Correlation between COVID-19 severity and previous exposure of patients to Lyme Disease

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A new study by researchers from Wroclaw Medical University-Poland, Hirszfeld Institute of Immunology and Experimental Therapy-Poland, the Regional Specialist Hospital in Wroclaw-Poland and the Healthcare Centre in Boleslawiec-Poland has revealed that individuals with a past history of Lyme disease have a higher risk of disease severity upon infection with the SARS-CoV-2 coronavirus.

Lyme disease is the most common vector-borne disease (that is, a disease transmitted by mosquitoes, ticks, or fleas) in the United States. In recent years, approximately 476,000 new cases of Lyme disease are reported in the US every year! https://www.globallymealliance.org/about-lyme/

The study findings were published on a preprint server: Research Square and are currently being peer reviewed. https://www.researchsquare.com/article/rs-1799732/v1

In this study we investigated potential correlations between detected antibody levels indicating exposure to Borrelia and the risk of increased severity of COVID-19.

Previous exposure to Borrelia was identified by multi-antigenic serological testing, and it revealed that increased levels of Borrelia-specific IgGs strongly correlated with COVID-19 severity and with the risk of hospitalization (Figs. 1 and 3, Supplementary Tables S1 and S2). For Borrelia-specific IgMs, correlations were weaker and mostly insignificant (Fig. 2 and Supplementary Fig. S3, Supplementary Tables S3 and S4).

Typically, pathogen-specific IgM increases at the early stage of infection, while IgG development takes more time. In borreliosis, at the early stage of infection (2–4 weeks) the immunological system detects only a few antigens of Borrelia, e.g. p41 (flagellin) and Osp proteins (outer surface proteins), targeted by IgM antibodies. Borrelia-specific IgGs, in turn, can be observed several weeks after the tick bite, and their increased serum concentration can remain for a long time, even after the resolution of clinical symptoms. OspC, OspA, and p41 are considered the most immunogenic proteins of B. burgdorferi19,20; consistently, in this study IgGs targeting these antigens were also the most frequent and they reached the highest levels (Fig. 1).

Other important targets for IgG diagnostics include VisE, p83, p58, and p17 19,20, also detected in this study. Interestingly, in many patients we observed antibodies targeting different species (e.g. B. burgdorferi sensu stricto, and at the same time B. afzelii, and/or B. garinii).

This may reflect some cross-reactivity of antibodies, but likely it may result from co-infections with more than one species, which according to the literature may also occur 9. Also, severe COVID-19 patients demonstrated significantly higher levels of IgG specific to Anaplasma (Fig. 1), which is often co-transmitted with Borrelia by ticks. This further supports the suggestion that increased risks in COVID-19 are linked to a history of tick bites and related infections (Fig. 4).

Important limitations should be considered for a full understanding of this study’s results. First, diagnostics of Lyme disease (active borreliosis) is still difficult and often unclear. Laboratory testing should be considered in conjunction with potential exposure and compatible clinical symptoms10; data on patients’ history of tick bites and on potential borreliosis-related symptoms were not available here.

Particularly severe COVID-19 patients under intensive care were not able to give them.

Thus, in the investigated group at least some individuals may demonstrate immunological memory of previous Borrelia infection/s but not an active disease. On the other hand, difficulties with rapid and unambiguous diagnosis may lead to some Borrelia-infected patients going untreated, with the pathogen affecting their health condition even for a long time.

Second, although this study demonstrated a significant correlation between serum levels of anti-Borrelia antibodies and COVID-19 severity observed in the same individuals, a correlation cannot be assumed to indicate causation. One cannot exclude that there was an unidentified primary factor that in these patients caused both higher vulnerability to Borrelia infection and to severe COVID-19.

This could possibly be immunodeficiency or other physiological disorders. Since these patients however demonstrated an efficient antibody response to SARS-CoV-2 (Fig. 1), this issue calls for further research. Alternatively, prolonged Lyme disease might affect the immune system, decreasing its efficacy in antiviral responses in the viral infection.

This has never been demonstrated yet, though important effects that Borrelia may have on the immune system have been described21,22. Of note, demographic parameters have been agreed between groups (Supplementary Fig. S2), so for instance elderly age was not a contributing factor here.

In spite of these important reservations, a strong link between detected anti-Borrelia antibodies and COVID-19 severity was observed in this study (Fig. 1, 2, and 3).

This was further supported by post-hoc analysis of IgG targeting selected antigens of Borrelia. These antigens included Osp proteins, p41, and VlsE, being highly immunogenic19 and important in the life cycle of spirochetes; they are engaged in bacterial colonization of ticks and mammals, virulence, and immune evasion by Borrelia23–25.

The analysis with multivariant logistic regression revealed that increased levels of IgG targeting Osp proteins (only) can be significant predictors of hospitalization due to COVID-19; in this study OspB, OspC B. burgdorferi sensu stricto, and OspC B. spielmanii demonstrated significance in this model (Supplementary Fig. S4, Supplementary Table S5).

To the best of our knowledge, this is the first observation that suggests links between Lyme disease and COVID-19 prognostics. Screening for antibodies targeting Borrelia may contribute to accurately assessing the odds of hospitalization for SARS-CoV-2 infected patients.

Though mechanisms of this association are not clear yet, it may help in establishing optimal treatment schedules and in efficient predictions of individual patients’ prognostics, supporting efforts for efficient control of COVID-19.

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