Incidence, co-occurrence, and evolution of long-COVID features

 

• Maxime Taquet ,
• Quentin Dercon,
• Sierra Luciano,
• John R. Geddes,
• Masud Husain,
• Paul J. Harrison

DOI: https://doi.org/10.1371/journal.pmed.1003773

PDF: https://journals.plos.org/plosmedicine/article/file?id=10.1371/journal.pmed.1003773&type=printable

Abstract

Background

Long-COVID refers to a variety of symptoms affecting different organs reported by people following Coronavirus Disease 2019 (COVID-19) infection. To date, there have been no robust estimates of the incidence and co-occurrence of long-COVID features, their relationship to age, sex, or severity of infection, and the extent to which they are specific to COVID-19. The aim of this study is to address these issues.

Methods and findings

We conducted a retrospective cohort study based on linked electronic health records (EHRs) data from 81 million patients including 273,618 COVID-19 survivors. The incidence and co-occurrence within 6 months and in the 3 to 6 months after COVID-19 diagnosis were calculated for 9 core features of long-COVID (breathing difficulties/breathlessness, fatigue/malaise, chest/throat pain, headache, abdominal symptoms, myalgia, other pain, cognitive symptoms, and anxiety/depression). Their co-occurrence network was also analyzed. Comparison with a propensity score–matched cohort of patients diagnosed with influenza during the same time period was achieved using Kaplan–Meier analysis and the Cox proportional hazard model. The incidence of atopic dermatitis was used as a negative control.

Among COVID-19 survivors (mean [SD] age: 46.3 [19.8], 55.6% female), 57.00% had one or more long-COVID feature recorded during the whole 6-month period (i.e., including the acute phase), and 36.55% between 3 and 6 months. The incidence of each feature was: abnormal breathing (18.71% in the 1- to 180-day period; 7.94% in the 90- to180-day period), fatigue/malaise (12.82%; 5.87%), chest/throat pain (12.60%; 5.71%), headache (8.67%; 4.63%), other pain (11.60%; 7.19%), abdominal symptoms (15.58%; 8.29%), myalgia (3.24%; 1.54%), cognitive symptoms (7.88%; 3.95%), and anxiety/depression (22.82%; 15.49%). All 9 features were more frequently reported after COVID-19 than after influenza (with an overall excess incidence of 16.60% and hazard ratios between 1.44 and 2.04, all p < 0.001), co-occurred more commonly, and formed a more interconnected network. Significant differences in incidence and co-occurrence were associated with sex, age, and illness severity. Besides the limitations inherent to EHR data, limitations of this study include that (i) the findings do not generalize to patients who have had COVID-19 but were not diagnosed, nor to patients who do not seek or receive medical attention when experiencing symptoms of long-COVID; (ii) the findings say nothing about the persistence of the clinical features; and (iii) the difference between cohorts might be affected by one cohort seeking or receiving more medical attention for their symptoms.

Conclusions

Long-COVID clinical features occurred and co-occurred frequently and showed some specificity to COVID-19, though they were also observed after influenza. Different long-COVID clinical profiles were observed based on demographics and illness severity.

Author summary

Why was this study done?

• Long-COVID has been described in recent studies. But we do not know the risk of developing features of this condition and how it is affected by factors such as age, sex, or severity of infection.
• We do not know if the risk of having features of long-COVID is more likely after Coronavirus Disease 2019 (COVID-19) than after influenza.
• We do not know about the extent to which different features of long-COVID co-occur.

What did the researchers do and find?

• This research used data from electronic health records of 273,618 patients diagnosed with COVID-19 and estimated the risk of having long-COVID features in the 6 months after a diagnosis of COVID-19. It compared the risk of long-COVID features in different groups within the population and also compared the risk to that after influenza.
• The research found that over 1 in 3 patients had one or more features of long-COVID recorded between 3 and 6 months after a diagnosis of COVID-19. This was significantly higher than after influenza.
• For 2 in 5 of the patients who had long-COVID features in the 3- to 6-month period, they had no record of any such feature in the previous 3 months.
• The risk of long-COVID features was higher in patients who had more severe COVID-19 illness, and slightly higher among females and young adults. White and non-white patients were equally affected.

What do these findings mean?

• Knowing the risk of long-COVID features helps in planning the relevant healthcare service provision.
• The fact that the risk is higher after COVID-19 than after influenza suggests that their origin might, in part, directly involve infection with SARS-CoV-2 and is not just a general consequence of viral infection. This might help in developing effective treatments against long-COVID.
• The findings in the subgroups, and the fact that the majority of patients who have features of long-COVID in the 3- to 6-month period already had symptoms in the first 3 months, may help in identifying those at greatest risk.

Funding: MT, PJH, and JRG were supported by the National Institute for Health Research (NIHR) Oxford Health Biomedical Research Centre (BRC-1215-20005). MT is an NIHR Academic Clinical Fellow and an NIHR Oxford Health BRC Senior Research Fellow. MH is supported by a Wellcome Trust Principal Research Fellowship (206330/Z/17/Z) and the NIHR Oxford Biomedical Research Centre. The views expressed are those of the authors and not necessarily those of the UK National Health Service, NIHR, or the UK Department of Health. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. NIHR: https://www.nihr.ac.uk Wellcome Trust: https://wellcome.org.

Competing interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: SL is an employee of TriNetX Inc. The other authors report no interests to declare.

• https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1003773#pmed.1003773.s003

Pseudoephedrine, derivatives antagonize SARS-CoV-2 viruses

 Shaopeng Yu,Yao Chen,Yusen Xiang,He Lin,Mengge Wang,Wenbo Ye,Pei Zhang,Hongzhuan Chen,Guoqiang Lin,Yuying Zhu,Lili Chen,Jiange Zhang,

DOI:  

https://doi.org/10.1002/ptr.7245

PDF: https://onlinelibrary.wiley.com/doi/epdf/10.1002/ptr.7245

Abstract

The coronavirus disease 2019 has infected over 150 million people worldwide and led to over 3 million deaths. Severe acute respiratory syndrome (SARS)-CoV-2 lineages B.1.1.7, B.1.617, B.1.351, and P.1 were reported to have higher infection rates than that of wild one. These mutations were noticed to happen in the receptor-binding domain of spike protein (S-RBD), especially mutations N501Y, E484Q, E484K, K417N, K417T, and L452R. Currently, there is still no specific medicine against the virus; moreover, cytokine storm is also a dangerous factor for severe infected patients. In this study, potential S-RBD-targeted active monomers from traditional Chinese medicine Ephedra sinica Stapf (ephedra) were discovered by virtual screening. NanoBiT assay was performed to confirm blocking activities of the screened compounds against the interaction between SARS-CoV-2 S-RBD and angiotensin-converting enzyme 2 (ACE2). We further analyzed the blocking effect of the active compounds on the interactions of mutated S-RBD and ACE2 by computational studies. Moreover, antiinflammatory activities were evaluated using qRT-PCR, enzyme-linked immune sorbent assay, and Western blot analysis. As a result, pseudoephedrine (MHJ-17) and its derivative (MHJ-11) were found as efficient inhibitors disrupting the interactions between ACE2 and both wild and mutated S-RBDs. In addition, they also have antiinflammatory activities, which can be potential drug candidates or lead compounds for further study.

Funding information: Emergency Scientific Research Programme of Shanghai University of Traditional Chinese Medicine, Grant/Award Numbers: 2019YJ 06-01, 2019YJ 06-03; Scientific Research Project of Shanghai Municipal Health Commission on Traditional Chinese Medicine for Prevention and Treatment of COVID-19, Grant/Award Numbers: 2020XGKY07, 2020XGKY09; Shanghai University of Traditional Chinese Medicine, Grant/Award Numbers: 2019YJ 06-01, 2020XGKY09, 2020XGKY07; The Third Research Institute of Ministry of Public Security; Department of Pharmacy, Nanjing University of Chinese Medicine

https://onlinelibrary.wiley.com/doi/10.1002/ptr.7245

Durability of immune responses to the BNT162b2 mRNA vaccine

  

View ORCID ProfileMehul S. Suthar, Prabhu S. Arunachalam, Mengyun Hu, Noah Reis, Meera Trisal, Olivia Raeber, Sharon Chinthrajah, Meredith E. Davis-Gardner, Kelly Manning, Prakriti Mudvari, Eli Boritz, Sucheta Godbole, Amy R. Henry, Daniel C. Douek, Peter Halfmann, Yoshihiro Kawaoka, Veronika I. Zarnitsyna, Kari Nadeau, Bali Pulendran

doi: https://doi.org/10.1101/2021.09.30.462488

This article is a preprint and has not been certified by peer review [what does this mean?].

PDF: https://www.biorxiv.org/content/10.1101/2021.09.30.462488v1.full.pdf

Abstract

The development of the highly efficacious mRNA vaccines in less than a year since the emergence of SARS-CoV-2 represents a landmark in vaccinology. However, reports of waning vaccine efficacy, coupled with the emergence of variants of concern that are resistant to antibody neutralization, have raised concerns about the potential lack of durability of immunity to vaccination. We recently reported findings from a comprehensive analysis of innate and adaptive immune responses in 56 healthy volunteers who received two doses of the BNT162b2 vaccination. Here, we analyzed antibody responses to the homologous Wu strain as well as several variants of concern, including the emerging Mu (B.1.621) variant, and T cell responses in a subset of these volunteers at six months (day 210 post-primary vaccination) after the second dose. Our data demonstrate a substantial waning of antibody responses and T cell immunity to SARS-CoV-2 and its variants, at 6 months following the second immunization with the BNT162b2 vaccine. Notably, a significant proportion of vaccinees have neutralizing titers below the detection limit, and suggest a 3rd booster immunization might be warranted to enhance the antibody titers and T cell responses.

Competing Interest Statement

The authors have declared no competing interest.

https://www.biorxiv.org/content/10.1101/2021.09.30.462488v1

Molnupiravir: coding for catastrophe

 

Brandon Malone & 

Elizabeth A. Campbell

Molnupiravir, a wide-spectrum antiviral that is currently in phase 2/3 clinical trials for the treatment of COVID-19, is proposed to inhibit viral replication by a mechanism known as ‘lethal mutagenesis’. Two recently published studies reveal the biochemical and structural bases of how molnupiravir disrupts the fidelity of SARS-CoV-2 genome replication and prevents viral propagation by fostering error accumulation in a process referred to as ‘error catastrophe’.

Despite the reprieve from COVID-19 granted by vaccination programs, SARS-CoV-2 continues to ravage many communities worldwide. Vaccine shortages, public hesitancy and the emergence of new virus variants have hindered public health efforts to prevent the spread of COVID-19. Furthermore, SARS-CoV-2 is likely to become endemic1, leading to the emergence of vaccine-resistant variants and reinforcing the need to develop antiviral therapeutic agents. Molnupiravir (MK-4482, EIDD-2801) is a candidate antiviral that inhibits viral propagation through lethal mutagenesis by introducing errors in the viral genome. The biochemical and structural basis of how molnupiravir induces lethal mutagenesis has remained largely unexplored. Recently, Götte and colleagues reported biochemical results exploring the antiviral activity of molnupiravir and provided a compelling model to explain the mutagenic patterns observed in coronaviruses exposed to molnupiravir in cell culture2. In this issue of Nature Structural & Molecular Biology, Cramer and colleagues3 further our understanding of this process by providing biochemical and structural data that reveal how molnupiravir introduces transition mutations into the SARS-CoV-2 genome. Together, the two studies offer complementary and comprehensive views of the mechanism of lethal mutagenesis and provide a platform for rational drug design.

Similar to other nucleoside analogs, molnupiravir targets the SARS-CoV-2 RNA-dependent RNA polymerase (RdRp), which mediates replication and transcription of the coronavirus genome. Viral RdRps are proven effective targets for inhibition, with several licensed nucleoside analogs that are used therapeutically1,4. Indeed, the only currently clinically approved antiviral used for the treatment of COVID-19 is remdesivir (Verklury), which targets the RdRp5. Similar to remdesivir, molnupiravir has been re-investigated as a coronavirus antiviral agent that leads to increased frequency of G-to-A and C-to-U transition mutations6,7,8,9. Molnupiravir was also shown to inhibit propagation of the SARS-CoV, MERS-CoV and SARS-CoV-2 viruses, re-enforcing its pan-coronaviral inhibitory profile8,10. Treatment with molnupiravir failed to induce viral-resistance mutations, which suggests a high genetic barrier to immune evasion6,7. Notably, in contrast to the antiviral nucleoside analogs fluorouracil (5-FU) and ribavarin11,12,13, molnupiravir is resistant to the proofreading exoribonuclease encoded by coronaviruses7, which makes it an attractive target for further development. Thus, understanding the molecular basis of inhibition of molnupiravir reveals the lethal mutagenesis mechanism that will aid the informed design of related inhibitors.

Molnupiravir is a prodrug derivatized from the ribonucleoside analog β-D-N4-hydroxycytidine (NHC) that is converted to its active form molnupiravir triphosphate (MTP) in the cell6. Both Gordon et al.2 and Kabinager et al.3 investigated the selective incorporation of MTP versus the natural nucleotides (ATP, GTP, UTP and CTP). They determined that MTP competes most effectively with CTP for incorporation into the product RNA. MTP also competes with UTP less efficiently, which suggests that MTP is unlikely to function as a UTP analog in the cellular milieu. After incorporation of molnupiravir (as the monophosphorylated MNP), RNA synthesis proceeds without stalling, which indicates that MNP does not act as a chain terminator, but is readily incorporated into the nascent RNA. The lack of interruption to RNA synthesis may mitigate engagement of the proofreading complex, rendering it incapable of excising the incorporated MNP. Both groups hypothesized that the newly synthesized RNA transcript that contains MNP in lieu of cytidine could be subsequently used as the template RNA in the next round of viral RNA synthesis.

Kabinger et al.3 used solid-phase synthesis to generate a template RNA strand with an internal MNP base to specifically asses the role of an NHC as the templating base. By contrast, Gorden et al.2 enzymatically synthesized a template RNA containing MNP. Notably, they both observed that the templating MNP could form base pairs and subsequently incorporate either GTP or ATP into the new product-RNA strand. The finding that MNP can template ATP explains the previous observation of a G-to-A mutational bias after viral exposure to molnupiravir. The rationale for MNP recognizing both G and A is that the NHC base exists as two tautomers13. The hydroxylamine or amino form behaves chemically like C and enables base pairing with G, whereas the oxime or imino form mimics U and pairs with A (Fig. 1f). Thus, tautomerization controls whether the correct (GTP) or incorrect (ATP) nucleotide is inserted and, therefore, whether mutagenesis will occur. By promoting incorporation of A instead of G into the nascrent RNA strand, the incorporated A templates a U in the next round of RNA synthesis, resulting in an overall C-to-U error. A pathway for the C-to-U transition mutation that follows C+-to-G− to-M+-to-A-to-U+, in which the ‘+’ and ‘−’ refers to the positive- and negative sense strands, respectively, is shown in Fig. 1.This pathway supports the current evidence that there is an accumulation of C-to-U mutations in the genomes of coronaviruses exposed to molnupiravir7,8.

Fig. 1: Schematization of mutagenic pathway by molnupiravir.

a, Schematic representation of the SARS-CoV-2 genome. b,c, Chemical structure of molnupiravir (b) and the activated form, molnupiravir triphosphate (MTP) (c). d, MTP competes mainly with CTP for incorporation opposite G. e, Schematic depicting the C-to-U transition mutation pathway. The MNP-templated A incorporates a U in place of C. f, The template strand MNP base pairs either with A (incorrect nucleotide) or G (correct nucleotide), depending on the tautomer.

Full size image

In addition to the biochemical studies, Kabinger et al.3 determined high-resolution cryo-EM structures that show MNP templating either A or G in the RdRp active site, without notable perturbations of the RdRp active site or of the nucleic acid scaffold. Although the cryo-EM maps cannot distinguish the two tautomeric forms, they reasonably assume that the amino form of molnupiravir base pairs with G, forming three hydrogen bonds. By contrast, the imino tautomer forms two hydrogen bonds with A. Furthermore, the authors note that the hydrogen bond between M–A and M–G was suboptimal, possibly explaining its lower selectivity when compared with the natural NTPs. These structures thus provide a valuable direct visualization of how the NHC base of molnupiravir in the template strand base pairs with G and A to introduce G-to-A transition mutations.

Kabinger et al.3 and Gordon et al.2 therefore arrive at similar conclusions about the mechanism of lethal mutagenesis by molnupiravir, with subtle differences. Gordon et al.2 stress that the C-to-U transition mutations occur when MNP is incorporated in the template strand because the two tautomers of NHC exist more equally than its substrate triphosphate form. This model rationalizes the biochemical findings in the context of the high frequencies of G-to-A and C-to-U transition mutations in coronaviruses exposed to molnupiravir8. Another difference is the model provided by Kabinger et al.3 entertains A-to-G transitions, which can occur in coronaviruses exposed to molnupiravir, albeit at much lower frequencies8. Thus, although the biochemical evidence indicates that MTP is a better CTP analog, the genetic data suggest that MTP can compete weakly with UTP, inducing A-to-G transitions.

In summary, the two studies demonstrate that molnupiravir-induced lethal mutagenesis is minimally a two-step mechanism characterized by a relatively high selectivity of MTP for incorporation as a CTP analog and the indiscriminate incorporation of either ATP (mutagenesis) or GTP when MNP is localized in the templating strand. The erroneously incorporated AMP can subsequently template UTP incorporation, generating downstream C-to-U mutations. The accumulation of mutations pushes viral replication over the ‘error threshold’ that demarcates the replication fidelity required for viability. This mechanism distinguishes molnupiravir from remdesivir, which impedes the progression of viral RdRp, and provides insights into alternative mechanisms of RdRp inhibition. Finally, molnupiravir possesses excellent pharmacokinetic properties14, which include oral administration. An orally bioavailable antiviral will have far-reaching benefits in tackling the spread of COVID-19 in hard-to-reach communities worldwide. As with all therapeutic agents, off-target effects are a concern. In its triphosphate form, molnupirivar is a substrate for the mitochondrial RNA polymerase, which can also incorporate MTP as a U or C analog. Reassuringly, the same study noted that mitochondrial function over 14 days was not significantly inhibited15, and Sheahan et al. did not observe mutagenesis of host mRNA8. However, it has been suggested that exposure to molnupiravir can be mutagenic to host DNA during host DNA replication16. Therefore, the potential off-target effects will require further investigation.

https://www.nature.com/articles/s41594-021-00657-8