Abstract

The interplay between tuberculosis and depression has been problematic since the humoralists. Over the centuries similarities in disease management have transpired. With the advent of isoniazid chemotherapy, transformation of tuberculosis patients from morbidly depressive to euphoric was noted. Isoniazid was thereafter widely prescribed for depression: hepatotoxicity ending its use as an antidepressant in 1961. Isoniazid monotherapy led to the emergence of drug resistant tuberculosis, stimulating new drug development. Vastly increased investment into antidepressants ensued thereafter while investment in new drugs for tuberculosis lagged. In the 21st century, both diseases independently contribute significantly to global disease burdens: renewed convergence and the resultant syndemic is detrimental to both patient groups. Ending the global tuberculosis epidemic and decreasing the burden of depression and will require multidisciplinary, patient-centered approaches that consider this combined co-morbidity. The emerging era of big data for health, digital interventions and novel and repurposed compounds promise new ways to treat both diseases and manage the syndemic, but absence of clinical structures to support these innovations may derail the treatment programs for both. New policies are urgently required optimizing use of the current advances in healthcare available in the digital era, to ensure that patient-centered care takes cognizance of both diseases.

Highlights

  • Tuberculosis contributes considerably to human disease burdens

  • Depression is forecast to be the greatest contributor to global disease burdens by 2030 [3]

  • From 1990 to 2007, the prevalence of major depression increased by 33.4%, increasing a further 14.3% over the following 10 years [2], affecting South Asia, Africa and the Middle East (PPP of 6.6), the lowest incidence reported from North America (PPP of 3.7) [5]

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Summary

INTRODUCTION

Tuberculosis contributes considerably to human disease burdens. In 2018, the estimated incidence was 10.0 million cases globally, with 1.45 million deaths [1]; the estimated prevalence, including latent infection, was 1.93 billion in 2017 [2]. Herman Hyman Fox, working at Hoffman-La Roche in New Jersey, studied the semi-carbazones, knowing that they have antituberculotic potential When he investigated these compounds in mice, he coincidently included some of the intermediaries, among which was INH/propiozid. The World Health organization has set the “End. Tuberculosis Strategy” goal to eliminate tuberculosis by 2035, requiring vast investments in the discovery and development of new tools for tuberculosis control, including an effective vaccine [52], but wider understanding of the patient as an individual, obstacles to successful management and why treatment failures occur, and addressing the economic and social determinants of disease, are of equal importance [51, 53]. Deep learning algorithms targeting single nucleotide polymorphisms as genetic biomarkers may predict clinical treatment outcomes and adverse drug reactions in patients with major depressive disorder treated with antidepressants [64]

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