Dataset Information

Tregs: Where We Are and What Comes Next?

ABSTRACT: Regulatory T cells are usually recognized as a specialized subset of CD4+ T cells functioning in establishment and maintenance of immune tolerance. Meanwhile, there is emerging evidence that regulatory T cells (Tregs) are also present in various non-lymphoid tissues, and that they have unique phenotypes credited with activities distinct from regulatory function. Their development and function have been described in plenty of manuscripts in the past two decades. However, with the deepening of research in recent years, emerging evidence revealed some novel mechanisms about how Tregs exert their activities. First, we discuss the expanding family of regulatory lymphocytes briefly and then, try to interpret how fork-head box P3 (Foxp3), a master regulator of the regulatory pathway in the development and function of regulatory T cells, functions. Subsequently, another part of our focus is varieties of tissue Tregs. Next, we primarily discuss recent research on how Tregs work and their faceted functions in terms of soluble mediators, functional proteins, and inhibitory receptors. In particular, unless otherwise noted, the term "Treg" is used here to refer specially to the "CD4+CD25+Foxp3+" regulatory cells.

SUBMITTER: Zhao H

PROVIDER: S-EPMC5705554 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Tregs: Where We Are and What Comes Next?

Zhao Hai H Liao Xuelian X Kang Yan Y

Frontiers in immunology 20171124

Regulatory T cells are usually recognized as a specialized subset of CD4<sup>+</sup> T cells functioning in establishment and maintenance of immune tolerance. Meanwhile, there is emerging evidence that regulatory T cells (Tregs) are also present in various non-lymphoid tissues, and that they have unique phenotypes credited with activities distinct from regulatory function. Their development and function have been described in plenty of manuscripts in the past two decades. However, with the deepe ...[more]

PMID: 29225597

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Project description:BackgroundTo describe long-term outcomes in JDM using patient questionnaires and link to longitudinal, prospectively collected data for each patient within the Juvenile Dermatomyositis Cohort and Biomarker Study, UK and Ireland (JDCBS) to determine outcome predictors. METHODS: JDCBS participants aged ≥ 16y completed the SF36, HAQ and a questionnaire regarding current disease features, medications, education and employment. Data collected from the JDCBS included disease subtype, demographics, clinical and laboratory features. Intensity indices were calculated for physician VAS, modified skin DAS, CMAS and MMT8 by dividing area under the curve (AUC) from longitudinal score trajectories by duration of study follow-up (y). Relationships between questionnaire and JDCBS clinical / laboratory data were investigated fitting statistical models appropriate for cross sectional and longitudinal data.ResultsOf 190 questionnaires sent, 84 (44%) were returned. Average age of respondents was 20.6 years (SD 3.9), time since diagnosis was 12.4 years (SD 5.0), age at onset was 9.2 years (SD 4.3), female to male ratio 4.25:1. Forty-nine (59%) self-reported persistently active disease, 54 (65%) were still taking immunosuppressive medication. 14/32 at school/higher education reported myositis adversely affecting academic results. 18-24 year-olds were twice as likely to be unemployed compared the UK population (OR = 0.456, 95% CI 0.24, 0.84, p = 0.001). Participants ≥ 18 years were three times as likely to be living with a parent/guardian (OR = 3.39, p < 0.001). SF36 MCS and MMT8 intensity index scores were significantly correlated (ρ = 0.328, p = 0.007).ConclusionsAfter 12.4 years, questionnaire responders reported self-perceived high rates of persistently active disease and medication use, reduced rates of employment and were more likely to live with a parent/guardian. Perceived persistently active muscle disease appeared to affect quality of life in these patients and was the most significant contributor to long-term outcomes. Our findings highlight the importance of including the patient perspective in the assessment of long term outcomes, so that that we can start to target initial management strategies more effectively based on a combination of clinical and patient-reported data.

Dataset Information

Tregs: Where We Are and What Comes Next?

Publications

Tregs: Where We Are and What Comes Next?

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