Leprosy is a multifactorial chronic disease caused by Mycobacterium leprae or Mycobacterium lepromatosis that affects the skin and nerves. More than 200.000 new cases are diagnosed per year; thus,... Show moreLeprosy is a multifactorial chronic disease caused by Mycobacterium leprae or Mycobacterium lepromatosis that affects the skin and nerves. More than 200.000 new cases are diagnosed per year; thus, transmission is still ongoing. The most likely way of transmission is the respiratory route form human-to-human; however, transmission is still not clearly understood. Early diagnosis of leprosy is crucial to reduce and avoid transmission as well as leprosy-associated disabilities, which are also a cause of stigma. Currently, diagnosis is performed based on clinical signs and symptoms and late- or mis-diagnosis are not uncommon.In this thesis, we combined the study of pathogen transmission with host transcriptomic and genomic biomarkers. To explore M. leprae transmission a One Health approach was followed, where human, animal and environmental samples were studied.The combination of demographic characteristics, pathogen detection, genetic and/or transcriptomic biomarkers can be applied in a multifactorial leprosy signature applicable for early diagnosis of leprosy and/or to guide intervention strategies. Identification of predictive biomarkers will in due course lead to prompt treatment, preventing leprosy-associated irreversible disabilities as well as reducing M. leprae transmission. Show less
Tio-Coma, M.; Kielbasa, S.M.; Eeden, S.J.F. van den; Mei, H.L.; Roy, J.C.; Wallinga, J.; ... ; Geluk, A. 2021
Background: Leprosy, a chronic infectious disease caused by Mycobacterium leprae, is often late-or misdiag-nosed leading to irreversible disabilities. Blood transcriptomic biomarkers that... Show moreBackground: Leprosy, a chronic infectious disease caused by Mycobacterium leprae, is often late-or misdiag-nosed 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 pres-ence 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 iden-tified, 1,613 genes were differentially expressed in progressors before diagnosis compared to HC. We identi-fied 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 ina 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 pre-dicting development of leprosy 4 to 61 months before clinical diagnosis. Assessment of this signature in con-tacts of leprosy patients can function as an adjunct diagnostic tool to target implementation of interventions to restrain leprosy development. (C) 2021 The Author(s). Published by Elsevier B.V. Show less
Braak, B. ter; Niemeijer, M.; Boon, R.; Parmentier, C.; Baze , A.; Richert. L.; ... ; Water, B. van de 2021
Various adaptive cellular stress response pathways are critical in the pathophysiology of liver disease and drug-induced liver injury. Human-induced pluripotent stem cell (hiPSC)-derived hepatocyte... Show moreVarious adaptive cellular stress response pathways are critical in the pathophysiology of liver disease and drug-induced liver injury. Human-induced pluripotent stem cell (hiPSC)-derived hepatocyte-like cells (HLCs) provide a promising tool to study cellular stress response pathways, but in this context there is limited insight on how HLCs compare to other in vitro liver models. Here, we systematically compared the transcriptomic profiles upon chemical activation in HLCs, hiPSC, primary human hepatocytes (PHH) and HepG2 liver cancer cells. We used targeted RNA-sequencing to map concentration transcriptional response using benchmark concentration modeling for the various stress responses in the different test systems. We found that HLCs are very sensitive towards oxidative stress and inflammation conditions as corresponding genes were activated at over 3 fold lower concentrations of the corresponding pathway inducing compounds as compared to PHH. PHH were the most sensitive model when studying UPR related effects. Due to the non-proliferative nature of PHH and HLCs, these do not pose a good/sensitive model to pick up DNA damage responses, while hiPSC and HepG2 were more sensitive in these conditions. We envision that this study contributes to a better understanding on how HLCs can contribute to the assessment of cell physiological stress response activation to predict hepatotoxic events. Show less
