The Evolution of Diagnostic Techniques in the Paleopathology of Tuberculosis: A Scoping Review

Abstract

Tuberculosis (TB) is an ancient chronic infectious disease that remains a global health concern. In human remains, the most common and characteristic clinical signs are the skeletal modifications involving the spine, such as in Pott's disease. Diagnosing TB in ancient human remains is challenging. Therefore, in this systematic review, the authors investigated the studies assessing molecular diagnosis of Pott's disease in ancient human remains with the intention to survey the literature, map the evidence, and identify gaps and future perspectives on TB in paleopathology. Our systematic review offers a full contextualization of the history of Pott's disease in ancient times. Our search strategy was performed between August 2022 and March 2023. The authors initially identified 340 records, and 74 studies were finally included and assessed for qualitative analysis. Due to non-specific clinical signs associated with TB, how best to diagnose tuberculosis in human remains still represents a central point. Nevertheless, ancient DNA (aDNA) analysis, lipid biomarkers, and spoligotyping might be extremely useful tools in the study of TB in human remains. Moreover, we propose the extraction and study of immune response genes involved in innate and adaptive immunity versus Mycobacterium spp. as an innovative and vastly overlooked approach in TB paleopathology. Complementary methodologies should be integrated to provide the best approach to the study of TB in human remains.

Keywords: Mycobacterium Tuberculosis Complex (MTBC); Tuberculosis; ancient DNA; human remains; spondylodiscitis.

Figure 1.

Flowchart of the Reporting items for the systematic review adapted from the Preferred reporting items for systematic reviews (PRISMA) statement [44]. Researchers initially identified 340 records; 74 were included and further processed using the open, online Research Screener machine learning tool (Research Screener, 2021) and evaluated for the qualitative synthesis using the NVivo qualitative data analysis software (QSR International Pty, Ltd., Melbourne, VIC, Australia).

Figure 2.

Node diagrams based on NVivo qualitative data analysis software output (QSR International Pty, Ltd., Melbourne, VIC, Australia). The larger boxes have been used to identify themes, the smaller to define subthemes.