Patients and treatment
This observational study was conducted in two tertiary care hospitals in Dhaka from June 2014 to May 2017. TB patients (n = 40) were recruited from the National Institute of the Diseases of the Chest and Hospital (NIDCH) and TB-DM patients (n = 40) from Bangladesh Institute of Research and Rehabilitation for Diabetes, Endocrine and Metabolic Disorders (BIRDEM). Age- and sex-matched healthy individuals (n = 20) were randomly recruited as controls. Diabetes status was defined (WHO criteria) as patients having either a fasting blood glucose concentration ≥ 7 mmol/liter or HbA1c ≥ 6.5%. Inclusion criteria: adult males and females, age 18–60 years, newly diagnosed TB using sputum-smear microscopy and/or GeneXpert MTB/RIF and a history of diabetes for ≤ 5 years (TB-DM group). Exclusion criteria: previous history of TB, systemic or miliary TB, > 1 week of anti-TB treatment, pregnancy, history of type 2 DM for ≥ 9 years, and concomitant illnesses such as cardiovascular, liver or kidney diseases, cancer or HIV infection.
Standard anti-TB treatment involved directly observed therapy short-course (DOTS) regimen consisting of isoniazid, rifampicin, pyrazinamide and ethambutol for 2 months followed by isoniazid and rifampicin for subsequent 4 months. At enrollment, DM patients received different types of anti-diabetic medications including metformin hydrochloride (n = 3), insulin (n = 29), a combination of metformin and insulin (n = 7) or other drugs (n = 1).
Clinical Samples And Procedures
After enrolment, socio-economic status (SES), body weight, height, clinical history including duration of illness, history of contact with active TB cases, Bacillus Calmette–Guérin (BCG) vaccination, smoking habits and medication history (TB-DM patients) were recorded. SES was estimated utilizing a wealth index, generated through principal component analysis of household assets [29]. At baseline, and months- 1, -2 and − 6 after initiation of standard anti-TB treatment, clinical evaluation (mentioned in Table 1 and Table S1) and radiological examinations were performed.
Table 1
Baseline characteristic of the study participants
Variables | TB (n = 40) | TB-DM (n = 40) | p-valuea | Healty Controls (n = 20) | p-valueb | p-valuec |
Sex, Male (n, %) | 29 (75.5) | 39 (97.5) | 0.0024 | 14 (70.0) | 0.466 | < 0.001 |
Age (years) | 26.6 ± 7.6 | 40.1 ± 8.8 | < 0.0001 | 32.5 ± 6.3 | 0.036 | 0.030 |
BMI (Kg/m2) | 17.6 ± 2.7 | 21.7 ± 2.5 | < 0.001 | 26.1 ± 3.9 | < 0.001 | < 0.005 |
Family SES | | | | | | |
1st tertile (poor), n (%) | 19 (47.5) | 8 (20.00) | | 0 | | |
2nd tertile (middle), n (%) | 13 (32.5) | 15 (37.5) | | 3 | | |
3rd tertile (rich), n (%) | 8 (20.00) | 17 (42.5) | | 17 | | |
BCG vaccination status, n (%) | 23 (57.5) | 35 (87.5) | < 0.0025 | 18 (90.0) | 0.023 | 0.775 |
History of contact with active cases | 19 (54.3%) | 16 (45.7%) | 0.255 | - | | |
Duration of Symptom (days) | 61(30, 105.5) | 75.5(60, 121) | 0.087 | - | | |
Sputum smear results (AFB), n (%) | | | | | | |
dAFB negative | 0 | 2 (5%) | | - | | |
1 + AFB | 9 (22.5%) | 10 (25.0%) | | - | | |
2 + AFB | 11 (27.5%) | 9 (22.5%) | | - | | |
3 + AFB | 20 (50.0%) | 19 (47.5%) | | - | | |
Quantitative data are presented as median ± IQR; Categorical data are presented as n (%). Statistical analysis comparing aTB vs TB-DM, bTB vs HC, and cTB-DM vs HC was done using Chi-square, Kruskal-Wallis and Dunn´s post-test or the Mann-Whitney U-test. AFB: Acid-Fast Bacilli; BCG: Bacillus Calmette–Guérin; BMI: body mass index; SES: socioeconomic status. dSputum samples positive in the GeneXpert MTB/RIF test |
Fasting blood and sputum samples were collected from the patients at baseline and at follow up visits. Healthy controls provided a fasting blood sample once. Blood glucose and HbA1c level were measured using Clinical Chemistry Analyzer (Cobas C311, Roch Diagnostics GmbH, Mannheim, Germany). Whole blood was routinely analyzed for erythrocyte sedimentation rate (ESR) using ESR analyser (SRS 100/II, Greiner Bio-One GmbH, Kremsmunster, Austria) and complete blood count (CBC) using automated hematology analyzer (XN-1000, Sysmex Corporation, Kobe, Japan). CBC assessment included total and differential blood cell counts (Table S2) and hemoglobin concentration. Peripheral blood mononuclear cells (PBMC) and plasma were isolated from heparinized blood using Ficoll-Paque PLUS (GE Healthcare, Uppsala, Sweden) density gradient centrifugation. Plasma levels of metabolic hormones insulin and C-peptide were measured by Luminex assay using Bio-Plex Diabetes kit (Bio-Rad Laboratories, Inc. USA). Sputum samples were used for sputum-smear microscopy and culture. PBMC and one part of sputum were stored at -80 °C in 1 ml of RNAlater (Qiagen GmbH, Hilden, Germany) for mRNA analysis.
Clinical Composite Tb Score
A modified clinical composite TB score was determined for patients based on the presence of typical TB symptoms: fever, cough, chest pain, night sweats, hemoptysis, anemia, anorexia, weight loss and severity of lung pathology. Symptoms were recorded and scored as present (1) or absent (0) as previously described [30]. Lung involvement was scored based on the tertile values; 1st tertile score: 1, 2nd tertile score: 2 and the highest tertile score: 3. According to this scoring system, the highest expected score was 11.
Mtb Sputum-smear Microscopy, Sputum-culture And The Xpert Mtb/rif Assay
Sputum-smear microscopy was conducted at the NIDCH or BIRDEM, while Mtb culture was performed in the Mycobacteriology laboratory at icddr,b. Ziehl-Neelsen staining was applied to detect and grade Acid fast bacilli by smear microscopy. Decontaminated sputum pellets were cultured on Lowenstein-Jensen (L-J) slants, which were examined weekly until Mtb colonies were detected to confirm the diagnosis of TB disease. The Xpert MTB/RIF assay was performed using sputum from all TB patients at NIDCH or BIRDEM to rule out rifampicin resistance in the patients following NTP guidelines in Bangladesh. Drug susceptibility testing was not done in the isolated Mtb strains as it is not a requirement by NTP.
Chest X-ray
For lung pathology analysis, a semi-quantitative visual scoring system of 2-dimensional chest x-rays was used as previously reported [31, 32] with some modifications. The lung field was divided into three zones: upper, mid and lower zones. Presence of nodules, patchy or confluent consolidations and cavitations were recorded in each of the three zones. The effusion volume, extent of opacification, cavitation or additional pathology were graded as the percentage of the affected lung. The percent (%) affected area in each zone was scored numerically as: no involvement (0 points); 0.1–33.3% (1 point); 33.4–66.6% (2 points); 66.7–100% (3 points) of pulmonary involvement; finally, the total percentage of the affected lung was calculated.
Mrna Extraction And Real-time Pcr
mRNA analysis of PBMCs and sputum cells was conducted to assess inflammation in the peripheral circulation compared to the local site of Mtb infection. mRNA was extracted using Ambion RiboPure RNA extraction kit (Life Technologies, Vilnius, Lithuania). cDNA conversion was performed using a SuperScript cDNA conversion kit (Invitrogen, Carlsbad, CA). The target genes (CD4, CD8, IL-10, IL-1β, TNF-α and matrix metalloproteinase (MMP)-9, and house-keeping gene (18srRNA) were amplified using Taqman gene expression mastermix and primers in the QuantStudio 5 Real-Time PCR System (Applied Biosystems, Foster City, CA). The cycle threshold (Ct) values for target genes were normalized to 18srRNA and relative mRNA expression was determined using the 2−ΔΔCT method. mRNA analysis of sputum samples was performed at baseline, month-1 and month- 2, since most TB patients were unable to produce sputum after 6 months.
Sample Size Calculation
This was an exploratory pilot study, where we aimed to investigate immunological responses in patients with TB-DM compared to TB patients. In general, simulation studies have identified samples size requirements of > 20 for conducting more power-full parametric analyses even when the data is non-normally distributed. Human clinical data tends to be variable, involving patients or volunteers > 30. Based on our previous experiences of TB studies in high-endemic countries [33–37], inclusion of patient numbers > 20 in each sub-group enabled parametric analyses, while smaller sub-group analyses were performed using non-parametric methods. Assuming an initial sample size of 30, accounting for loss to follow-up of 15% and low quality or insufficient clinical materials in another 10% of the patients, we used a sample size of n = 40 in the TB-DM and TB groups.
Statistical analysis
Data is presented as mean and standard deviation (SD) or median and interquartile range (IQR) for continuous, and numbers with percentages for categorical variables. Statistical significance was determined using non-parametric Kruskal-Wallis test with Dunn’s post-test (comparing more than two unmatched groups), Mann-Whitney test (comparing two unmatched groups) and Friedman test with Dunn’s multiple comparison test (comparing non-parametric one-way repeated measurements). The Chi-square test was used to compare the proportion of patients having TB symptoms between TB and TB-DM groups at baseline. Multivariable regression model and GEE (related to lung pathology only) were used to estimate the difference in outcome variables between the TB-DM and TB groups, and data was adjusted for covariates (age, sex, BCG vaccination status, baseline body mass index (BMI) and SES score). The GEE model (beta (β) value and 95% confidence interval (CI)) were created with an interaction (follow-up month × groups) to analyze changes in blood hemagram markers and percent lung involvement across time by group status. This analysis was performed on baseline, and three follow up visits, with the following predictors: Time (months- 0, 1, 2 and 6), group, and an interaction term of these two (visit month × group). Covariates that influenced the model R2 by 5% or more, were selected to avoid colinearity. To evaluate within group changes in TB score, BMI, radiological feature, blood glucose, HbA1c and CBC, the analyses were performed by using 2-way repeated measure Analysis of variance (ANOVA). Spearman´s correlation test was used for the correlation analyses. Stata/IC (v.13, Stata Corp., LP, College Station, Texas, USA) and GraphPad Prism 7.05 were used for statistical analysis. A P-value < 0.05 was considered as significant.