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Purpose: Biallelic pathogenic NBAS variants manifest as a multisystem disorder with heterogeneous clinical phenotypes such as recurrent acute liver failure, growth retardation, and susceptibility to infections. This study explores how NBAS-associated disease affects cells of the innate and adaptive immune system. Methods: Clinical and laboratory parameters were combined with functional multi-parametric immunophenotyping methods in fifteen NBAS-deficient patients to discover possible alterations in their immune system. Results: Our study revealed reduced absolute numbers of mature CD56dim natural killer (NK) cells. Notably, the residual NK cell population in NBAS-deficient patients exerted a lower potential for activation and degranulation in response to K562 target cells, suggesting an NK cell–intrinsic role for NBAS in the release of cytotoxic granules. NBAS-deficient NK cell activation and degranulation was normalized upon pre-activation by IL-2 in vitro, suggesting that functional impairment was reversible. In addition, we observed a reduced number of naïve B cells in the peripheral blood associated with hypogammaglobulinemia. Conclusion: In summary, we demonstrate that pathogenic biallelic variants in NBAS are associated with dysfunctional NK cells as well as impaired adaptive humoral immunity. [ABSTRACT FROM AUTHOR]

Background: Global life expectancy is rising, with the 60 + age group projected to hit 2 billion by 2050. Aging impacts the immune system. A notable marker of immune system aging is the presence of Aging-Related Immune Cell Phenotypes (ARIPs). Despite their importance, links between immune cell phenotypes including ARIPs and mortality are underexplored. We prospectively investigated 16 different immune cell phenotypes using flow cytometry and IL-6 in relation to survival outcome among dementia-free Framingham Heart Study (FHS) offspring cohort participants who attended the seventh exam (1998–2001). Results: Among 996 participants (mean age 62 years, range 40 to 88 years, 52% female), the 19-year survival rate was 65%. Adjusting for age, sex, and cytomegalovirus (CMV) serostatus, higher CD4/CD8 and Tc17/CD8 + Treg ratios were significantly associated with lower all-cause mortality (HR: 0.86 [0.76–0.96], 0.84 [0.74–0.94], respectively), while higher CD8 regulatory cell levels (CD8 + CD25 + FoxP3 +) were associated with increased all-cause mortality risk (HR = 1.17, [1.03–1.32]). Elevated IL-6 levels correlated with higher all-cause, cardiovascular, and non-cardiovascular mortality (HR = 1.43 [1.26–1.62], 1.70 [1.31–2.21], and 1.36 [1.18–1.57], respectively). However, after adjusting for cardiovascular risk factors and prevalent cancer alongside age, sex, and CMV, immune cell phenotypes were no longer associated with mortality in our cohort. Nonetheless, IL-6 remained significantly associated with all-cause and cardiovascular mortality (HRs: 1.3 [1.13–1.49], 1.5 [1.12–1.99], respectively). Conclusions: In 19-year follow-up, higher Tc17/CD8 + Treg and CD4/CD8 ratios were associated with lower all-cause mortality, while the CD8 + CD25 + FoxP3 + (CD8 + Treg) phenotype showed increased risk. Elevated IL-6 levels consistently correlated with amplified mortality risks. These findings highlight the links between immune phenotypes and mortality, suggesting implications for future research and clinical considerations. [ABSTRACT FROM AUTHOR]

Chronic lymphocytic leukemia is the most common type of leukemia in Western Europe and North America. It is mainly a disease of the elderly [9]. Average age of incidence - 72 years [5]. The pathological substrate is cells of the immune system - predominantly mature lymphocytes with a B-phenotype [1]. The clinical picture is variable, the rate of development of the disease is characterized by a wide range both in objective data and in hematological analyzes. The disease can be asymptomatic for many years, and is detected only during routine examination as an incidental finding. In such cases, a strategy of observation and waiting is chosen, without applying specific treatment. The main goals of treatment are to achieve complete or partial remission with improvement and stabilization of the clinical and hematological picture. [10]. To study the features of the epidemiology, clinical course and modern methods of treating CLL, a study was conducted on the basis of a database of 50 patients registered at the Consultative and Diagnostic Center of the Oncological Institute, Chisinau, Republic of Moldova. It was found that the main group with this diagnosis is people 55-75 years old (62%). The mean age of diagnosis among the selected group is 63 years. The incidence of CLL among men (58%) is slightly higher than among women (42%). The use of bio immunotherapy allows you to establish a positive trend in the course of the disease, as well as improve the quality of life of patients [4]. [ABSTRACT FROM AUTHOR]

Traditionally, the immune system is understood to be divided into discrete cell types that are identified via surface markers. While some cell type distinctions are no doubt discrete, others may in fact vary on a continum, and even within discrete types, differences in surface marker abundance could have functional implications. Here we propose a new way of looking at immune data, which is by looking directly at the values of the surface markers without dividing the cells into different subtypes. To assess the merit of this approach, we compared it with manual gating using cytometry data from the Singapore Longitudinal Aging Study (SLAS) database. We used two different neural networks (one for each method) to predict the presence of several health conditions. We found that the model built using raw surface marker abundance outperformed the manual gating one and we were able to identify some markers that contributed more to the predictions. This study is intended as a brief proof-of-concept and was not designed to predict health outcomes in an applied setting; nonetheless, it demonstrates that alternative methods to understand the structure of immune variation hold substantial progress. [ABSTRACT FROM AUTHOR]

Motivation For immune system monitoring in large-scale studies at the single-cell resolution using CyTOF, (semi-)automated computational methods are applied for annotating live cells of mixed cell types. Here, we show that the live cell pool can be highly enriched with undefined heterogeneous cells, i.e. 'ungated' cells, and that current semi-automated approaches ignore their modeling resulting in misclassified annotations. Result We introduce 'CyAnno', a novel semi-automated approach for deconvoluting the unlabeled cytometry dataset based on a machine learning framework utilizing manually gated training data that allows the integrative modeling of 'gated' cell types and the 'ungated' cells. By applying this framework on several CyTOF datasets, we demonstrated that including the 'ungated' cells can lead to a significant increase in the precision of the 'gated' cell types prediction. CyAnno can be used to identify even a single cell type, including rare cells, with higher efficacy than current state-of-the-art semi-automated approaches. Availability and implementation The CyAnno is available as a python script with a user-manual and sample dataset at https://github.com/abbioinfo/CyAnno. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]