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Pre-Diabetes Increases Tuberculosis Disease Severity, While High Body Fat Without Impaired Glucose Tolerance Is Protective.

ABSTRACT: Type 2 diabetes (T2D) is a well-known risk factor for tuberculosis (TB), but little is known about pre-diabetes and the relative contribution of impaired glucose tolerance vs. obesity towards susceptibility to TB. Here, we developed a preclinical model of pre-diabetes and TB. Mice fed a high fat diet (HFD) for 12 weeks presented with impaired glucose tolerance and hyperinsulinemia compared to mice fed normal chow diet (NCD). Infection with M. tuberculosis (Mtb) H₃₇R_v after the onset of dysglycemia was associated with significantly increased lung pathology, lower concentrations of TNF-α, IFN-γ, IFN-β and IL-10 and a trend towards higher bacterial burden at 3 weeks post infection. To determine whether the increased susceptibility of pre-diabetic mice to TB is reversible and is associated with dysglycemia or increased body fat mass, we performed a diet reversal experiment. Pre-diabetic mice were fed a NCD for 10 additional weeks (HFD/NCD) at which point glucose tolerance was restored, but body fat mass remained higher compared to control mice that consumed NCD throughout the entire experiment (NCD/NCD). Upon Mtb infection HFD/NCD mice had significantly lower bacterial burden compared to NCD/NCD mice and this was accompanied by restored IFN-γ responses. Our findings demonstrate that pre-diabetes increases susceptibility to TB, but a high body mass index without dysglycemia is protective. This murine model offers the opportunity to further study the underlying immunological, metabolic and endocrine mechanisms of this association.

SUBMITTER: Sinha R

PROVIDER: S-EPMC8291147 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Pre-Diabetes Increases Tuberculosis Disease Severity, While High Body Fat Without Impaired Glucose Tolerance Is Protective.

Sinha Roma R Ngo Minh Dao MD Bartlett Stacey S Bielefeldt-Ohmann Helle H Keshvari Sahar S Hasnain Sumaira Z SZ Donovan Meg L ML Kling Jessica C JC Blumenthal Antje A Chen Chen C Short Kirsty R KR Ronacher Katharina K

Frontiers in cellular and infection microbiology 20210706

Type 2 diabetes (T2D) is a well-known risk factor for tuberculosis (TB), but little is known about pre-diabetes and the relative contribution of impaired glucose tolerance vs. obesity towards susceptibility to TB. Here, we developed a preclinical model of pre-diabetes and TB. Mice fed a high fat diet (HFD) for 12 weeks presented with impaired glucose tolerance and hyperinsulinemia compared to mice fed normal chow diet (NCD). Infection with M. tuberculosis (Mtb) H37R ...[more]

PMID: 34295838

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Project description:IntroductionImpaired glucose tolerance (IGT) is diagnosed by a standardized oral glucose tolerance test (OGTT). However, the OGTT is laborious, and when not performed, glucose tolerance cannot be determined from fasting samples retrospectively. We tested if glucose tolerance status is reasonably predictable from a combination of demographic, anthropometric, and laboratory data assessed at one time point in a fasting state.MethodsGiven a set of 22 variables selected upon clinical feasibility such as sex, age, height, weight, waist circumference, blood pressure, fasting glucose, HbA1c, hemoglobin, mean corpuscular volume, serum potassium, fasting levels of insulin, C-peptide, triglyceride, non-esterified fatty acids (NEFA), proinsulin, prolactin, cholesterol, low-density lipoprotein, HDL, uric acid, liver transaminases, and ferritin, we used supervised machine learning to estimate glucose tolerance status in 2,337 participants of the TUEF study who were recruited before 2012. We tested the performance of 10 different machine learning classifiers on data from 929 participants in the test set who were recruited after 2012. In addition, reproducibility of IGT was analyzed in 78 participants who had 2 repeated OGTTs within 1 year.ResultsThe most accurate prediction of IGT was reached with the recursive partitioning method (accuracy = 0.78). For all classifiers, mean accuracy was 0.73 ± 0.04. The most important model variable was fasting glucose in all models. Using mean variable importance across all models, fasting glucose was followed by NEFA, triglycerides, HbA1c, and C-peptide. The accuracy of predicting IGT from a previous OGTT was 0.77.ConclusionMachine learning methods yield moderate accuracy in predicting glucose tolerance from a wide set of clinical and laboratory variables. A substitution of OGTT does not currently seem to be feasible. An important constraint could be the limited reproducibility of glucose tolerance status during a subsequent OGTT.

Project description:BackgroundAround 308 million people worldwide are estimated to have impaired glucose tolerance (IGT); 25% to 75% of these will develop diabetes within a decade of initial diagnosis. At diagnosis, half will have tissue-related damage and all have an increased risk for coronary heart disease.ObjectivesThe objective of this review was to assess the effects and safety of Chinese herbal medicines for the treatment of people with impaired glucose tolerance or impaired fasting glucose (IFG).Search strategyWe searched the following databases: The Cochrane Library, PubMed, EMBASE, AMED, a range of Chinese language databases, SIGLE and databases of ongoing trials.Selection criteriaRandomised clinical trials comparing Chinese herbal medicines with placebo, no treatment, pharmacological or non-pharmacological interventions in people with IGT or IFG were considered.Data collection and analysisTwo authors independently extracted data. Trials were assessed for risk of bias against key criteria: random sequence generation, allocation concealment, blinding of participants, outcome assessors and intervention providers, incomplete outcome data, selective outcome reporting and other sources of bias.Main resultsThis review examined 16 trials lasting four weeks to two years involving 1391 participants receiving 15 different Chinese herbal medicines in eight different comparisons. No trial reported on mortality, morbidity or costs. No serious adverse events like severe hypoglycaemia were observed. Meta-analysis of eight trials showed that those receiving Chinese herbal medicines combined with lifestyle modification were more than twice as likely to have their fasting plasma glucose levels return to normal levels (i.e. fasting plasma glucose <7.8 mmol/L and 2hr blood glucose <11.1 mmol/L) compared to lifestyle modification alone (RR 2.07; 95% confidence intervall (CI) 1.52 to 2.82). Those receiving Chinese herbs were less likely to progress to diabetes over the duration of the trial (RR 0.33; 95% CI 0.19 to 0.58). However, all trials had a considerable risk of bias and none of the specific herbal medicines comparison data was available from more than one study. Moreover, results could have been confounded by rates of natural reversion to normal glucose levels.Authors' conclusionsThe positive evidence in favour of Chinese herbal medicines for the treatment of IGT or IFG is constrained by the following factors: lack of trials that tested the same herbal medicine, lack of details on co-interventions, unclear methods of randomisation, poor reporting and other risks of bias.

Dataset Information

Pre-Diabetes Increases Tuberculosis Disease Severity, While High Body Fat Without Impaired Glucose Tolerance Is Protective.

Publications

Pre-Diabetes Increases Tuberculosis Disease Severity, While High Body Fat Without Impaired Glucose Tolerance Is Protective.

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