Research

Doctoral Research

Amyloidosis is defined by the deposition of insoluble amyloid fibrils in the extracellular spaces of organs and tissues. These amyloid fibrils disrupt the normal function of these organs, frequently resulting in death. Amyloid A amyloidosis (AA amyloidosis) is a fatal systemic disorder that occurs secondary to chronic inflammatory diseases such as Rheumatoid Arthritis (RA), Tuberculosis (TB), and Inflammatory bowel disease (IBD) (IBD). These inflammatory diseases result in the continuous production of cytokines such as TNF-α, IL-1, and IL-6, which act on hepatocytes, leading to increased production of serum amyloid A (SAA) protein by liver. These increased levels of SAA trigger their cleavage by proteases to generate amyloidogenic fragments that get deposit in various organs like the spleen, liver, and kidney and lead to organ failure. However, the various mechanisms of formation, distribution, and deposition of AA amyloids are not fully explored yet. Most of the current treatment strategies work on the principle of inhibiting SAA production by blocking TNF-α, IL-1, or IL-6 receptors. But there is no definite cure for this disease. One of the reasons for this lack is the unknown and unexplored natural history of amyloid formation in chronic inflammatory conditions.

According to WHO, Tuberculosis (TB), a chronic inflammatory condition caused by Mycobacterium tuberculosis, is one of the top 10 causes of death worldwide. Approximately 1.5 million people die from TB every year, with India reporting the highest number of TB patients (27%). Epidemiological studies revealed that a significant number of TB patients also show secondary amyloid formation, suggesting the possibility of a correlation between the two diseases. Therefore, uncovering the mechanism of SAA degradation and aggregation in TB animal models is imperative for preventing the deaths of TB patients due to amyloidosis. It would further aid clinicians in the early diagnosis and treatment of the disease and help identify novel biomarkers in the event of plausible overlaps.