4.6 Article

Revisiting IgG Antibody Reactivity to Epstein-Barr Virus in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome and Its Potential Application to Disease Diagnosis

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FRONTIERS IN MEDICINE
卷 9, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fmed.2022.921101

关键词

Epstein-Barr virus; Myalgic Encephalomyelitis; Chronic Fatigue Syndrome; antigen mimicry; biomarker discovery; patient stratification

资金

  1. ME Research UK [SC036942]
  2. Fundacao para a Ciencia e Tecnologia, Portugal [UIDB/00006/2020, SFRH/BD/149758/2019, SFRH/BD/147629/2019]
  3. Polish National Agency for Academic Exchange, Poland [PPN/ULM/2020/1/00069/U/00001]
  4. National Institutes of Health [NIH 2R01AI103629]
  5. FCT -Fundacao para a Ciencia e a Tecnologia [UIDB/00006/2020]
  6. ME Association [PF8947_ME]
  7. Weidenhammer Zoebele
  8. Lost Voices Foundation, Germany
  9. Fundação para a Ciência e a Tecnologia [SFRH/BD/149758/2019, SFRH/BD/147629/2019] Funding Source: FCT

向作者/读者索取更多资源

Infections by Epstein-Barr virus are associated with patients suffering from ME/CFS. This study re-analyzed microarray data and identified two antigens that may serve as biomarkers for disease diagnosis in this patient subgroup. Further research will be conducted to confirm this finding in a separate cohort of patients.
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 (HCs). 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-analyzed 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 distinguish patients from healthy controls. A similar finding was obtained when comparing patients with non-infectious or unknown disease trigger with healthy controls. However, when data analysis was restricted to the comparison between HCs and patients with a putative infection at their 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. To confirm this finding, a follow-up study will be conducted in a separate cohort of patients.

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