Mechanisms underlying TB-DM comorbidity

Cellular and molecular mechanisms underlying TB-DM comorbidity highlight the complex interaction between tuberculosis (TB) and diabetes mellitus (DM), affecting global health outcomes. Multi-platform approaches including cellular immunology, genomics, transcriptomics, proteomics, lipidomics, and metabolomics provide insights into the inflammatory processes and immune dysfunctions in TB-DM comorbidity. See also: https://lintblab.weebly.com/

Cellular Immunology: The interplay between TB and DM compromises immune cell function, particularly in macrophages and T cells. DM is associated with diminished functionality of macrophages and neutrophils, impaired cytokine signaling, and altered T cell responses, which contribute to increased susceptibility to TB.

Genomics: Studies have identified genetic variants that may predispose individuals to TB-DM, such as polymorphisms in IL-6 and IL-18 genes. These findings support the use of personalized medicine and help identify individuals at risk.

Transcriptomics: Research indicates that TB-DM comorbidity is characterized by chronic inflammation and distinct gene expression patterns that affect the immune response. These variations are particularly pronounced in the regulation of neutrophil and innate immune pathways.

Proteomics: Proteomic analysis has revealed that DM induces changes in the expression of proteins involved in immune responses, potentially leading to novel biomarkers for TB-DM. Elevated levels of proteins related to the complement and coagulation cascades in TB-DM patients suggest links to lipid metabolism dysregulation.

Lipidomics: Altered lipid profiles in TB-DM patients are associated with increased TB risk. Studies have identified specific glycerophospholipids that may serve as biomarkers for TB-DM.

Metabolomics: This approach has identified specific metabolic disruptions in TB-DM patients, such as changes in bile acids and carbohydrate metabolism molecules. These alterations highlight the impact of DM on TB pathophysiology.

Integrative Analysis: Combining data from various omics fields enhances understanding of TB-DM interactions and supports the development of host-directed therapies. Multi-omic studies have identified specific biomarkers and therapeutic targets that can differentiate TB-DM from other conditions and predict treatment outcomes.

Epidemiological data reveal a notable prevalence of DM among TB patients, influenced by factors like age, lifestyle, socio-economic status, family history, and hypertension. Yet, disparities in TB-DM comorbidity across regions remain underexplored, necessitating investment in molecular epidemiology to tailor public health strategies effectively.

The bidirectional relationship between TB and DM complicates clinical management and accelerates disease progression. Research indicates that DM correlates with higher mycobacterial loads and distinctive lung damage, underscoring the need for integrated health approaches that address both conditions simultaneously. Proposed strategies include improved TB screening for DM patients, reciprocal screening, and expanded research into transmission dynamics among patient contacts. Additionally, examining how DM-related multimorbidities affect TB-DM patients' inflammatory profiles could enhance biomarker and treatment target identification.

Advancements in technologies like single-cell analysis could revolutionize our understanding of TB-DM at the cellular level, offering detailed insights into immune cell dysfunction and revealing new therapeutic targets and biomarkers. Furthermore, integrating genetic, molecular, and clinical data to develop predictive scores could transform disease progression and treatment outcome assessments.

The potential development of targeted TB vaccines for populations with compromised immune responses, informed by a deepened understanding of immune dysfunction in TB-DM comorbidity, is also discussed. Moreover, creating comprehensive risk scores that incorporate socio-demographic, lifestyle, and clinical data could refine the precision of public health interventions, taking into account regional variations in TB-DM comorbidity.

The critical need for a synergistic approach that combines epidemiological, clinical, genomic, transcriptomic, proteomic, and lipidomic research to unravel the complexities of TB-DM. The application of multi-omic platforms offers profound opportunities for enhancing disease management and improving global health outcomes by facilitating the development of precise diagnostic tools, personalized treatments, and informed public health strategies. 

Source: Araujo-Pereira, M., Vinhaes, C.L., Barreto-Duarte, B., Villalva-Serra, K., Queiroz, A.T.L., & Andrade, B.B. (2024). Intersecting epidemics: Deciphering the complexities of tuberculosis-diabetes comorbidity. Frontiers in Tuberculosis, 2, Article 1487793. https://doi.org/10.3389/ftubr.2024.1487793