TuberculosisEMIISNCT07638670
Effect of Mycobacterial Infection on Immune Status
An observational study of Tuberculosis, run by First Affiliated Hospital of Ningbo University at 1 site in China.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Tuberculosis
- How many people
- 120 participants
- Where
- 1 siteChina
- Study dates
- 9 Jul 2025to 20 Jul 2026
- How long will I take part?
- 60 Days
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
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.
Who may be able to join
- 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).
Show all 9Show fewer
- 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.
Who cannot join
- 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.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
China1 site, 1 recruiting
- Recruiting
The First Affiliated Hospital of Ningbo University
Ningbo
About this study
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.
- Conditions
- Tuberculosis
- Medical subject headings
- Tuberculosis
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| 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 being measured
The primary outcome is the main question the study is designed to answer.
To establish a multi-immune pathway interaction network and composite biomarkers in mycobacterial infection thing
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.
Measured: 3 days before treatment and 2 months after treatment
Secondary outcomes (8)
Immune cell subsets and mechanisms of possible effects of anti-tuberculosis drugs
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.
Measured: 3 days before treatment and 2 months after treatment
Differences in immune subsets between normal persons and patients with active pulmonary tuberculosis
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.
Measured: 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
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.
Measured: 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
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.
Measured: 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
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.
Measured: 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
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.
Measured: 3 days before treatment and 2 months after treatment
Differences in metabolic function between multidrug-resistant tuberculosis group and drug-sensitive tuberculosis group
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.
Measured: 3 days before treatment and 2 months after treatment
Influence of immune status on the efficacy of NTM
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.
Measured: 3 days before treatment and 2 months after treatment
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted10 Jun 2026
- Study start9 Jul 2025
- Primary completion20 Jul 2026 (estimated)
- Study completion20 Jul 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for TuberculosisStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 120 participants (estimated)
- Target duration
- 60 Days
Sponsor and investigators
- Lead sponsor
- First Affiliated Hospital of Ningbo University
- Sponsor type
- Research network
- Responsible party
- Principal investigator, Chao Cao, Ph.D., First Affiliated Hospital of Ningbo University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07638670
- Sponsor's protocol ID
- 2025-157A-01
- Acronym
- EMIIS
- Status last verified
- Jun 2026
- First submitted
- 19 May 2026
- Last updated
- 10 Jun 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 10 Jun 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Effect of Mycobacterial Infection on Immune Status
- ClinicalTrials.gov ID
- NCT07638670
- Acronym / sponsor ID
- EMIIS / 2025-157A-01
- Conditions
- Tuberculosis
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 120 participants (estimated)
- Lead sponsor
- First Affiliated Hospital of Ningbo UniversityResearch network
- Study start
- 9 Jul 2025 (actual)
- Primary completion
- 20 Jul 2026 (estimated)
- Study completion
- 20 Jul 2026 (estimated)
- First posted
- 10 Jun 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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 design
- Observational model
- Cohort
- Time perspective
- Prospective
- Target follow-up
- 60 Days
- Number of arms
- 5
| Arm | Type | Receives |
|---|---|---|
| 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. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- 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.
Key inclusion criteria (9 listed)
- 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.
Key exclusion criteria (5 listed)
- 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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
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.
8 secondary outcomes
Immune cell subsets and mechanisms of possible effects of anti-tuberculosis drugs
Time frame: 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
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
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
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
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
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
Influence of immune status on the efficacy of NTM
Time frame: 3 days before treatment and 2 months after treatment
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 10 Jun 2026.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Tuberculosis, run by First Affiliated Hospital of Ningbo University at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 9 inclusion and 5 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 10 Jun 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Chao Cao (+86-0574-87089878, caodoctor@163.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
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). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 10 Jun 2026.