Effect of Mycobacterial Infection on Immune Status (EMIIS)

June 4, 2026 updated by: 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.

Study Overview

Status

Status

Indicates the current recruitment status or the expanded access status.
Recruiting

Conditions

Conditions

The disease, disorder, syndrome, illness, or injury that is being studied. On ClinicalTrials.gov, conditions may also include other health-related issues, such as lifespan, quality of life, and health risks.

Study Type

Study Type

Describes the nature of a clinical study. Study types include interventional studies (also called clinical trials), observational studies (including patient registries), and expanded access.
Observational

Enrollment (Estimated)

Enrollment

The number of participants in a clinical study. The "anticipated" enrollment is the target number of participants that the researchers need for the study.
120

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact

The name and contact information for the person who can answer enrollment questions for a clinical study. Each location where the study is being conducted may also have a specific contact, who may be better able to answer those questions.

Study Contact Backup

Study Locations

  • China
      • Ningbo, China
        • Recruiting
        • The First Affiliated Hospital of Ningbo University

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Eligibility Criteria

The key requirements that people who want to participate in a clinical study must meet or the characteristics they must have. Eligibility criteria consist of both inclusion criteria (which are required for a person to participate in the study) and exclusion criteria (which prevent a person from participating). Types of eligibility criteria include whether a study accepts healthy volunteers, has age or age group requirements, or is limited by sex.

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Probability Sample

Study Population

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.

Description

Inclusion Criteria and Exclusion Criteria:

Inclusion Criteria：

  1. Age ≥ 18 years, all genders and races accepted.
  2. Patients with active pulmonary tuberculosis diagnosed clinically or by bronchoscopy within less than 1 week.
  3. Patients with latent tuberculosis infection (positive T-SPOT test but no evidence of active tuberculosis infection).
  4. Patients with tuberculous pleurisy with onset within less than 1 week.
  5. Voluntarily join this study and sign the informed consent form.
  6. Patients whose drug susceptibility test or NGS results indicate resistance to at least isoniazid and rifampicin (MDR-TB).
  7. Patients whose drug susceptibility test or NGS results indicate sensitivity to first-line anti-tuberculosis drugs.
  8. Patients whose drug susceptibility test or NGS results indicate resistance to only one anti-tuberculosis drug.
  9. Patients with newly identified nontuberculous mycobacterial infection (within less than 1 week) by sputum culture or NGS.

Exclusion Criteria：

  1. Immunosuppressive conditions including HIV infection, long-term use (>1 month) of immunosuppressive agents or corticosteroids, severe malnutrition, etc.
  2. Concurrent other lung diseases, severe liver or kidney dysfunction, severe endocrine diseases, hematological diseases, or malignant tumors that may affect the study outcomes.
  3. Patients with diabetes mellitus.
  4. Pregnant or lactating women.
  5. Patients unable or unwilling to provide informed consent, or with poor compliance.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort

Group / Cohort

A group or subgroup of participants in an observational study that is assessed for biomedical or health outcomes.
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.
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.
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.
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.
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.

What is the study measuring?

Primary Outcome Measures

Primary Outcome Measures

In a clinical study's protocol, the planned outcome measure that is the most important for evaluating the effect of an intervention/treatment. Most clinical studies have one primary outcome measure, but some have more than one.
Outcome Measure
Measure Description
Time Frame
To establish a multi-immune pathway interaction network and composite biomarkers in mycobacterial infection thing
Time Frame: 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

Secondary Outcome Measures

Secondary Outcome Measures

In a clinical study's protocol, a planned outcome measure that is not as important as the primary outcome measure for evaluating the effect of an intervention but is still of interest. Most clinical studies have more than one secondary outcome measure.
Outcome Measure
Measure Description
Time Frame
Immune cell subsets and mechanisms of possible effects of anti-tuberculosis drugs
Time Frame: 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
Differences in immune subsets between normal persons and patients with active pulmonary tuberculosis
Time Frame: 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
To explore whether the peripheral blood before treatment contains a certain marker can predict the short-term efficacy
Time Frame: 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
Comparison of the dynamic changes of immune subsets in peripheral blood and pleural effusion of TP patients before and after treatment
Time Frame: 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.
3 days before treatment and 2 months after treatment
To explore the differences of peripheral blood immune subsets between TP patients and healthy people before treatment
Time Frame: 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.
3 days before treatment and 2 months after treatment
To explore the metabolic differences of three major nutrients between TP patients and healthy people before treatment
Time Frame: 3 days before treatment and 2 months after treatment
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.
3 days before treatment and 2 months after treatment
Differences in metabolic function between multidrug-resistant tuberculosis group and drug-sensitive tuberculosis group
Time Frame: 3 days before treatment and 2 months after treatment
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.
3 days before treatment and 2 months after treatment
Influence of immune status on the efficacy of NTM
Time Frame: 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

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Sponsor

The organization or person who initiates the study and who has authority and control over the study.
First Affiliated Hospital of Ningbo University

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

Study Start

The actual date on which the first participant was enrolled in a clinical study. The "anticipated" study start date is the date that the researchers think will be the study start date.
July 9, 2025

Primary Completion (Estimated)

Primary Completion

The date on which the last participant in a clinical study was examined or received an intervention to collect final data for the primary outcome measure. Whether the clinical study ended according to the protocol or was terminated does not affect this date. For clinical studies with more than one primary outcome measure with different completion dates, this term refers to the date on which data collection is completed for all the primary outcome measures. The "anticipated" primary completion date is the date that the researchers think will be the primary completion date for the study.
July 20, 2026

Study Completion (Estimated)

Study Completion

The date on which the last participant in a clinical study was examined or received an intervention/treatment to collect final data for the primary outcome measures, secondary outcome measures, and adverse events (that is, the last participant's last visit). The "anticipated" study completion date is the date that the researchers think will be the study completion date.
July 20, 2026

Study Registration Dates

First Submitted

First Submitted

The date on which the study sponsor or investigator first submitted a study record to ClinicalTrials.gov. There is typically a delay of a few days between the first submitted date and the record's availability on ClinicalTrials.gov (the first posted date).
May 19, 2026

First Submitted That Met QC Criteria

First Submitted That Met QC Criteria

The date on which the study sponsor or investigator first submits a study record that is consistent with National Library of Medicine (NLM) quality control (QC) review criteria. The sponsor or investigator may need to revise and submit a study record one or more times before NLM's QC review criteria are met. It is the responsibility of the sponsor or investigator to ensure that the study record is consistent with the NLM QC review criteria.
June 4, 2026

First Posted (Actual)

First Posted

The date on which the study record was first available on ClinicalTrials.gov after National Library of Medicine (NLM) quality control (QC) review has concluded. There is typically a delay of a few days between the date the study sponsor or investigator submitted the study record and the first posted date.
June 10, 2026

Study Record Updates

Last Update Posted (Actual)

Last Update Posted

The most recent date on which changes to a study record were made available on ClinicalTrials.gov. There may be a delay between when the changes were submitted to ClinicalTrials.gov by the study's sponsor or investigator (the last update submitted date) and the last update posted date.
June 10, 2026

Last Update Submitted That Met QC Criteria

Last Update Submitted That Met QC Criteria

The most recent date on which the study sponsor or investigator submitted changes to a study record that are consistent with National Library of Medicine (NLM) quality control (QC) review criteria. It is the responsibility of the sponsor or investigator to ensure that the study record is consistent with the NLM QC review criteria.
June 4, 2026

Last Verified

Last Verified

The most recent date on which the study sponsor or investigator confirmed the information about a clinical study on ClinicalTrials.gov as accurate and current. If a study with a recruitment status of recruiting; not yet recruiting; or active, not recruiting has not been confirmed within the past 2 years, the study's recruitment status is shown as unknown.
June 1, 2026

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

Other Study ID Numbers

Identifiers or ID numbers other than the NCT number that are assigned to a clinical study by the study's sponsor, funders, or others. These numbers may include unique identifiers from other trial registries and National Institutes of Health grant numbers.
  • 2025-157A-01

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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