Revisiting IgG antibody reactivity to Epstein-Barr virus in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome and its potential application to disease diagnosis
Authors
Nuno Sepúlveda, João Torrado Malato, Franziska Sotzny, Anna D. Grabowska, André Fonseca, Clara Cordeiro, Luís Graça, Przemysław Biecek, Uta Behrends, Josef Mautner, Francisco Westermeier, Eliana Mattos Lacerda, Carmen Scheibenbogen
Abstract
Infections by the Epstein-Barr virus (EBV) are often at the disease onset of patients suffering from Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS). However, serological analyses of these infections remain inconclusive when comparing patients with healthy controls. In particular, it is unclear if certain EBV-derived antigens eliciting antibody responses have a biomarker potential for disease diagnosis. With this purpose, we re-analysed a previously published microarray data on the IgG antibody responses against 3,054 EBV-related antigens in 92 patients with ME/CFS and 50 HCs. This re-analysis consisted of constructing different regression models for binary outcomes with the ability to classify patients and HCs. In these models, we tested for a possible interaction of different antibodies with age and gender. When analyzing the whole data set, there were no antibody responses that could be used to distinguish patients from healthy controls. A similar finding was obtained when comparing patients with noninfectious or unknown disease trigger to healthy controls. However, when data analysis was restricted to the comparison between HCs and patients with a putative infection at disease onset, we could identify stronger antibody responses against two candidate antigens (EBNA4_0529 and EBNA6_0070). Using antibody responses to these two antigens together with age and gender, the final classification model had an estimated sensitivity and specificity of 0.833 and 0.720, respectively. This reliable case-control discrimination suggested the use of the antibody levels related to these candidate viral epitopes as biomarkers for disease diagnosis in this subgroup of patients. When a bioinformatic analysis was performed on these epitopes, it revealed a potential molecular mimicry with several human proteins. To confirm these promising findings, a follow-up study will be conducted in a separate cohort of patients.
The study: https://www.medrxiv.org/content/10.1101/2022.04.20.22273990v1
Authors
Nuno Sepúlveda, João Torrado Malato, Franziska Sotzny, Anna D. Grabowska, André Fonseca, Clara Cordeiro, Luís Graça, Przemysław Biecek, Uta Behrends, Josef Mautner, Francisco Westermeier, Eliana Mattos Lacerda, Carmen Scheibenbogen
Abstract
Infections by the Epstein-Barr virus (EBV) are often at the disease onset of patients suffering from Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS). However, serological analyses of these infections remain inconclusive when comparing patients with healthy controls. In particular, it is unclear if certain EBV-derived antigens eliciting antibody responses have a biomarker potential for disease diagnosis. With this purpose, we re-analysed a previously published microarray data on the IgG antibody responses against 3,054 EBV-related antigens in 92 patients with ME/CFS and 50 HCs. This re-analysis consisted of constructing different regression models for binary outcomes with the ability to classify patients and HCs. In these models, we tested for a possible interaction of different antibodies with age and gender. When analyzing the whole data set, there were no antibody responses that could be used to distinguish patients from healthy controls. A similar finding was obtained when comparing patients with noninfectious or unknown disease trigger to healthy controls. However, when data analysis was restricted to the comparison between HCs and patients with a putative infection at disease onset, we could identify stronger antibody responses against two candidate antigens (EBNA4_0529 and EBNA6_0070). Using antibody responses to these two antigens together with age and gender, the final classification model had an estimated sensitivity and specificity of 0.833 and 0.720, respectively. This reliable case-control discrimination suggested the use of the antibody levels related to these candidate viral epitopes as biomarkers for disease diagnosis in this subgroup of patients. When a bioinformatic analysis was performed on these epitopes, it revealed a potential molecular mimicry with several human proteins. To confirm these promising findings, a follow-up study will be conducted in a separate cohort of patients.
The study: https://www.medrxiv.org/content/10.1101/2022.04.20.22273990v1
