Brain-targeted autoimmunity is strongly associated with Long COVID and its chronic fatigue syndrome as well as its affective symptoms
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Abstract
Background
Autoimmune responses contribute to the pathophysiology of Long COVID, affective symptoms and myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS).
Objectives
To examine whether Long COVID, and its accompanying affective symptoms and CFS are associated with immunoglobulin (Ig)A/IgM/IgG directed at neuronal proteins including myelin basic protein (MBP), myelin oligodendrocyte glycoprotein (MOG), synapsin, α+β-tubulin, neurofilament protein (NFP), cerebellar protein-2 (CP2), and the blood-brain-barrier-brain-damage (BBD) proteins claudin-5 and S100B.
Methods
IgA / IgM/IgG to the above neuronal proteins, human herpes virus-6 (HHV-6) and Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) were measured in 90 Long COVID patients and 90 healthy controls, while C-reactive protein (CRP), and advanced oxidation protein products (AOPP) in association with affective and CFS ratings were additionally assessed in a subgroup thereof.
Results
Long COVID is associated with significant increases in IgG directed at tubulin (IgG-tubulin), MBP, MOG and synapsin; IgM-MBP, MOG, CP2, synapsin and BBD; and IgA-CP2 and synapsin. IgM-SARS-CoV-2 and IgM-HHV-6 antibody titers were significantly correlated with IgA/IgG/IgM-tubulin and -CP2, IgG/IgM-BBD, IgM-MOG, IgA/IgM-NFP, and IgG/IgM-synapsin. Binary logistic regression analysis shows that IgM-MBP and IgG-MBP are the best predictors of Long COVID. Multiple regression analysis shows that IgG-MOG, CRP and AOPP explain together 41.7% of the variance in the severity of CFS. Neural network analysis shows that IgM-synapsin, IgA-MBP, IgG-MOG, IgA-synapsin, IgA-CP2, IgG-MBP and CRP are the most important predictors of affective symptoms due to Long COVID with a predictive accuracy of r=0.801.
Conclusion
Brain-targeted autoimmunity contributes significantly to the pathogenesis of Long COVID and the severity of its physio-affective phenome.
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This Zenodo record is a permanently preserved version of a Structured PREreview. You can view the complete PREreview at https://prereview.org/reviews/10253453.
Does the introduction explain the objective of the research presented in the preprint? Yes The introduction begins by first explaining the prevalence of established studies that show a correlation relationship between neuropsychiatric symptoms such as CSF, depression and anxiety, and Long COVID. Then, it begins to highlight that due to the high prevalence of these studies in recent times, there is has becoming an increasing need to address the underlying causes of such an observed association. Finally, the paper lays out that it aims to to investigate autoimmune reactions and the …This Zenodo record is a permanently preserved version of a Structured PREreview. You can view the complete PREreview at https://prereview.org/reviews/10253453.
Does the introduction explain the objective of the research presented in the preprint? Yes The introduction begins by first explaining the prevalence of established studies that show a correlation relationship between neuropsychiatric symptoms such as CSF, depression and anxiety, and Long COVID. Then, it begins to highlight that due to the high prevalence of these studies in recent times, there is has becoming an increasing need to address the underlying causes of such an observed association. Finally, the paper lays out that it aims to to investigate autoimmune reactions and the presence of specific autoantibodies in individuals with Long COVID, by specifically focusing on their potential association with CFS and other observed symptomsAre the methods well-suited for this research? Somewhat appropriate For the most part, the methods seem to be rigorous and appropriate for this study; however, there seem to be minor potential issues that could occur from relying on retrospective data here. The methods clearly define their criteria for Long COVID and patient selection as they adhere to the WHO criteria for Long COVID, ensuring standardization among all obtained patients. As for the sample size that was included, there was quite a large set of patients taken for both Part 1 and Part 2 of the research, and the exclusion criteria for this cohort was also clearly defined to be any individuals with pre-existing neuro-immune, autoimmune, and immune-related conditions. Both of these measures taken not only add specificity to the study cohort but also further validate its results. The issue, however, primarily lies in the fact that this is a retrospective study that relies on existing data. At times these data points are incomplete or ambiguous to the study since they might have been collected for another reason. For this study, the accuracy and consistency of the recorded PBT and SpO2 readings taken for the acute phase could've varied from different healthcare sites and the impact of the PBT and SpO2 on biomarkers and neuropsychiatric rating scales could've been subject to information bias.Are the conclusions supported by the data? Highly supported The study makes some very significant findings, such as that Long COVID patients displayed elevated levels of autoantibodies against diverse neuronal antigens as well as increased CRP and AOPP, suggesting that Long COVID is associated with certain upregulated autoimmune processes. The study also suggested that the physio-affective phenome of Long COVID such as CSF can be predicted by autoimmune responses against neuronal proteins. However, the study does take into account that there are many potential limitations of the baseline results, one of which being that there is still a need for other autoantibodies to be analyzed in future studies to further validate results. They also suggest that there was a need to collect patient follow-up data that they didn't quite address in the study. Overall, the study introduces a lot of segways into further causal research on the topic and has significant findings that it does over-generalize, making it highly supported in the claims that it does make.Are the data presentations, including visualizations, well-suited to represent the data? Highly appropriate and clear The data presentations include tables that consolidate information on univariate and multiple regression graphs as well as summarize socio-demographic and clinical data, figures displaying regression graphs of specific outcomes based on the Fibro-Fatigue Scale and Hamilton Anxiety Rating Scale on selected biomarkers. Although the data collected was complex and statistically sophisticated, it was clearly labeled and explained in language of the results section as well illustrated in enough different mediums for it to be clear to readers.How clearly do the authors discuss, explain, and interpret their findings and potential next steps for the research? Very clearly The authors clearly explain the limitations of their studies as well as the importance of their findings in making significant strides in the field of Long COVID research quite effectively. Many of the biomarkers, antibodies, tests, and characteristics analyzed are clearly introduced in the introduction and further defined and clarified both in the methods section and results. The discussion also clearly addresses larger implications of the study's results if further studies were done to examine other autoantibodies.Is the preprint likely to advance academic knowledge? Highly likely There has already been a lot of literature studying how Long COVID can affect neuropsychiatric processes and cause issues such as CSF, however, this study does offer further insights into how that could be an actual association with autoantibodies and other biomolecular data. If other studies follow up on its results and examine other autoantibodies and receive similar conclusions, the findings could become invaluable in the field of Long COVID research.Would it benefit from language editing? No There are little to no grammatical or language issues that impede the understanding of the paper's purpose and results.Would you recommend this preprint to others? Yes, but it needs to be improved Although the results of this preprint prove to be promising and have the potential to be further explored in future studies, there definitely could be better methods used to collect the data to ensure that there is complete and accurately reflected data points collected to prove the causal relationship. A study such as this one would be better if done in real-time and adhered to follow-ups with the patients to further make the results more convincing.Is it ready for attention from an editor, publisher or broader audience? Yes, as it is Aside from minor methodological issues in the study's design, its conclusions and results are supported by rigorous analyses. The study mentions it's limitations and novelty to the field, making it clear that it's results could be further expanded and refined upon in future studies.Competing interests
The author declares that they have no competing interests.
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Danilo Buonsenso
Review 2: "Brain-targeted Autoimmunity is Strongly Associated with Long COVID and Its Chronic Fatigue Syndrome as Well as Its Affective Symptoms"
Reviewers were overall positive in evaluating this preprint, finding it reliable to strong. Reviewers thought it was overall methodologically sound and important in advancing knowledge about Long COVID.
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Zhao Zhong Chong, Nizar Souayah
Review 1: "Brain-targeted Autoimmunity is Strongly Associated with Long COVID and Its Chronic Fatigue Syndrome as Well as Its Affective Symptoms"
Reviewers were overall positive in evaluating this preprint, finding it reliable to strong. Reviewers thought it was overall methodologically sound and important in advancing knowledge about Long COVID.
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Strength of evidence
Reviewers: Z Chong & N Souayah (Rutgers University) | 📘📘📘📘📘
D Buonsenso (Gemelli University) | 📗📗📗📗◻️ -