by using self-reported diaries, and the nasal viral load was assessed by using quantitative PCR. T-cell responses were analyzed by using a three-color FluoroSpot assay, flow cytometry with MHC I-peptide tetramers, and RNA sequencing, with candidate markers being confirmed by using the immunohistochemistry results for endobronchial biopsy specimens. Measurements and Main Results: After challenge, 57% of participants became infected. Preexisting influenza-specific CD8+ T cells in blood correlated strongly with a reduced viral load, which peaked at Day 3. Influenza-specific CD8+ T cells in BAL fluid were highly enriched and predominantly expressed the Trm markers CD69 and CD103. Comparison between preinfection CD8+ T cells in BAL fluid and blood by using RNA sequencing revealed 3,928 differentially expressed genes, including all major Trm-cell markers. However, gene set enrichment analysis of BAL-fluid CD8+ T cells showed primarily innate cell-related pathways and, during infection, included upregulation of innate chemokines (Cxcl1, Cxcl10, and Cxcl16) that were also expressed by CD8+ cells in bronchial tissues. Conclusions: CD8+ Trm cells in the human lung display innate-like gene and protein expression that demonstrates blurred divisions between innate and adaptive immunity. Clinical study registered with www.clinicaltrials.gov (NCT02755948). [ABSTRACT FROM AUTHOR]

Efforts of the scientific community led to the development of multiple screening approaches for COVID-19 that rely on machine learning methods. However, there is a lack of works showing how to tune the classification models used for such a task and what the tuning effect is in terms of various classification quality measures. Understanding the impact of classifier tuning on the results obtained will allow the users to apply the provided tools consciously. Therefore, using a given screening test they will be able to choose the threshold value characterising the classifier that gives, for example, an acceptable balance between sensitivity and specificity. The presented work introduces the optimisation approach and the resulting classifiers obtained for various quality threshold assumptions. As a result of the research, an online service was created that makes the obtained models available and enables the verification of various solutions for different threshold values on new data. [ABSTRACT FROM AUTHOR]

Acute myeloid leukemia (AML) is an aggressive cancer that progresses rapidly with a poor prognosis. Cytogenetic analysis provides the most accurate determination of diagnosis and prognosis however, about 42–48% of AML patients have a cytogenetically normal karyotype. Genetic analysis can provide further information and the identification of new mutations could result in improved risk stratification, prognosis and better understanding of the mechanisms of AML leukaemogenesis. In this study, we analyzed genetic alterations in 16 human AML cases by Haloplex sequencing with confirmation of two previously unreported mutations in the genes DNMT3A and RUNX1 by Sanger sequencing or pyrosequencing. The two novel mutations consist of two frameshift mutations identified in two different AML patients and reported as deleterious by bioinformatic analysis. These mutations confirm the exclusion and co-occurrence of specific gene mutation patterns in AML and may provide further information for patient diagnosis and prognosis. [ABSTRACT FROM AUTHOR]

Therapy-related and more specifically radiotherapy-associated acute myeloid leukaemia (AML) is a well-recognized potential complication of cytotoxic therapy for the treatment of a primary cancer. The CBA mouse model is used to study radiation leukaemogenesis mechanisms with Sfpi1/PU.1 deletion and point mutation already identified as driving events during AML development. To identify new pathways, we analysed 123 mouse radiation-induced AML (rAML) samples for the presence of mutations identified previously in human AML and found three genes to be mutated; Sfpi1 R235 (68%), Flt3 -ITD (4%) and Kras G12 (3%), of which G12R was previously unreported. Importantly, a significant decrease in Sfpi1 gene expression is found almost exclusively in rAML samples without an Sfpi1 R235 mutation and is specifically associated with up-regulation of mir-1983 and mir-582-5p. Moreover, this down-regulation of Sfpi1 mRNA is negatively correlated with DNA methylation levels at specific CpG sites upstream of the Sfpi1 transcriptional start site. The down regulation of Sfpi1/PU.1 has also been reported in human AML cases revealing one common pathway of myeloid disruption between mouse and human AML where dysregulation of Sfpi1/PU.1 is a necessary step in AML development. [ABSTRACT FROM AUTHOR]

Activin A strongly influences immune responses; yet, few studies have examined its role in infectious diseases. We measured serum activin A levels in two independent tuberculosis (TB) patient cohorts and in patients with pneumonia and sarcoidosis. Serum activin A levels were increased in TB patients compared to healthy controls, including those with positive tuberculin skin tests, and paralleled severity of disease, assessed by X-ray scores. In pneumonia patients, serum activin A levels were also raised, but in sarcoidosis patients, levels were lower. To determine whether blockade of the activin A signaling axis could play a functional role in TB, we harnessed a soluble activin type IIB receptor fused to human IgG1 Fc, ActRIIB-Fc, as a ligand trap in a murine TB model. The administration of ActRIIB-Fc to Mycobacterium tuberculosis -infected mice resulted in decreased bacterial loads and increased numbers of CD4 effector T cells and tissue-resident memory T cells in the lung. Increased frequencies of tissue-resident memory T cells corresponded with downregulated T-bet expression in lung CD4 and CD8 T cells. Altogether, the results suggest a disease-exacerbating role of ActRIIB signaling pathways. Serum activin A may be useful as a biomarker for diagnostic triage of active TB or monitoring of anti-tuberculosis therapy., Importance: Tuberculosis remains the leading cause of death by a bacterial pathogen. The etiologic agent of tuberculosis, Mycobacterium tuberculosis , can remain dormant in the infected host for years before causing disease. Significant effort has been made to identify biomarkers that can discriminate between latently infected and actively diseased individuals. We found that serum levels of the cytokine activin A were associated with increased lung pathology and could discriminate between active tuberculosis and tuberculin skin-test-positive healthy controls. Activin A signals through the ActRIIB receptor, which can be blocked by administration of the ligand trap ActRIIB-Fc, a soluble activin type IIB receptor fused to human IgG1 Fc. In a murine model of tuberculosis, we found that ActRIIB-Fc treatment reduced mycobacterial loads. Strikingly, ActRIIB-Fc treatment significantly increased the number of tissue-resident memory T cells. These results suggest a role for ActRIIB signaling pathways in host responses to Mycobacterium tuberculosis and activin A as a biomarker of ongoing disease., Competing Interests: The authors declare no conflict of interest.

Rationale: Suboptimal vaccine immunogenicity and antigenic mismatch, compounded by poor uptake, means that influenza remains a major global disease. T cells recognizing peptides derived from conserved viral proteins could enhance vaccine-induced cross-strain protection. Objectives: To investigate the kinetics, phenotypes, and function of influenza virus-specific CD8 + resident memory T (Trm) cells in the lower airway and infer the molecular pathways associated with their response to infection in vivo . Methods: Healthy volunteers, aged 18-55, were inoculated intranasally with influenza A/California/4/09(H1N1). Blood, upper airway, and (in a subgroup) lower airway samples were obtained throughout infection. Symptoms were assessed by using self-reported diaries, and the nasal viral load was assessed by using quantitative PCR. T-cell responses were analyzed by using a three-color FluoroSpot assay, flow cytometry with MHC I-peptide tetramers, and RNA sequencing, with candidate markers being confirmed by using the immunohistochemistry results for endobronchial biopsy specimens. Measurements and Main Results: After challenge, 57% of participants became infected. Preexisting influenza-specific CD8 + T cells in blood correlated strongly with a reduced viral load, which peaked at Day 3. Influenza-specific CD8 + T cells in BAL fluid were highly enriched and predominantly expressed the Trm markers CD69 and CD103. Comparison between preinfection CD8 + T cells in BAL fluid and blood by using RNA sequencing revealed 3,928 differentially expressed genes, including all major Trm-cell markers. However, gene set enrichment analysis of BAL-fluid CD8 + T cells showed primarily innate cell-related pathways and, during infection, included upregulation of innate chemokines ( Cxcl1 , Cxcl10 , and Cxcl16 ) that were also expressed by CD8 + cells in bronchial tissues. Conclusions: CD8 + Trm cells in the human lung display innate-like gene and protein expression that demonstrates blurred divisions between innate and adaptive immunity. Clinical study registered with www.clinicaltrials.gov (NCT02755948).