Tuberculosis is a global health issue with annually about 1.5 million deaths and 2 billion infected people worldwide.
Extra-pulmonary tuberculosis comprises 13% of all cases of which
tuberculous meningitis is the most severe. It has a high mortality and is often diagnosed once irreversible neurological damage has already occurred. Development of diagnostic and treatment strategies requires a thorough understanding of the pathogenesis of
tuberculous meningitis. This disease is characterized by the formation of a cerebral
granuloma, which is a collection of immune cells that attempt to immunologically restrain, and physically contain bacteria. The
cytokine tumor necrosis factor-α is known for its important role in
granuloma formation. Because traditional experimental animal studies exploring
tuberculous meningitis are difficult and expensive, another approach is needed to begin to address this important and significant disease outcome. Here, we present an in silico model capturing the unique immunological environment of the brain that allows us to study the key mechanisms driving
granuloma formation in time. Uncertainty and sensitivity analysis reveals a dose-dependent effect of
tumor necrosis factor-α on bacterial load and immune cell numbers thereby influencing the onset of
tuberculous meningitis. Insufficient levels result in bacterial overgrowth, whereas high levels lead to uncontrolled
inflammation being detrimental to the host. These findings have important implications for the development of immuno-modulating treatment strategies for
tuberculous meningitis.