Revisiting IgG Antibody Reactivity to Epstein-Barr Virus in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome and Its Potential Application to Disease Diagnosis - Sepúlveda, Nuno; Malato, João; Sotzny, Franziska; Grabowska, Anna D.; Fonseca, André; Cordeiro, Clara; Graça, Luís; Biecek, Przemyslaw; Behrends, Uta; Mautner, Josef; Westermeier, Francisco; Lacerda, Eliana M.; et al. (Frontiers in Medicine, 2022)
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.