Long‑COVID Fatigue Is Not Predicted By Pre‑pandemic Plasma IL‑6 Levels in Mild COVID‑19

Abstract

Objective and design Fatigue is a prominent symptom in the general population and may follow a viral infection, including SARS-CoV2 infection which causes COVID-19. Chronic fatigue lasting more than three months is the major symptom of the post-COVID syndrome (known colloquially as long-COVID). The mechanisms underlying long-COVID fatigue are unknown. We hypothesized that the development of long-term chronic fatigue is driven by the pro-inflammatory immune status of an individual before COVID-19.

Cistanche can act as an anti-fatigue and stamina enhancer, and experimental studies have shown that the decoction of Cistanche tubulosa could effectively protect the liver hepatocytes and endothelial cells damaged in weight-bearing swimming mice, upregulate the expression of NOS3, and promote hepatic glycogen synthesis, thus exerting anti-fatigue efficacy. Phenylethanoid glycoside-rich Cistanche tubulosa extract could significantly reduce the serum creatine kinase, lactate dehydrogenase, and lactate levels, and increase the hemoglobin (HB) and glucose levels in ICR mice, and this could play an anti-fatigue role by decreasing the muscle damage and delaying the lactic acid enrichment for energy storage in mice. Compound Cistanche Tubulosa Tablets significantly prolonged the weight-bearing swimming time, increased the hepatic glycogen reserve, and decreased the serum urea level after exercise in mice, showing its anti-fatigue effect. The decoction of Cistanchis can improve endurance and accelerate the elimination of fatigue in exercising mice, and can also reduce the elevation of serum creatine kinase after load exercise and keep the ultrastructure of skeletal muscle of mice normal after exercise, which indicates that it has the effects of enhancing physical strength and anti-fatigue. Cistanchis also significantly prolonged the survival time of nitrite-poisoned mice and enhanced the tolerance against hypoxia and fatigue.

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Subjects and methods We analyzed pre-pandemic plasma levels of IL-6, which plays a key role in persistent fatigue, in  N=1274 community-dwelling adults from TwinsUK. Subsequent COVID-19-positive and -negative participants were categorized based on SARS-CoV-2 antigen and antibody testing. Chronic fatigue was assessed using the Chalder Fatigue Scale.

Results COVID-19-positive participants exhibited mild disease. Chronic fatigue was a prevalent symptom among this population and significantly higher in positive vs. negative participants (17% vs........ 11%, respectively; p=0.001). The qualitative nature of chronic fatigue as determined by individual questionnaire responses was similar in positive and negative participants. Pre-pandemic plasma IL-6 levels were positively associated with chronic fatigue in negative, but not positive individuals. Raised BMI was associated with chronic fatigue in positive participants.

Conclusions Pre-existing increased IL-6 levels may contribute to chronic fatigue symptoms, but there was no increased risk in individuals with mild COVID-19 compared with uninfected individuals. Elevated BMI also increased the risk of chronic fatigue in mild COVID-19, consistent with previous reports.

Keywords Long-COVID · Chronic fatigue · IL-6 · Infammation · BMI

Introduction

Fatigue is a common symptom of COVID-19 and is one of its most pronounced acute and post-acute clinical manifestations [1]. Long-lasting manifestations—so-called long-COVID—are a subject of intense interest. Affected individuals report fatigue along with shortness of breath, headache, and loss of sense of taste and smell [2]. Mechanisms underlying the persistence of long-term symptoms are yet to be determined. To date, exploration of blood-borne biomarkers following COVID-19 infection has not revealed an association with inflammatory markers or white cell count [3].

The cytokine interleukin (IL)-6 has a recognized role in fatigue development in many clinical settings, including autoimmune inflammatory arthritis (reviewed in [4]) and cancer [5]. It is an established driver of acute responses to COVID-19, and treatment with anti-IL-6 monoclonal antibodies reduces mortality in severe COVID-19 [6, 7]. IL-6 is also considered a key mediator of neuropsychiatric symptoms of long-COVID, including fatigue [8]. Finally, a Mendelian randomization study of depressive symptoms has suggested that IL-6 manifests a causal influence on fatigue, as well as sleep problems, and suicidality [9].

We hypothesized that long-term COVID fatigue is driven at least in part by the pre-existing immune status of an individual. We have shown previously that chronic fatigue induced by treatment with interferon-alpha (IFN-α) for chronic hepatitis B viral infection is predicted by higher baseline IL-6 and IL-10 levels, as well as an exaggerated elevation of IL-6 and IL-10, in response to treatment [10]. In addition, increasing age is a major risk factor for both illness severity and longevity after SARS-CoV-2 infection [2]. Aging has been associated with elevated levels of pro-inflammatory cytokines, such as TNF-α and IL-6, and reduced levels of anti-inflammatory mediator IL-10 [11, 12]. An age-related, chronic, pro-inflammatory milieu may mediate the risk for susceptibility to COVID-19 and long-COVID fatigue. To test this hypothesis, we analyzed levels of pro-inflammatory cytokine IL-6 in plasma collected before the SARS-CoV-2 pandemic in a longitudinal cohort sample of UK adults, who were assessed during the pandemic for chronic fatigue symptoms and SARSCoV-2 infection.

Materials and methods

Sample and phenotyping

Participants were selected from the UK Twin Registry  (TwinsUK), an adult cohort that is representative of the general population for lifestyle and health-related traits [13]. Ethics permission was obtained and participants provided fully informed consent; the Declaration of Helsinki was adhered to. The registry comprises 14,500 same-sex mono- and dizygotic twin volunteers from the general UK population recruited from previous twin registers and national media campaigns. The cohort is predominantly female (83%), and mainly of  Northern European descent [14]. Samples and data for this project were collected as part of ongoing research initiatives into undamaging as well as more recent research into COVID-19. Participant selection and grouping are depicted in Fig. 1. Participants (n = 5755) were invited to complete a COVID-19 Personal Experience (CoPE)  Questionnaire which included questions about COVID-19 infection, related symptoms, and fatigue over the previous three months [15]. CoPE was completed in multiple waves during the pandemic: April 2020, August 2020, November  2020, and April 2021. Participants also provided serum for COVID-19 antigen and antibody testing at multiple points during the pandemic, with primary collections of n=506 in April 2020, n = 5165 in August 2020, n =137 in  November–December 2020, and n = 4291 in April–May 2021.

We followed guidance on interpretation of antibody test results from the Centres for Disease Control and Prevention (https://www.cdc.gov/coronavirus/2019-ncov/lab/resources/antibody-tests-guidelines.html) to assign natural COVID-19 infection status from the results of swab antigen tests; and enzyme-linked immunosorbent assays (ELISA) anti-Nucleocapsid (anti-N) and anti-Spike (antiS) Roche antibody tests [16] performed at both King's College London and 3rd-party laboratories as described previously [17]. Individuals with a positive antigen test at any point over the CoPE questionnaire administration period, who were positive for anti-S antibodies before self-reported COVID-19 vaccination date, or positive for anti-N antibodies at any point, were classified as COVID-19-positive cases. Individuals with negative antigen or anti-N antibody results, or negative anti-S antibody results before COVID-19 vaccination, were classified as COVID-19 negative, or controls. Those with negative anti-N antibodies and negative antigen results but positive anti-S after COVID-19 vaccination were excluded from the analysis as anti-S antibodies are generated in response to vaccination.  Individuals with no laboratory antigen or antibody test results were also excluded from the analysis.

Within the CoPE questionnaire, the Chalder Fatigue Scale (CFQ) [18] was used to classify participants into those experiencing chronic fatigue and those who did not. CFQ comprises 11 questions concerning the physical and mental aspects of fatigue. Reliability of CFQ has been shown in clinical and non-clinical settings [18, 19]. CFQ responses were extracted from the CoPE questionnaires administered in August and November 2020. Responses were coded as 0 (“Less than usual”, “No more than usual”) or 1 (“More than usual”, “Much more than usual”) followed by summing the scores for different questions and assigning a diagnosis of fatigue to those with a summary score of 4 or more [19]. Volunteers reporting fatigue at both time points were diagnosed as having chronic fatigue because it lasted 3 months or longer. Those who reported fatigue at a single time point were removed from the study.

Pre-pandemic IL-6 levels were ascertained using plasma specimens obtained in 1997–2018 (median 2009). Samples were assayed using Olink Target 96 Inflammation assay (https://www.olink.com/products-services/target/infammati  on/). Where multiple plasma specimens were available, we selected the most recent, pre-pandemic specimen. IL-6 levels were expressed as normalized protein expression on the Olink arbitrary unit in the log2 scale.

Statistical analysis

A generalized mixed-effects model with chronic fatigue as a dichotomous categorical response variable and IL-6 levels as a predictor was examined, adjusting for age, body mass index (BMI), and sex as fixed effects. Family structure and zygosity were considered random factors. IL-6 levels were adjusted for age and BMI followed by the transformation of the residuals to a normal distribution using the norm function in an R statistical environment. The model was fitted for COVID-19-positive and COVID-19-negative participants separately.  A set of sensitivity analyses was performed. The first investigated sample integrity over time and comprised only plasma samples collected two years before the pandemic; the second was analysis without adjustment of IL-6 levels for age and  BMI levels. Finally, we repeated the analysis after excluding individuals with major inflammatory diseases (rheumatoid arthritis, systemic lupus erythematosus, ulcerative colitis, and Crohn’s disease; n=11).

Results

Prevalence of fatigue

After selecting participants reporting the same fatigue status at both time points, the sample for analysis comprised a total of n=1274 participants, of whom n=282 were classified as COVID-19 positive, and n=162 were classified as having chronic fatigue (Table 1). None of the COVID-19-positive participants had been hospitalized, so their COVID-19 was considered relatively mild. The prevalence of long-term fatigue was 17.4% among COVID-19-positive participants and 11.4% among COVID-19-negative participants (Fisher’s exact p=0.011). COVID-19-positive participants were on average two years younger than COVID-19-negative participants, and there was no difference in BMI observed (Table 1). Two (1.1%) and nine (0.7%) cases of major inflammatory disease were reported by those with and without chronic fatigue, respectively (Fisher’s exact test p=0.641).

Structure of fatigue

The qualitative nature of chronic fatigue was similar in COVID-19-positive and -negative participants, with no differences in the prevalence of positive answers in the CFQ  (Table 2).

IL‑6 levels

In the total sample, chronic fatigue was associated with elevated pre-pandemic plasma IL-6 levels, which persisted after adjusting cytokine levels for age, sex, BMI, and COVID-19 status; chronic fatigue was also associated with higher levels of BMI (Fig. 2).

Stratified analysis established that pre-pandemic plasma  IL-6 levels were elevated in participants with chronic fatigue in the COVID-19-negative group. The same relationship was not seen in the COVID-19-positive group  (Table 3). We also calculated the prevalence of fatigue in COVID-19-positive and COVID-19-negative participants stratified by high and low levels of pre-pandemic IL-6. We defined high and low IL-6 levels as values equal to or above the 75% percentile of IL-6 distribution and equal to or below the 25% percentile, respectively. The prevalence of fatigue was found to be significantly higher in the high  IL-6 level group compared to the low IL-6 level group in  COVID-negative participants (17.5% vs 7.6%, p=0.001); however, no such differences were found in the COVIDpositive group (19.2% vs 19.0%, p=0.999). Sensitivity analysis of participants having plasma collected no earlier than 2017 showed similarity with the main analysis:  β = 0.653 ± 0.375, p = 0.0814; and β=−0.760 ± 0.625, p=0.224 for COVID-19-negative and COVID-19-positive participants, respectively). Sensitivity analysis without adjusting IL-6 levels for age and BMI levels at the time of plasma collection, produced almost identical results to the main analysis: β=0.321 ± 0.115, p = 0.005; and β=− 0.061 ± 0.180, p=0.774 for COVID-19-negative and COVID-19-positive participants, respectively. Sensitivity analysis excluding cases of major inflammatory disease, produced almost identical results, too: β=0.307 ± 0.108, p = 0.004; and β=-0.078 ± 0.166, p=0.639, for COVID-19-negative and COVID-19-positive participants, respectively.

BMI

Higher BMI was associated with chronic fatigue in  COVID-19-positive participants and the whole sample (Table 3). To explore the relationship between chronic fatigue and BMI in COVID-19-positive participants, we examined groups by BMI (BMI < 18.5; n = 6), healthy weight (BMI > 18.5 and < 25; n = 115), overweight (BMI > 25 and < 30; n = 102), and obese (BMI ≥ 30; n=59). There was a significant difference in the prevalence of these groups in COVID-19-positive cases with and without chronic fatigue (χ2=8.3, df=3, p value=0.040; Fig. 3). This was largely driven by a lower prevalence of healthy weight and a higher prevalence of obesity in COVID-19-positive participants with chronic fatigue.

Discussion

This is among the first studies to examine pre-infective inflammatory cytokine levels and subsequent long-term chronic fatigue in participants who experienced mild COVID-19 illness. We found elevated pre-pandemic IL-6 levels increased the risk of developing fatigue in adult volunteers who had never had COVID-19; however, pre-pandemic IL-6 levels did not predict fatigue in our COVID-19-positive group. This finding is in keeping with other post-viral and post-infective fatigue research and studies in a general population [20, 21]. We previously demonstrated that greater pro-inflammatory cytokine elevations in response to IFN-α treatment were associated with developing persistent fatigue  [10]. In that study, we also observed a role for pre-treatment higher cytokine levels of IL-6 and lower IL-10 and the development of chronic fatigue — which led to the current hypothesis.

While our COVID-19-positive group was not hospitalized and therefore classified with 'mild' illness, IL-6 and other pro-inflammatory cytokines likely reach high levels during COVID-19 infection [20], well over levels associated with well-known risk factors such as elevated BMI [21]. Taken together, these and our findings suggest any elevation of circulating pro-inflammatory cytokines, be it a protracted, low-grade inflammatory dysregulation or an acute sickness response to infection will increase chronic fatigue risk, with higher cytokine levels associated with higher risk. The baseline immune status or cytokine levels of a healthy individual may only predict chronic fatigue in the absence of pronounced cytokine elevation, such as an acute sickness response to viral or bacterial infection.

Our hypothesis that chronic fatigue in community-dwelling adults after SARS-CoV-2 infection was predicated on a pre-existing pro-inflammatory immune state) was not supported by our results.

We did, however, find a statistically significant association between higher BMI and long-term fatigue in COVID-19-positive participants (Table 3). This is consistent with a study demonstrating an association between obesity and fatigue while controlling for other potential contributors including IL-6 levels [22]. Indeed, almost a third of circulating IL-6 is thought to be produced by adipocytes [23], in keeping with BMI being an important risk factor for chronic fatigue. Of interest, the relationship between BMI and chronic fatigue was not evident in COVID-19-negative participants, an association usually apparent in the population [24].

Allied with this, higher BMI and advanced age are well-established risk factors for severe COVID-19 [22], and both are associated with greater systemic inflammation [23]. Our findings show that following mild COVID-19 chronic fatigue does not appear to be qualitatively different from other forms of chronic fatigue, at least according to the CFQ, which is a well-validated tool to discriminate between clinical and non-clinical conditions [19]. Whether this is true for more severe diseases requiring hospitalization is unclear.

The most pronounced limitation to this study is the focus on a single cytokine and we recognize that other inflammatory mediators such as TNF-α are likely to contribute to chronic fatigue also.

In summary, our work sheds light on the role of IL-6 in general chronic fatigue, but it does not support a specific role for IL-6 levels in the development of chronic fatigue following mild COVID-19.

Acknowledgements The study was supported by Kennedy Trust grant  #KENN 19-20-10. JML is supported by the NIHR Birmingham Biomedical Research Centre, and CMP by the South London and Maudsley NHS Foundation Trust & King’s College London Biomedical Research Centre; the views expressed here are those of the authors and not necessarily those of the NHS, NIHR or Department for Health and Social Care. Mario Falchi is supported by MRC grant MR/T004142/1. TwinsUK is funded by the Wellcome Trust, Medical Research Council, Versus Arthritis, European Union Horizon 2020, Chronic Disease Research Foundation (CDRF), Zoe Ltd and the National Institute for Health Research (NIHR) Clinical Research Network (CRN) and Biomedical Research Centre based at Guy’s and St Thomas’ NHS Foundation Trust in partnership with King’s College London.

Author contributions Clinical data acquisition: NC, ED, CS, KJD, MHM. Cytokine data acquisition and pre-processing: NR, MF, MBF. Data analysis: NC, NR, MBF, AB. Manuscript preparation: MBF, FMKW, IGS, JML, PF, CP. All authors reviewed and approved the manuscript.

Data availability The datasets analyzed in the current study are available on request from the TwinsUK repository (https://twinsukapps.kcl.ac. uk/data_request).

Declarations

Conflict of interest Authors declare no conflicts of interest to disclose.

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