Usage Information

Defects of T-cell effector function and post-thymic maturation in X-linked hyper-IgM syndrome
Ashish Jain, T. Prescott Atkinson, Peter E. Lipsky, Jay E. Slater, David L. Nelson, Warren Strober
Ashish Jain, T. Prescott Atkinson, Peter E. Lipsky, Jay E. Slater, David L. Nelson, Warren Strober
View: Text | PDF
Article

Defects of T-cell effector function and post-thymic maturation in X-linked hyper-IgM syndrome

Abstract

X-linked hyper-IgM syndrome (XHIM) results from mutations in the gene encoding for CD40 ligand (CD154). Patients with the syndrome suffer from infections with opportunistic pathogens such as Cryptosporidium and Pneumocystis carinii. In this study, we demonstrate that activated T cells from patients with XHIM produce markedly reduced levels of IFN-γ, fail to induce antigen-presenting cells to synthesize IL-12, and induce greatly reduced levels of TNF-α. In addition, we show that the patients’ circulating T lymphocytes of both the CD4+ and CD8+ subsets contain a markedly reduced antigen-primed population, as determined by CD45RO expression. Finally, we demonstrate that the defects in antigen priming are likely due to the lack of CD154 expression and insufficient costimulation of T cells by CD80/CD86 interactions. Taken together, this study offers a basis for the increased susceptibility of patients with XHIM to certain opportunistic infections.

Authors

Ashish Jain, T. Prescott Atkinson, Peter E. Lipsky, Jay E. Slater, David L. Nelson, Warren Strober

×

Usage data is cumulative from June 2025 through June 2026.

Usage JCI PMC
Text version 707 59
PDF 110 18
Figure 434 14
Table 75 0
Citation downloads 113 0
Totals 1,439 91
Total Views 1,530
(Click and drag on plot area to zoom in. Click legend items above to toggle)

Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.

Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.

Advertisement