Effect of Mycobacterial Infection on Immune Status (EMIIS)
4 июня 2026 г. обновлено: Chao Cao, Ph.D., First Affiliated Hospital of Ningbo University
This study, titled "Effect of Mycobacterial Infection on Immune Status" (EMIIS), investigates the immune-driven mechanisms of mycobacterial infections, focusing on the dynamic immune characteristics of multidrug-resistant tuberculosis (MDR-TB), nontuberculous mycobacterial (NTM) infections, and tuberculous pleurisy.
Mycobacterial infections (including the Mycobacterium tuberculosis complex and nontuberculous mycobacteria) remain a major global public health threat.
EMIIS is a single-center, randomized, single-blind,prospective study.
The study recruited 120 participants, divided into groups of healthy individuals/community-acquired pneumonia patients, active pulmonary tuberculosis patients, latent tuberculosis infection patients, tuberculous pleurisy patients, and nontuberculous mycobacteria patients.
Blood samples were collected from all groups within 3 days before treatment and 2-3 months after treatment.
Pleural effusion samples were additionally collected from the tuberculous pleurisy group within 3 days before treatment and 2 months after treatment.
Exhaled breath condensate (EBC) was collected from the nontuberculous mycobacteria group.
Utilizing mass cytometry (CyTOF) and multi-dimensional indicators, the study aims to elucidate the immune-driven mechanisms of mycobacterial infections and provide new strategies for individualized treatment.
Обзор исследования
Статус
Рекрутинг
Условия
Тип исследования
Наблюдательный
Регистрация (Оцененный)
120
Контакты и местонахождение
В этом разделе приведены контактные данные лиц, проводящих исследование, и информация о том, где проводится это исследование.
Контакты исследования
- Имя: Shiyi He
- Номер телефона: +86-0574-87089878
- Электронная почта: shiyihii@163.com
Учебное резервное копирование контактов
- Имя: Chao Cao
- Номер телефона: +86-0574-87089878
- Электронная почта: caodoctor@163.com
Места учебы
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Ningbo, Китай
- Рекрутинг
- The First Affiliated Hospital of Ningbo University
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Критерии участия
Исследователи ищут людей, которые соответствуют определенному описанию, называемому критериям приемлемости. Некоторыми примерами этих критериев являются общее состояние здоровья человека или предшествующее лечение.
Критерии приемлемости
Возраст, подходящий для обучения
- Взрослый
- Пожилой взрослый
Принимает здоровых добровольцев
Нет
Метод выборки
Вероятностная выборка
Исследуемая популяция
Patients with clinical diagnosis including (active tuberculosis, latent tuberculosis, multidrug-resistant tuberculosis, tuberculous pleurisy, nontuberculous mycobacteria), older than 18 years, meeting the inclusion criteria and no exclusion criteria.
Описание
Inclusion Criteria and Exclusion Criteria:
Inclusion Criteria：
- Age ≥ 18 years, all genders and races accepted.
- Patients with active pulmonary tuberculosis diagnosed clinically or by bronchoscopy within less than 1 week.
- Patients with latent tuberculosis infection (positive T-SPOT test but no evidence of active tuberculosis infection).
- Patients with tuberculous pleurisy with onset within less than 1 week.
- Voluntarily join this study and sign the informed consent form.
- Patients whose drug susceptibility test or NGS results indicate resistance to at least isoniazid and rifampicin (MDR-TB).
- Patients whose drug susceptibility test or NGS results indicate sensitivity to first-line anti-tuberculosis drugs.
- Patients whose drug susceptibility test or NGS results indicate resistance to only one anti-tuberculosis drug.
- Patients with newly identified nontuberculous mycobacterial infection (within less than 1 week) by sputum culture or NGS.
Exclusion Criteria：
- Immunosuppressive conditions including HIV infection, long-term use (>1 month) of immunosuppressive agents or corticosteroids, severe malnutrition, etc.
- Concurrent other lung diseases, severe liver or kidney dysfunction, severe endocrine diseases, hematological diseases, or malignant tumors that may affect the study outcomes.
- Patients with diabetes mellitus.
- Pregnant or lactating women.
- Patients unable or unwilling to provide informed consent, or with poor compliance.
Учебный план
В этом разделе представлена подробная информация о плане исследования, в том числе о том, как планируется исследование и что оно измеряет.
Как устроено исследование?
Детали дизайна
Когорты и вмешательства
Группа / когорта |
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Immunometabolic differences between DS-TB and MDR-TB
Using a prospective, single-center, observational study design, it is planned to enroll 30 patients divided into drug-susceptible tuberculosis and multidrug-resistant tuberculosis.
CyTOF technology was used to analyze the differences in immune subsets and metabolic functions.
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To assess the effect of immune status on NTM
A total of 15 patients over the age of 18 diagnosed with non-tuberculous mycobacteria were included, and peripheral blood samples were collected after 2 months of treatment to analyze the changes in immune status and metabolic status of non-tuberculous mycobacterial patients in healthy people.
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Significance of studying the immunometabolic status of tuberculous pleurisy
A total of 20 patients over the age of 18 diagnosed with tuberculous pleurisy were included in the plan, divided into high-symptom and low-symptomatic groups, and pleural fluid and peripheral blood samples were collected before and after treatment to analyze the changes in their immune status and metabolic status before and after treatment.
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Study of immunometabolic status in different states of tuberculosis
A total of 15 patients over the age of 18 diagnosed with active pulmonary tuberculosis and 10 patients with latent pulmonary tuberculosis were enrolled, and peripheral blood samples were collected before and after treatment to analyze the changes in their immune status and metabolic status before and after treatment.
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A study of exhaled air condensate in NTM patients versus CAP patients
A total of 30 patients over the age of 18 diagnosed with nontuberculous mycobacteria and 30 healthy or community pneumonia patients were enrolled, and their exhaled air condensate was collected before or within 2 weeks after treatment to analyze its composition.
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Что измеряет исследование?
Первичные показатели результатов
Мера результата |
Мера Описание |
Временное ограничение |
|---|---|---|
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To establish a multi-immune pathway interaction network and composite biomarkers in mycobacterial infection thing
Временное ограничение: 3 days before treatment and 2 months after treatment
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This study utilized mass cytometry (CyTOF) and a pre-designed panel containing 41 metal-tagged antibodies for detection.
After data normalization and doublet exclusion, multiple machine learning algorithms were applied for clustering analysis to quantitatively compare the proportions of various immune subsets (such as Th1 cells, Th17 cells, classical monocytes, CD4TEM cells, CD8TEM cells,etc.)
among CD45+ leukocytes in the peripheral blood of healthy individuals and patients with active tuberculosis.
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3 days before treatment and 2 months after treatment
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Вторичные показатели результатов
Мера результата |
Мера Описание |
Временное ограничение |
|---|---|---|
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Immune cell subsets and mechanisms of possible effects of anti-tuberculosis drugs
Временное ограничение: 3 days before treatment and 2 months after treatment
|
This study utilized mass cytometry (CyTOF) and a pre-designed panel containing 41 metal-tagged antibodies for detection.
After data normalization and doublet exclusion, multiple machine learning algorithms were applied for clustering analysis to quantitatively compare the proportions of various immune subsets (such as Th1 cells, Th17 cells, classical monocytes, CD4TEM cells, CD8TEM cells,etc.)
among CD45+ leukocytes in the peripheral blood of healthy individuals and patients with active tuberculosis.
|
3 days before treatment and 2 months after treatment
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Differences in immune subsets between normal persons and patients with active pulmonary tuberculosis
Временное ограничение: 3 days before treatment and 2 months after treatment
|
This study utilized mass cytometry (CyTOF) and a pre-designed panel containing 41 metal-tagged antibodies for detection.
After data normalization and doublet exclusion, multiple machine learning algorithms were applied for clustering analysis to quantitatively compare the proportions of various immune subsets (such as Th1 cells, Th17 cells, classical monocytes, CD4TEM cells, CD8TEM cells,etc.)
among CD45+ leukocytes in the peripheral blood of healthy individuals and patients with active tuberculosis.
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3 days before treatment and 2 months after treatment
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To explore whether the peripheral blood before treatment contains a certain marker can predict the short-term efficacy
Временное ограничение: 3 days before treatment and 2 months after treatment
|
This study utilized mass cytometry (CyTOF) and a pre-designed panel containing 41 metal-tagged antibodies for detection.
After data normalization and doublet exclusion, multiple machine learning algorithms were applied for clustering analysis to quantitatively compare the proportions of various immune subsets (such as Th1 cells, Th17 cells, classical monocytes, CD4TEM cells, CD8TEM cells,etc.)
among CD45+ leukocytes in the peripheral blood of healthy individuals and patients with active tuberculosis.
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3 days before treatment and 2 months after treatment
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Comparison of the dynamic changes of immune subsets in peripheral blood and pleural effusion of TP patients before and after treatment
Временное ограничение: 3 days before treatment and 2 months after treatment
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Using CyTOF with a 41-metal-labeled antibody panel, peripheral blood samples from healthy controls and untreated patients with tuberculous pleurisy were analyzed.
After data normalization and debarcoding, clustering was applied to determine the percentages of CD45+ leukocyte subsets (Th1, Th17, classical monocytes, CD4+/CD8+ effector memory T cells, and NK cells).
Patients were divided into high- and low-symptom groups based on symptom severity.
Immune subset proportions were compared between each patient group and healthy controls, as well as between the two patient groups.
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3 days before treatment and 2 months after treatment
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To explore the differences of peripheral blood immune subsets between TP patients and healthy people before treatment
Временное ограничение: 3 days before treatment and 2 months after treatment
|
Using CyTOF with a 41-metal-labeled antibody panel, peripheral blood samples from healthy controls and untreated patients with tuberculous pleurisy were analyzed.
After data normalization and debarcoding, clustering was applied to determine the percentages of CD45+ leukocyte subsets (Th1, Th17, classical monocytes, CD4+/CD8+ effector memory T cells, and NK cells).
Patients were divided into high- and low-symptom groups based on symptom severity.
Immune subset proportions were compared between each patient group and healthy controls, as well as between the two patient groups.
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3 days before treatment and 2 months after treatment
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To explore the metabolic differences of three major nutrients between TP patients and healthy people before treatment
Временное ограничение: 3 days before treatment and 2 months after treatment
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Using CyTOF with an antibody panel including metabolic markers such as GLUT1 and CPT1A, the expression levels of these markers were measured in peripheral blood immune subsets (CD4+ T cells, CD8+ T cells, monocytes, etc.) from healthy controls and untreated patients with tuberculous pleurisy.
The median fluorescence intensity (MdFI) of GLUT1 and CPT1A on each subset was used as the primary metric to quantify differences in glucose metabolism and fatty acid oxidation capacity.
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3 days before treatment and 2 months after treatment
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Differences in metabolic function between multidrug-resistant tuberculosis group and drug-sensitive tuberculosis group
Временное ограничение: 3 days before treatment and 2 months after treatment
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In this study, CyTOF and a preconfigured panel consisting of 41 metal-conjugated antibodies were used for specimen detection.
After data normalization and doublet removal, multiple machine learning algorithms were utilized for cell clustering analysis.
We quantitatively compared the proportional differences of various immune subsets in peripheral blood CD45⁺ leukocytes among drug-resistant tuberculosis (DR-TB), drug-susceptible tuberculosis (DS-TB) and healthy control groups, including Th1 cells, Th17 cells, classical monocytes, CD4⁺ effector memory T cells and CD8⁺ effector memory T cells.
This study aims to characterize treatment-induced quantitative changes in immune subsets and provide evidence for screening novel biomarkers.
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3 days before treatment and 2 months after treatment
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Influence of immune status on the efficacy of NTM
Временное ограничение: 3 days before treatment and 2 months after treatment
|
This study utilized mass cytometry (CyTOF) and a pre-designed panel containing 41 metal-tagged antibodies for detection.
After data normalization and doublet exclusion, multiple machine learning algorithms were applied for clustering analysis to quantitatively compare the proportions of various immune subsets (such as Th1 cells, Th17 cells, classical monocytes, CD4TEM cells, CD8TEM cells,etc.)
among CD45+ leukocytes in the peripheral blood of healthy individuals and patients with active tuberculosis.
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3 days before treatment and 2 months after treatment
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Соавторы и исследователи
Здесь вы найдете людей и организации, участвующие в этом исследовании.
Даты записи исследования
Эти даты отслеживают ход отправки отчетов об исследованиях и сводных результатов на сайт ClinicalTrials.gov. Записи исследований и сообщаемые результаты проверяются Национальной медицинской библиотекой (NLM), чтобы убедиться, что они соответствуют определенным стандартам контроля качества, прежде чем публиковать их на общедоступном веб-сайте.
Изучение основных дат
Начало исследования (Действительный)
9 июля 2025 г.
Первичное завершение (Оцененный)
20 июля 2026 г.
Завершение исследования (Оцененный)
20 июля 2026 г.
Даты регистрации исследования
Первый отправленный
19 мая 2026 г.
Впервые представлено, что соответствует критериям контроля качества
4 июня 2026 г.
Первый опубликованный (Действительный)
10 июня 2026 г.
Обновления учебных записей
Последнее опубликованное обновление (Действительный)
10 июня 2026 г.
Последнее отправленное обновление, отвечающее критериям контроля качества
4 июня 2026 г.
Последняя проверка
1 июня 2026 г.
Дополнительная информация
Термины, связанные с этим исследованием
Дополнительные соответствующие термины MeSH
Другие идентификационные номера исследования
- 2025-157A-01
Планирование данных отдельных участников (IPD)
Планируете делиться данными об отдельных участниках (IPD)?
НЕТ
Информация о лекарствах и устройствах, исследовательские документы
Изучает лекарственный продукт, регулируемый FDA США.
Нет
Изучает продукт устройства, регулируемый Управлением по санитарному надзору за качеством пищевых продуктов и медикаментов США.
Нет
Эта информация была получена непосредственно с веб-сайта clinicaltrials.gov без каких-либо изменений. Если у вас есть запросы на изменение, удаление или обновление сведений об исследовании, обращайтесь по адресу register@clinicaltrials.gov. Как только изменение будет реализовано на clinicaltrials.gov, оно будет автоматически обновлено и на нашем веб-сайте. .