Dataset Information

Age-Related Gene Alteration in Naive and Memory T cells Using Precise Age-Tracking Model.

ABSTRACT: In aged individuals, age-related changes in immune cells, especially T cell deficiency, are associated with an increased incidence of infection, tumor, and autoimmune disease, as well as an impaired response to vaccination. However, the features of gene expression levels in aged T cells are still unknown. Our previous study successfully tracked aged T cells generated from one wave of developing thymocytes of young age by a lineage-specific and inducible Cre-controlled reporter (TCR? ^CreER R26 ^ZsGreen mouse strain). In this study, we utilized this model and genome-wide transcriptomic analysis to examine changes in gene expression in aged naïve and memory T cell populations during the aging process. We identified profound gene alterations in aged CD4 and CD8 T cells. Both aged CD4⁺ and CD8⁺ naïve T cells showed significantly decreased organelle function. Importantly, genes associated with lymphocyte activation and function demonstrated a significant increase in aged memory T cells, accompanied by upregulation of immunosuppressive markers and immune checkpoints, revealing an abnormal T cell function in aged cells. Furthermore, aging significantly affects T cell survival and death signaling. While aged CD4 memory T cells exhibited pro-apoptotic gene signatures, aged CD8 memory T cells expressed anti-apoptotic genes. Thus, the transcriptional analysis of gene expression and signaling pathways in aged T cell subsets shed light on our understanding of altered immune function with aging, which will have great potential for clinical interventions for older adults.

SUBMITTER: Yang X

PROVIDER: S-EPMC7905051 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Age-Related Gene Alteration in Naïve and Memory T cells Using Precise Age-Tracking Model.

Yang Xiaofeng X Wang Xin X Lei Lei L Sun Lina L Jiao Anjun A Zhu Kun K Xie Tao T Liu Haiyan H Zhang Xingzhe X Su Yanhong Y Zhang Cangang C Shi Lin L Zhang Dan D Zheng Huiqiang H Zhang Jiahui J Liu Xiaobin X Wang Xin X Zhou Xiaobo X Sun Chenming C Zhang Baojun B

Frontiers in cell and developmental biology 20210211

In aged individuals, age-related changes in immune cells, especially T cell deficiency, are associated with an increased incidence of infection, tumor, and autoimmune disease, as well as an impaired response to vaccination. However, the features of gene expression levels in aged T cells are still unknown. Our previous study successfully tracked aged T cells generated from one wave of developing thymocytes of young age by a lineage-specific and inducible Cre-controlled reporter (<i>TCR</i>δ <sup> ...[more]

PMID: 33644036

Similar Datasets

Project description:An unfortunate result of the rapid rise in geriatric populations worldwide is the increasing prevalence of age-related cognitive disorders such as Alzheimer's disease (AD). AD is a devastating neurodegenerative illness that is characterized by a profound impairment of cognitive function, marked physical disability, and an enormous economic burden on the afflicted individual, caregivers, and society in general. The rise in elderly populations is also resulting in an increase in individuals with related (potentially treatable) conditions such as "Mild Cognitive Impairment" (MCI) which is characterized by a less severe (but abnormal) level of cognitive impairment and a high-risk for developing dementia. Even in the absence of a diagnosable disorder of cognition (e.g., AD and MCI), the perception of increased forgetfulness and declining mental function is a clear source of apprehension in the elderly. This is a valid concern given that even a modest impairment of cognitive function is likely to be associated with significant disability in a rapidly evolving, technology-based society. Unfortunately, the currently available therapies designed to improve cognition (i.e., for AD and other forms of dementia) are limited by modest efficacy and adverse side effects, and their effects on cognitive function are not sustained over time. Accordingly, it is incumbent on the scientific community to develop safer and more effective therapies that improve and/or sustain cognitive function in the elderly allowing them to remain mentally active and productive for as long as possible. As diagnostic criteria for memory disorders evolve, the demand for pro-cognitive therapeutic agents is likely to surpass AD and dementia to include MCI and potentially even less severe forms of memory decline. The purpose of this review is to provide an overview of the contemporary therapeutic targets and preclinical pharmacologic approaches (with representative drug examples) designed to enhance memory function.

Project description:BackgroundRecent evidences have suggested that human microorganisms participate in important biological activities in the human body. The dysfunction of host-microbiota interactions could lead to complex human disorders. The knowledge on host-microbiota interactions can provide valuable insights into understanding the pathological mechanism of diseases. However, it is time-consuming and costly to identify the disorder-specific microbes from the biological "haystack" merely by routine wet-lab experiments. With the developments in next-generation sequencing and omics-based trials, it is imperative to develop computational prediction models for predicting microbe-disease associations on a large scale.ResultsBased on the known microbe-disease associations derived from the Human Microbe-Disease Association Database (HMDAD), the proposed model shows reliable performance with high values of the area under ROC curve (AUC) of 0.9456 and 0.8866 in leave-one-out cross validations and five-fold cross validations, respectively. In case studies of colorectal carcinoma, 80% out of the top-20 predicted microbes have been experimentally confirmed via published literatures.ConclusionBased on the assumption that functionally similar microbes tend to share the similar interaction patterns with human diseases, we here propose a group based computational model of Bayesian disease-oriented ranking to prioritize the most potential microbes associating with various human diseases. Based on the sequence information of genes, two computational approaches (BLAST+ and MEGA 7) are leveraged to measure the microbe-microbe similarity from different perspectives. The disease-disease similarity is calculated by capturing the hierarchy information from the Medical Subject Headings (MeSH) data. The experimental results illustrate the accuracy and effectiveness of the proposed model. This work is expected to facilitate the characterization and identification of promising microbial biomarkers.

Dataset Information

Age-Related Gene Alteration in Naive and Memory T cells Using Precise Age-Tracking Model.

Publications

Age-Related Gene Alteration in Naïve and Memory T cells Using Precise Age-Tracking Model.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets