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Prevalence of Auto-antibodies in Pulmonary Tuberculosis

Abstract The relationship between pulmonary tuberculosis and auto-antibodies remains undefined. In a study of 75 patients with pulmonary tuberculosis and 75 controls, the prevalence of auto-antibodies was assessed in a reference laboratory using a comprehensive panel with standardized methodology. No significant relationship was found between auto-antibody prevalence and pulmonary tuberculosis.

Autoimmune disorders represent a broad spectrum of diseases characterized by a pathological immune response directed at self-antigens and are hypothesized to arise from a constellation of genetic, hormonal, immunological, and environmental factors [1]. Certain chronic infections are thought to trigger the production of auto-antibodies through molecular mimicry or exuberant and persistent host responses that result in auto-immune or inflammatory pathologies [2].
Tuberculosis (TB) is the most common chronic bacterial infection worldwide, with an estimated 10.2 million incident cases and 10.1 million prevalent cases per year [3]. Like other infections, it has been associated with autoimmune manifestations, including nodular vasculitis [4]. TB has reportedly been linked with autoimmune disorders such as Sjögren's syndrome, systemic lupus erythematosus, rheumatoid arthritis, dermatomyositis, and polymyositis [5]. However, the nature, directionality, and robustness of this association remain unknown.
Although it is biologically plausible for patients with TB to develop auto-antibodies, the extent and magnitude to which this phenomenon occurs are unknown. The relationship between pulmonary TB and auto-antibodies remains undefined due to conflicting reports in the literature, inconsistent test selection, and nonstandardized testing methodology. The objective of this study was to determine if active TB is associated with an increased prevalence of auto-antibodies using a comprehensive panel with standardized methodology performed in a reference laboratory.

METHODS
We performed a cross-sectional study involving patients evaluated for active pulmonary tuberculosis from Bangladesh, South Africa, Peru, and Uganda. Patients 18 years of age or older who were treated at 1 of the study sites and provided written informed consent to participate were eligible. Patients were included in this study if they provided sputum samples for mycobacterial culture. Baseline characteristics were collected at the time of medical assessment. Covariates of interest included age, sex, and relevant medical comorbidities such as HIV co-infection status and chronic rheumatological diseases. Patients with a diagnosis of active pulmonary TB were compared with controls who were selected from a similar patient population and who sought medical attention due to a febrile respiratory illness. The subjects in the control group had multiple negative sputum cultures for Mycobacterium tuberculosis.
To test the hypothesis that patients with active TB have a higher prevalence of auto-antibodies, we performed comprehensive serological testing in our patient population. Patient samples were obtained at the time of presentation to medical care and before starting antimicrobial therapy. From a review of the literature, we identified several serological markers that could be produced in response to a chronic bacterial infection. complete list of all antibodies tested, their methods of assessment, and cutoffs for positivity. These assays were performed in a blinded fashion at the Mitogen Diagnostic Laboratory in Calgary, Alberta, Canada.
The relationship between different serological markers and tuberculosis was first analyzed using direct graphical visualization, followed by a classical hypothesis testing framework using the Fisher exact and Mann-Whitney U tests. Subsequently, sensitivity analysis was performed using multiple machine learning algorithms. First, Lasso logistic regression was used. The Lasso method allows for automatic variable selection and shrinkage, bypassing multiple comparison and effect inflation problems inherent with methods like stepwise regression. Second, 2 highly nonparametric tree-based methods were implemented: random forests and hierarchical cluster analysis (HCA). Finally, principal component analysis (PCA) was performed, and the first 3 principal components were plotted against each other to determine if they could discriminate between TB patients and controls. A detailed explanation of each procedure can be found in the references [8,9]. All analyses were performed using the base R statistical package (3.2.0) and the glmnet library (2.0-10). The study was approved by the FIND Office for Human Research Studies.

RESULTS
One hundred fifty patients were selected to participate in the study and provided serum samples for this analysis. Patient characteristics are presented in Table 1. The median age of the cohort at the time of testing was 33 years; 17 patients (11.3%) had a previous history of active TB, and 65 (43.3%) had a history of Bacillus Calmette-Guérin vaccination. In total, 75 patients were diagnosed with active pulmonary tuberculosis, and 75 presented with an acute febrile respiratory illness and were found to have an alternative diagnosis (other than TB). The most common alternate diagnoses in the control group were viral and bacterial respiratory tract infections. No patient had a reported history of HIV infection or of a primary rheumatological condition, including granulomatosis with polyangitis.
A detailed summary of serum auto-antibody testing results is shown in Table 2. When comparing cases and controls, the prevalence of ANA was not statistically different regardless of staining pattern: 46.7% of cases and controls had a nuclear pattern, 14.7% of cases and 18.7% of controls had a cytoplasmic pattern, and 30.7% of cases and 24.0% of controls had a mitotic pattern.
Among less frequently tested auto-antibodies, both groups had a similar prevalence of positive results (see Table 2 for   details). The highest prevalence of auto-antibodies was found for LAMP2 (24.0% in cases, 39.7% in controls), followed by DFS70 (21.3% in cases, 20.0% in controls) and RNP-A (4.0% in cases, 12.0% in controls). No patient tested positive for the following antibodies: HCP2, nucleosome, PCNA, Rpp38, Sm-Peptide, and VCP2. After Bonferroni correction, no single test was found to be statistically different between groups. Primary analysis using hypothesis testing and visual inspection did not reveal any statistically significant relationship between the diagnosis of tuberculosis and immune profiles. Variable selection using lasso regression also could not identify variables with significant discriminatory power. Random forests and HCA were used as nonparametric methods but failed to identify clusters of patients based on immune profile and tuberculosis diagnosis. PCA found no relationship between the covariates and the outcome of interest. Please see the Supplementary Data for additional details.

DISCUSSION
Despite effective antimicrobial therapy, TB remains a significant cause of morbidity and mortality and mortality worldwide. Although TB has been associated with autoimmune manifestations and rheumatological conditions, our data reveal that it is not associated with conventional or novel serological markers of autoimmunity. Our results contradict previous reports [6,7] and suggest that active TB is not associated with the presence of ANCA, ACA, and Scl-70 positivity.  Several studies have linked TB with the development of auto-antibodies. Several mechanisms have been proposed to explain this association, including molecular mimicry. In vitro data suggest homology between species in cell wall glycolipids and DNA [10], bystander activation of CD8+ lymphocytes [11], and TLR agonism [12]. However, conflicting data exist regarding the association between TB and clinical autoimmune disease; our patient population did not have any reported rheumatological conditions. It is of note that our population was tested before the onset of treatment, which could theoretically affect auto-antibody production. It is possible that antimycobacterial treatment increases auto-antibody production by exposing novel antigens, which could explain a higher prevalence of certain markers of auto-immunity in other studies [13].
Our results must be interpreted in the context of the study characteristics. We were unable to follow patients longitudinally to assess for the development of auto-antibodies or auto-immune manifestations. Furthermore, all samples in our study were obtained from passive case finding. As such, it was not possible to determine the duration of disease before seeking medical attention. From epidemiologic studies, those diagnosed passively tend to have more severe disease and a longer duration of symptoms than those detected through active case finding, such as immigrant screening [14]. We also evaluated auto-antibodies in a relatively small patient population with imbalances in baseline characteristics between groups. However, there is no reason a priori to suggest that these imbalances would explain the negative results of our study.
We selected patients with active TB from 4 geographically diverse areas and patients with febrile respiratory conditions as opposed to healthy volunteers. Due to the limited diagnostic capacity in many of the study centers, we were unable to diagnose a microbial pathogen in the control population. We performed the most thorough auto-immune workup in patients with active TB to date with a complete panel of novel serological assays and assessed them in a blinded fashion in a reference laboratory. In conclusion, we did not observe an association between serological markers of auto-immunity and active TB when compared with patients with acute febrile respiratory illnesses.