Biomedical subjects

Steven H Kleinstein

Publications and source records attributed to Steven H Kleinstein.

5 recordsLinked to original sources

PubMed2025

Innate immune molecular landscape following controlled human influenza virus infection.

Viral infections can induce prolonged changes in innate immunity. Here, we use blood samples from a human influenza H3N2 challenge study (NCT03883113) to perform comprehensive multi-omics analyses. We detect remodeling of immune programs in circulating innate immune cells that persist after resolution of the infection. We find changes associated with suppressed inflammation, including decreased cytokine and AP-1 gene expression as well as decreased accessibility at AP-1 targets and interleukin-related gene promoter regions. We also find decreased histone deacetylase gene expression, increased MAP kinase gene expression, and increased accessibility at interferon-related gene promoter regions. Genes involved in inflammation and methylation remodeling show modulation of gene-chromatin site regulatory circuit activity. These results reveal a coordinated rewiring of the molecular landscape in innate immune cells induced by mild influenza virus infection.

Humans↗

PubMed2025

High-affinity CD16A polymorphism associated with reduced risk ofsevere COVID-19.

CD16A is an activating Fc receptor on NK cells that mediates antibody-dependent cellular cytotoxicity (ADCC), a key mechanism in antiviral immunity. However, the role of NK cell-mediated ADCC in SARS-CoV-2 infection remains unclear, particularly whether it limits viral spread and disease severity or contributes to the immunopathogenesis of COVID-19. We hypothesized that the high-affinity CD16AV176 polymorphism influences these outcomes. Using an in vitro reporter system, we demonstrated that CD16AV176 is a more potent and sensitive activator than the common CD16AF176 allele. To assess its clinical relevance, we analyzed 1,027 patients hospitalized with COVID-19 from the Immunophenotyping Assessment in a COVID-19 cohort (IMPACC), a comprehensive longitudinal dataset with extensive transcriptomic, proteomic, and clinical data. The high-affinity CD16AV176 allele was associated with a significantly reduced risk of ICU admission, mechanical ventilation, and severe disease trajectories. Lower anti-SARS-CoV-2 IgG titers were correlated to CD16AV176; however, there was no difference in viral load across CD16A genotypes. Proteomic analysis revealed that participants homozygous for CD16AV176 had lower levels of inflammatory mediators. These findings suggest that CD16AV176 enhances early NK cell-mediated immune responses, limiting severe respiratory complications in COVID-19. This study identifies a protective genetic factor against severe COVID-19, informing future host-directed therapeutic strategies.

Humans↗

PubMed2006

Mutation parameters from DNA sequence data using graph theoretic measures on lineage trees.

MOTIVATION: B cells responding to antigenic stimulation can fine-tune their binding properties through a process of affinity maturation composed of somatic hypermutation, affinity-selection and clonal expansion. The mutation rate of the B cell receptor DNA sequence, and the effect of these mutations on affinity and specificity, are of critical importance for understanding immune and autoimmune processes. Unbiased estimates of these properties are currently lacking due to the short time-scales involved and the small numbers of sequences available. RESULTS: We have developed a bioinformatic method based on a maximum likelihood analysis of phylogenetic lineage trees to estimate the parameters of a B cell clonal expansion model, which includes somatic hypermutation with the possibility of lethal mutations. Lineage trees are created from clonally related B cell receptor DNA sequences. Important links between tree shapes and underlying model parameters are identified using mutual information. Parameters are estimated using a likelihood function based on the joint distribution of several tree shapes, without requiring a priori knowledge of the number of generations in the clone (which is not available for rapidly dividing populations in vivo). A systematic validation on synthetic trees produced by a mutating birth-death process simulation shows that our estimates are precise and robust to several underlying assumptions. These methods are applied to experimental data from autoimmune mice to demonstrate the existence of hypermutating B cells in an unexpected location in the spleen.

Algorithms↗

PubMed2003

Estimating hypermutation rates from clonal tree data.

To understand the mechanisms underlying the varying patterns of mutations that occur during immune and autoimmune responses, estimates of the somatic hypermutation rate are critical. However, despite its significance, precise estimates of the mutation rate do not currently exist. Microdissection studies of mutating B cell clones provide an opportunity to measure this rate more accurately than previously possible. Each microdissection provides a number of clonally related sequences that, through the analysis of shared mutations, can be genealogically related to each other. The shape of these clonal trees is influenced by many processes, including the hypermutation rate. We have developed two different methods to estimate the mutation rate based on these data. These methods are applied to two sets of experimental data, one from an autoimmune response and one from the antihapten response to (4-hydroxy-3-nitrophenyl)acetyl (NP). Comparable mutation rates are estimated for both responses, 0.7-0.9 x 10(-3) and 0.9-1.1 x 10(-3) bp(-1) division(-1) for the autoimmune and NP responses, respectively. In addition to comparing the results of the two procedures, we investigate the effect on our estimate of assumptions, such as the fraction of lethal mutations.

Animals↗

PubMed2003

Why are there so few key mutant clones? The influence of stochastic selection and blocking on affinity maturation in the germinal center.

A small number of key somatic mutations lead to high-affinity binding in the anti-hapten immune responses to 2-phenyl-5-oxazolone (phOx) and (4-hydroxy-3-nitrophenyl)acetyl (NP). Affinity maturation models of the germinal center hold that B cells carrying these key mutations are preferentially selected for expansion within the germinal centers. However, additional factors are required to account for some quantitative aspects of affinity maturation in vivo. Radmacher et al. have shown that key mutants are observed in vivo significantly less frequently than expected by these models. To account for this finding, they propose that selection is a stochastic process where key mutants may be overlooked by positive selection or recruited out of the germinal center. While acknowledging that a minimal amount of stochastic selection is probably unavoidable in the germinal center, we instead propose a structural explanation for this key mutant discrepancy. This model is based on the existence of a large number of blocking mutations whose presence can prevent the ability of key mutations to confer high-affinity binding. Using mathematical modeling and computer simulation, we show that in addition to reconciling the key mutant discrepancy, the blocking model accounts for other aspects of experimental data that are not predicted by the stochastic selection model. In particular, the blocking model is consistent with the observation that key mutants generally exhibit a higher number of mutations per sequence in the phOx response, but a lower number in the NP response.

Amino Acid Sequence↗