Household Contacts of Leprosy Patients in Endemic Areas Display a Specific Innate Immunity Profile

Leprosy is a chronic infectious disease, caused by Mycobacterium leprae, that can lead to severe life-long disabilities. The transmission of M. leprae is continuously ongoing as witnessed by the stable new case detection rate. The majority of exposed individuals does, however, not develop leprosy and is protected from infection by innate immune mechanisms. In this study the relation between innate immune markers and M. leprae infection as well as the occurrence of leprosy was studied in household contacts (HCs) of leprosy patients with high bacillary loads. Serum proteins associated with innate immunity (ApoA1, CCL4, CRP, IL-1Ra, IL-6, IP-10, and S100A12) were determined by lateral flow assays (LFAs) in conjunction with the presence of M. leprae DNA in nasal swabs (NS) and/or slit-skin smears (SSS). The HCs displayed ApoA1 and S100A12 levels similar to paucibacillary patients and could be differentiated from endemic controls based on the levels of these markers. In the 31 households included the number (percentage) of HCs that were concomitantly diagnosed with leprosy, or tested positive for M. leprae DNA in NS and SSS, was not equally divided. Specifically, households where M. leprae infection and leprosy disease was not observed amongst members of the household were characterized by higher S100A12 and lower CCL4 levels in whole blood assays of HCs in response to M. leprae. Lateral flow assays provide a convenient diagnostic tool to quantitatively measure markers of the innate immune response and thereby detect individuals which are likely infected with M. leprae and at risk of developing disease or transmitting bacteria. Low complexity diagnostic tests measuring innate immunity markers can therefore be applied to help identify who should be targeted for prophylactic treatment

Blood RNA signature RISK4LEP predicts leprosy years before clinical onset

Background: Leprosy, a chronic infectious disease caused by Mycobacterium leprae, is often late- or misdiagnosed leading to irreversible disabilities. Blood transcriptomic biomarkers that prospectively predict those who progress to leprosy (progressors) would allow early diagnosis, better treatment outcomes and facilitate interventions aimed at stopping bacterial transmission. To identify potential risk signatures of leprosy, we collected whole blood of household contacts (HC, n=5,352) of leprosy patients, including individuals who were diagnosed with leprosy 4-61 months after sample collection. Methods: We investigated differential gene expression (DGE) by RNA-Seq between progressors before presence of symptoms (n=40) and HC (n=40), as well as longitudinal DGE within each progressor. A prospective leprosy signature was identified using a machine learning approach (Random Forest) and validated using reverse transcription quantitative PCR (RT-qPCR). Findings: Although no significant intra-individual longitudinal variation within leprosy progressors was identified, 1,613 genes were differentially expressed in progressors before diagnosis compared to HC. We identified a 13-gene prospective risk signature with an Area Under the Curve (AUC) of 95.2%. Validation of this RNA-Seq signature in an additional set of progressors (n=43) and HC (n=43) by RT-qPCR, resulted in a final 4-gene signature, designated RISK4LEP (MT-ND2, REX1BD, TPGS1, UBC) (AUC=86.4%). Interpretation: This study identifies for the first time a prospective transcriptional risk signature in blood predicting development of leprosy 4 to 61 months before clinical diagnosis. Assessment of this signature in contacts of leprosy patients can function as an adjunct diagnostic tool to target implementation of interventions to restrain leprosy development. Funding: This study was supported by R2STOP Research grant, the Order of Malta-Grants-for-Leprosy-Research, the Q.M. Gastmann-Wichers Foundation and the Leprosy Research Initiative (LRI) together with the Turing Foundation (ILEP# 702.02.73 and # 703.15.07).</p