| Literature DB >> 33287713 |
Akhirunnesa Mily1,2, Protim Sarker2, Inin Taznin2, Delwar Hossain3, Md Ahsanul Haq2, S M Mostofa Kamal4, Birgitta Agerberth5, Susanna Brighenti1, Rubhana Raqib6.
Abstract
BACKGROUND: Diabetes mellitus type 2 (DM) may impede immune responses in tuberculosis (TB) and thus contribute to enhanced disease severity. In this study, we aimed to evaluate DM-mediated alterations in clinical, radiological and immunological outcomes in TB disease.Entities:
Keywords: Anti-inflammatory cytokine; Diabetes mellitus; IL-10; Pulmonary pathology; Sputum culture; TB score
Mesh:
Substances:
Year: 2020 PMID: 33287713 PMCID: PMC7722325 DOI: 10.1186/s12879-020-05473-x
Source DB: PubMed Journal: BMC Infect Dis ISSN: 1471-2334 Impact factor: 3.090
Baseline characteristic of the study participantsa
| Variables | TB ( | TB-DM ( | Healty Controls ( | |||
|---|---|---|---|---|---|---|
| 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 (%) | ||||||
| eAFB 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%) | – | |||
aQuantitative data are presented as median ± IQR; Categorical data are presented as n (%). Statistical analysis comparing bTB vs TB-DM, cTB vs HC, and dTB-DM vs HC was done using Chi-square, Kruskal-Wallis and Dunn’s post-test or the Mann-Whitney U-test eSputum samples positive in the GeneXpert MTB/RIF test. AFB: Acid-Fast Bacilli; BCG: Bacillus Calmette–Guérin; BMI: body mass index; SES: socioeconomic status
Fig. 1Flow chart illustrating enrollment and follow-up of TB and TB-DM patients
Fig. 2Glycemic markers in TB and TB-DM patients and in healthy controls (a, b), and correlation of glycemic markers (c, d), homeostatic model assessment of insulin resistance (HOMA-IR) (e) and C-peptide reactivity-insulin resistance (CPR-IR) (f) with time-since–treatment in TB-DM patients. Fasting blood glucose levels (mmol/L) and HbA1c concentrations (%) were assessed in TB (n = 35) and TB-DM (n = 36) patients at enrolment and after 1, 2 and 6 months of anti-TB treatment, and once in healthy controls (n = 20). Plasma insulin levels (pg/mL) and plasma C-peptide levels (pg/mL) were assessed in TB-DM (n = 35) patients at enrolment and after 1, 2 and 6 months of anti-TB treatment. HOMA-IR was calculated using the formula: HOMA-IR = (fasting insulin [pmol/L] × fasting plasma glucose [mmol/L]) / 135). CPR-IR was calculated using the formula: CPR-IR = 20 / (fasting C-peptide [nmol/L] x fasting plasma glucose [mmol/L]). Data are presented as mean withstandard error of mean (a, b) or as mean difference with 95% confidence interval (c, d, e, f). Statistical differences were calculated using multivariate regression, adjusting for age, sex, SES score, BCG vaccination status and baseline BMI (a, b), and Friedman's test (c, d, e, f). *p < 0.05 was considered significant. BMI: body mass index; BCG: Bacillus Calmette–Guérin; HbA1c: glycosylated hemoglobin; SES: socio economic status
Fig. 3BMI and composite TBscore in TB and TB-DM patients. a BMI (kg/m2) and b composite TBscore were assessed in TB (n = 35) and TB-DM (n = 36) patients at enrolment and after 1, 2 and 6 months of anti-TB treatment. BMI was also assessed on one occasion in healthy controls (n = 20). Data is presented as mean with standard error of mean. Statistical differences were calculated using adjusted multivariate regression. The regression model was adjusted for age, sex, SES score and BCG vaccination status. *p < 0.05 was considered significant. BMI: body mass index; BCG: Bacillus Calmette–Guérin; SES: socio economic status
Fig. 4Chest X-ray findings in TB and TB-DM patients. a total percent lung involvement (combined pathology in upper, middle and lower zones of the left and right lungs), b percent lung involvement in the upper zone, c percent lung involvement in the middle zone, and d percent lung involvement in the lower zone was assessed in TB (n = 35) and TB-DM (n = 36) patients at enrolment and after 1, 2 and 6 months of anti-TB treatment. Note that each of the three zones in the two lungs could have a maximum of 100% pathological involvement, and therefore the total percent lung involvement in the upper, middle or lower zones, respectively, could be maximum 100 + 100 = 200% (b-d), while the total percent lung involvement including all three zones in both lungs in a patient could be maximum 3 × 100 × 2 = 600% (a). Data is presented as median values. Statistical differences between the TB and TB-DM group were calculated using the Mann-Whitney U-tests, and p < 0.05* was considered significant
Longitudinal association of lung involvement with TBscore and blood hemogram markers in TB and TB-DM patientsa
| % lung involvementb | ||||
|---|---|---|---|---|
| TB ( | TB-DM ( | |||
| β-coefficient (95% CI) | β-coefficient (95% CI) | |||
| TBscore | −0.003(−0.03, 0.02) | 0.802 | 0.02(−0.01, 0.04) | 0.143 |
| ESR | 0.03(− 0.0003, 0.05) | 0.053 | 0.06 (0.03, 0.09) | < 0.001 |
| Hb | −0.34(− 0.66, − 0.01) | 0.041 | −1.15(−1.80, − 0.49) | 0.001 |
| WBC | 0.32 (0.08, 0.56) | 0.008 | 0.41 (0.13, 0.69) | 0.004 |
| Lymphocyte | −0.05(− 01.2, 0.02) | 0.173 | − 0.14(− 0.23, − 0.05) | 0.002 |
| Neutrophils | 0.06(− 0.003, 0.13) | 0.060 | 0.11 (0.04, 0.18) | 0.002 |
| Monocyte | −0.22(− 0.64, 0.20) | 0.298 | 0.01(− 0.40, 0.41) | 0.980 |
| Platelet | 0.02 (0.01, 0.04) | 0.001 | 0.02 (0.01, 0.03) | 0.005 |
| NLR | 0.09(−0.02, 0.21) | 0.121 | 0.10(−0.11, 0.31) | 0.353 |
| MLR | 8.53(−2.43, 19.49) | 0.127 | 6.07(−0.78, 12.93) | 0.082 |
| PLR | 0.17 (0.07, 0.27) | 0.001 | 0.12 (0.04, 0.20) | 0.003 |
aData were analyzed using Generalized estimating equation (GEE), and the results are expressed as beta β-coefficient and 95% confidence interval (CI). The GEE model was adjusted by age, sex, baseline BMI, SES score, BCG vaccination status and time (to reduce multicollinearity)
bEach of the three zones in the two lungs could have a maximum of 100% pathological involvement, and therefore the total % lung involvement in the upper, middle or lower zones respectively could be maximum 100 + 100 = 200%, while the total % lung involvement including all three zones in both lungs in a patient could be maximum 3 × 100 × 2 = 600%
cp-values demonstrate the significant association of lung involvement and the listed variables in both TB and TB-DM patients
BCG Bacillus Calmette–Guérin, BMI body mass index, CI confidence interval, ESR erythrocyte sedimentation rate, Hb hemoglobin, MLR monocyte-to-lymphocyte ratio, NLR neutrophil-to-lymphocyte ratio, PLR platelet-to-lymphocyte ratio, SES socioeconomic status, WBC white blood cell
Fig. 5mRNA profiling of PBMCs and sputum cell samples from TB and TB-DM patients. Quantitative mRNA expression of CD4, CD8, IL-1β, TNF-α and IL-10 in PBMCs (a-e) and sputum cell samples (f-j) from TB (n = 7) and TB-DM (n = 15) patients were analyzed at enrolment and after 1 and 2 months of anti-TB treatment. Data is presented as median values and statistical differences between the TB and TB-DM group were calculated using the Mann-Whitney U-tests, and *p < 0.05 was considered significant. Note that mRNA data is presented in dot-plot graphs with a log-scale, while the statistical analyses were performed on non-transformed data. PBMCs: Peripheral blood mononuclear cells
Fig. 6Correlation of sputum IL-10 transcript with fasting blood glucose and HbA1c levels. IL-10 transcript levels in sputum samples from TB and TB-DM patients combined (n = 22) were correlated with fasting blood glucose at (a) baseline and after (b) 1 month and (c) 2 months, and HbA1c levels at (d) baseline and after (e) 1 month and (f) 2 months of anti-TB treatment. Data is presented as median and the correlation was calculated using Spearman’s correlation test. *p < 0.05 was considered significant