Algorithm Design for a Cytokine Release Assay of Antigen-Specific In Vitro Stimuli of Circulating Leukocytes to Classify Leprosy Patients and Household Contacts

Abstract

Background Immunological biomarkers have often been used as a complementary approach to support clinical diagnosis in several infectious diseases. The lack of commercially available laboratory tests for conclusive early diagnosis of leprosy has motivated the search for novel methods for accurate diagnosis. In the present study, we describe an integrated analysis of a cytokine release assay using a machine learning approach to create a decision tree algorithm. This algorithm was used to classify leprosy clinical forms and monitor household contacts. Methods A model of Mycobacterium leprae (M. leprae) antigen-specific in vitro assay with subsequent cytokine measurements by ELISA was employed to measure the levels of TNF, IFN-γ, IL-4, and IL-10 in culture supernatants of peripheral blood mononuclear cells from leprosy patients, healthy controls as well as household contacts. Receiver Operating Characteristic (ROC) curve analysis was carried out to define each cytokine's global accuracy and performance indices to identify clinical subgroups. Results Data demonstrated that TNF [Control Culture (CC): AUC=0.72; antigen-stimulated culture (Ml): AUC=0.80] and IL-10 (CC: AUC=0.77; Ml: AUC=0.71) were the most accurate biomarkers to classify subgroups of household contacts and leprosy patients, respectively. Decision tree classifier algorithms were for TNF analysis categorized subgroups of household contacts according to the operational classification with moderate accuracy (CC:79%, 48/61, and Ml:84%, 51/61). Additionally, IL-10 analysis categorized leprosy patients' subgroups with moderate accuracy (CC:73%, 22/30 and Ml:70%, 21/30). Conclusions Together, our findings demonstrated that a cytokine-release assay is a promising method to complement clinical diagnosis, ultimately contributing to effective control of the disease.

Artificial Intelligence on Diagnostic Aid of Leprosy: A Systematic Literature Review

“…Some papers have classified leprosy according to the operational classification, which is recommended by the WHO. Studies by [ 14 , 87 , 94 ] classified leprosy as either paucibacillary or multibacillary. Binary classification occurred in 43% of the selected articles [ 12 , 14 , 76 , 82 , 83 , 87 , 94 , 95 , 96 ].…”

“…Studies by [ 14 , 87 , 94 ] classified leprosy as either paucibacillary or multibacillary. Binary classification occurred in 43% of the selected articles [ 12 , 14 , 76 , 82 , 83 , 87 , 94 , 95 , 96 ]. The remaining 57% of the articles used multiclass classification tasks, in which the models classified different skin diseases and, among them, leprosy [ 84 , 85 , 86 , 88 , 89 , 90 , 91 , 92 , 93 , 97 , 98 , 99 ].…”

“…The studies [ 14 , 76 , 87 , 94 , 96 ] utilized the outcomes of tests as input data to AI models, such as the RNA sequencing technique (RNA-Seq) and real-time reverse transcription polymerase chain reaction (RT-qPCR) used in molecular and cellular biology. The RNA-Seq technique extracts total RNA from a biological sample, converts it into complementary DNA (cDNA), and performs next-generation sequencing (NGS) [ 100 ].…”

“…To retrieve relevant studies, we used two search terms combined with their synonyms to design the search string presented in Box 1 . The following three control articles were selected to guide the searches in the digital libraries [ 12 , 14 , 76 ]. The validation process of the search strings occurred in the databases, which demonstrated their ability to find studies suitable for this SLR, including the control articles.…”

“…The diagnosis is predominantly made by analyzing clinical and dermato-neurological signs, and complementary tests such as heat sensitivity test and Mitsuda intradermal reaction test, and serology may also be used [ 13 ]. However, the absence of early symptomatology and similarity to other dermatological conditions can lead to an inconclusive diagnosis and, consequently, lack of appropriate treatment [ 14 ].…”