Simultaneous COVID-19 in Monozygotic Twins
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Résumé
Letters8 December 2020Simultaneous COVID-19 in Monozygotic TwinsFREECorrection(s) for this article:CorrectionsMar 2021Correction: Simultaneous COVID-19 in Monozygotic TwinsFREEDavide Lazzeroni, MD, Pietro Concari, MD, and Luca Moderato, PhDDavide Lazzeroni, MDIRCCS Fondazione Don Carlo Gnocchi, Milan, Italy, Pietro Concari, MDSuzzara Hospital, Mantova, Italy, and Luca Moderato, PhDGuglielmo da Saliceto Hospital, Piacenza, ItalyAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/L20-1207 SectionsAboutVisual AbstractPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail Background: Although we are rapidly learning more about coronavirus disease 2019 (COVID-19), we still know little about why some infected persons have severe disease and others are asymptomatic or have mild disease.Objective: To understand these differences better by examining the experiences of 2 patients with COVID-19 who were similar in many respects but had different clinical illnesses.Case Report: On 9 March 2020, male twins who were 60 years old and considered monozygotic because of their appearances and other personal characteristics developed symptoms that started with fever and nasal congestion; continued with fatigue, dyspnea, and dry cough; and, after 10 days, led to hospitalization. Nasopharyngeal swabs tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using a real-time reverse transcriptase polymerase chain reaction assay. Neither twin had a history of chronic disease, cardiovascular risk factors, or long-term therapy. They lived at the same address and worked at the same location repairing automobiles in a body shop. Contact tracing identified 1 of their customers who interacted closely with them without protective measures as the likely source of their infections. The twins had similar presentations at admission (Table); both had mild interstitial pneumonia. However, because of limited resources during a surge in admissions, the diagnosis in twin 1 was based on lung ultrasonography that showed subpleural B-lines and chest radiography that showed bibasilar ground-glass opacification, whereas the diagnosis in twin 2 was based on a chest computed tomography scan that showed bilateral multifocal ground-glass opacities with 25% lung involvement. The same medical team provided care to both twins during the first 2 weeks of their hospital stays, where they were treated with supplemental oxygen, paracetamol, hydroxychloroquine, darunavir/cobicistat, and enoxaparin at prophylactic dosages. Despite having similar presentations and early treatment, the twins had different clinical courses. The Figure compares key clinical measures during the first 2 weeks of hospitalization, which was from admission to discharge for twin 1 and from admission to transfer to the intensive care unit for twin 2. Twin 1 was discharged without complications and recovered uneventfully. In contrast, twin 2 had a progressive increase in leukocyte count and C-reactive protein level associated with a variable increase in body temperature. Moreover, noninvasive ventilation was necessary because of a decrease in the Pao2/FIo2 ratio. After 3 days of ineffective ventilation, he was transferred to the intensive care unit where he reached his lowest Pao2/FIo2 value of 58 and was intubated and mechanically ventilated. He developed septic shock from an anaerobic bacterial infection that required vasopressors, antibiotics, steroids, and 4 days of invasive ventilation. His intensive care unit stay was followed by 17 days of uncomplicated hospitalization and a posthospitalization recovery that was slow but ended in full recovery of gas exchange without long-term consequences.Figure. Body temperature (A), Pao2/FIo2 ratio (B), C-reactive protein level (C), and leukocyte count (D) during the first 2 weeks of hospitalization, which was from admission to discharge for twin 1 and admission to transfer to the intensive care unit for twin 2. Download figure Download PowerPoint Table. Patient History and Clinical Characteristics at Hospital AdmissionDiscussion: Genetic factors are often proposed to explain differences in how COVID-19 affects people. For example, others have suggested that polymorphisms of ACE2 and TMPRSS2, differences in the ABO blood group system, and additional genetic factors may be associated with the susceptibility for acquiring SARS-CoV-2 and the severity of COVID-19 (1, 2). That possibility seems unlikely in the 2 patients we describe, especially if we assume no spontaneous mutations or epigenetic differences. In addition, other factors have been associated with an adverse prognosis, such as older age; cardiovascular risk factors; and chronic diseases of the lung, kidney, liver, or cardiovascular system (3). Our patients were identical in these respects. Moreover, some have proposed that environmental factors, such as air pollution, are associated with susceptibility to COVID-19 (4) and by extension may be related to disease severity. However, our patients lived at the same address and worked at the same job in the same workplace, so they probably had similar environmental exposures. Also, differences in the virus—for example, differences in the infecting dose (5) or viruses with different mutations—may explain differences in illness severity. We do not have direct information about these viral characteristics, but we believe both patients were infected by the same person, so they likely acquired the same virus. We also know that the number of polymerase chain reaction cycles needed to produce detectable viral RNA was similar (Table), which suggests that the viral load at diagnosis was similar.References1. Hou Y, Zhao J, Martin W, et al. New insights into genetic susceptibility of COVID-19: an ACE2 and TMPRSS2 polymorphism analysis [Letter]. BMC Med. 2020;18:216. [PMID: 32664879] doi:10.1186/s12916-020-01673-z CrossrefMedlineGoogle Scholar2. Ellinghaus D, Degenhardt F, Bujanda L, et al; Severe Covid-19 GWAS Group. Genomewide association study of severe Covid-19 with respiratory failure. N Engl J Med. 2020;383:1522-1534. [PMID: 32558485] doi:10.1056/NEJMoa2020283 CrossrefMedlineGoogle Scholar3. Cunningham JW, Vaduganathan M, Claggett BL, et al. Clinical outcomes in young US adults hospitalized with COVID-19. JAMA Intern Med. 2020. [PMID: 32902580] doi:10.1001/jamainternmed.2020.5313 Google Scholar4. Zhu Y, Xie J, Huang F, et al. Association between short-term exposure to air pollution and COVID-19 infection: evidence from China. Sci Total Environ. 2020;727:138704. [PMID: 32315904] doi:10.1016/j.scitotenv.2020.138704 CrossrefMedlineGoogle Scholar5. Pujadas E, Chaudhry F, McBride R, et al. SARS-CoV-2 viral load predicts COVID-19 mortality. Lancet. 2020;8:E70. doi.org/10.1016/S2213-2600(20)30354-4. Google Scholar Comments 0 Comments Sign In to Submit A Comment Giuseppe NovelliTor Vergata University of Rome, Italy and Nevada University, Reno8 December 2020 The variability of normality The case described is interesting and confirms the extreme phenotypic variability of SARS-CoV-2 infection. The high sensitivity of the new sequencing methods makes it possible to identify previously unthinkable levels of mosaicism and allow us to clarify much of the phenotypic discord between monozygotic twins. Somatic mutations generated by different mechanisms differ in their size, tissue of origin and temporal pattern. Many such mechanisms operate throughout the lifetime of an individual, whereas others (such as Alu and L1 retrotransposition) are likely to have specific temporal patterns. Added to this is the clonal heterogeneity of the viral genome during its replicas. For this reason it is important to study the genomics of the pathogen, of the host. The case report shows that every individual is a mosaic, even in the response to infectious diseases such as COVID-19. Disclosures: None Mahdi MovahedAbtahiBASIR Inst.7 December 2020 COVID-19 in Homozygous Twins: Different Risk Management I read with interest this article but at discussion, the authors could not find why twins manifested and experienced different clinical illnesses. There were many forgotten prognostic indicators: 1) Heart rate (in line with temperature) in twin 2 was not elevated as much as in twin 1. 2) Platelets were markedly increased in twin 2 than in twin 1. Both above indicators recommend different risk management and different prognosis. Twin 2 has been ignored. Maroun M. SfeirDepartment of Pathology, University of Connecticut Health Center, Farmington, CT 060308 December 2020 Homozygous twins with different COVID-19 severity: Any role for intestinal dysbiosis? Lazzeroni and colleagues describe the experiences of two 60-year-old male homozygous twins who developed similar presenting symptoms of coronavirus disease of 2019 (COVID-19) after exposure to the same source of infection (1). However, the clinical course was different despite the same initial medical care. Unlike twin 1 who recovered without complications, twin 2 developed septic shock caused by an anaerobic infection and he also required mechanical ventilation (1). The degree of relevant analogy between the twins including genetic predisposition, comorbidities, exposure, ethnic and geographic factors, precluded a definitive explanation for the difference in the severity of the twins' course of illness. A fundamental question that arises is whether twin 2 suffered from dysbiosis. A study by Zuo et al showed fecal microbiota alterations correlated with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) fecal levels and COVID-19 severity. For instance, a predominance of three anaerobic Gram-positive bacteria, Coprobacillus spp., Clostridium ramosum, and Clostridium hathewayi was significantly associated with higher COVID-19 severity (2). To that end, further emphasis on the type and source of the anaerobic infection twin 2 had should be added. Note that twin 2 is unmarried (1). Research has shown unmarried individuals consume less healthful foods that may alter the intestinal microbiome (3). Contrarily, the food behaviors of married individuals were more in line with the dietary guidelines (4). It is apparent that diet modulates gut microbiota (3, 4). Moreover, the action of intestinal bacteria on dietary fibers is apparent to increase short-chain fatty acids in the blood and protect against lung inflammation (5). The cytokine storm in COVID-19 is triggered by the dysregulated secretion of pro-inflammatory cytokines (6). A recent study examined the alteration of intestinal microbiota which was correlated with high serum and fecal levels of IL-18, a pro-inflammatory cytokine secreted by intestinal epithelial cells, and serum specific anti-SARS-CoV-2 IgA targeting the spike protein (6). However, specific SARS-CoV-2 IgA levels in fecal samples derived from COVID-19 patients and healthy controls were not significantly different, which indicates the increased production of spike protein IgA was probably due to mucosal infection in the respiratory tract rather than the intestines (6).In conclusion, a plausible explanation for the COVID-19 progression in twin 2 may be related in part to the altered gut microbiome influencing the lung's susceptibility to viral infection and COVID-19 progression. More research is needed to further dissect the role of intestinal microbiota in severe COVID-19 infection. References:1. Lazzeroni D, Concari P, Moderato L. Simultaneous COVID-19 in Homozygous Twins. Ann Intern Med. 2020 Dec 8.2. Zuo T, Zhang F, Lui GCY, et al. Alterations in Gut Microbiota of Patients With COVID-19 During Time of Hospitalization. Gastroenterology. 2020 Sep;159(3):944-955.e8.3. Gerrior SA, Guthrie JF, Fox JJ, et al. Differences in dietary quality of adults living in single versus multiperson households. J Nutr Educ. 1995;27:113. 4. Roos E, Lahelma E, Virtanen M, Prattala R, Pietinen P. Gender, socioeconomic status and family status as determinants of food behavior. Soc Sci Med. 1998;46:1519–1529.5. Trompette, A., Gollwitzer, E., Yadava, K. et al. Gut microbiota metabolism of dietary fiber influences allergic airway disease and hematopoiesis. Nat Med 2014; 20, 159–166.6. Tao W, Zhang G, Wang X, et al. Analysis of the intestinal microbiota in COVID-19 patients and its correlation with the inflammatory factor IL-18. Medicine in Microecology 2020; 5,100023 Andrew DemchukUniversity of Calgary8 December 2020 Professor of Neurology This case report provides very unique insight into otherwise hard to measure factors associated with COVID infection severity. The infection of monozygotic twins by the same person essentially eliminates all genetic and different viral strain explanations for differences in COVID illness severity. Leaving the most difficult to measure factor of viral inoculum dose as the most likely explanation for the different outcomes. With the sicker twin likely infected by alot more virus than the other. It would be very worthwhile knowing the amount of time each twin spent in close contact with the infection individual and whether the infected individual was coughing/sneezing in proximity to one of the twins and whether there was more verbal communication with the one twin. As duration of contact and degree of droplet transmission (sneezing/coughing/talking) may have been quite dissimilar resulting in differences in viral dose exposure each twin received the day of being infected. Kiran WagleNone8 December 2020 *Presumed* homozygous? Am I correct in thinking that these twins weren't tested to prove they were homozygous rather than assuming it based on appearance? And was the virus sequenced to show it was the same, or was that assumed due to contact tracing? I didn't see any discussion of those things. Richard WeissStudent9 December 2020 Differing viral load could affect course of illness I forwarded this article to a Professor acquaintance who commented as follows: "Could be difference in viral load. If they lived together, and one got from the other, my prediction would be the first one to get would fare better than the second one since viral load would be higher for a close family contact transmission than a public contact" Morgan BirabaharanDivision of Infectious Diseases and Global Public Health, Department of Medicine, University of California, San Diego11 December 2020 Simultaneous COVID-19 in Homozygous Twins: There is great heterogeneity in the clinical course and presentation of coronavirus disease 2019 (COVID-19). In this case report, homozygous twins who had similar health profiles, environmental exposures, and lifestyle factors had disparate COVID-19 disease outcomes [1]. Twin 1 had a brief hospitalization while twin 2 required escalation to intensive care and mechanical ventilation. Fortunately, both were with favorable outcome. The story of the twins offers an unprecedented view into pathomechanisms that underlie risk for severe COVID-19 disease. While Lazzeroni and colleagues provide a thorough investigation of characteristics that may be at play, the immune system, specifically T-cell immunity, warrants consideration. Early in the pandemic, 20-50% of unexposed participants were found to have T cell responses that resembled pre-existing immunity against SARS-CoV-2 [2]. Following this surprising finding, Mateus et al demonstrated that those T-cells reactive against SARS-CoV-2 from unexposed participants, were also reactive against seasonal common cold coronaviruses (CCC), including human coronavirus (HCoV)-OC43, HCoV-229E, HCoV-NL62, and HCoV-HKU1 [3]. From this, the hypothesis propagated that T-cell memory from prior CCC infection may confer partial protection against SARS-CoV-2— possibly explaining the extensive heterogeneity observed with COVID-19 [3]. To help extend this theory into clinical context, Sager et al performed a retrospective study investigating the difference in clinical outcomes of hospitalized COVID-19 patients, stratified by history of prior CCC infection [4]. Patients with prior CCC infection were found to have lower rates of ICU admissions and higher rates of survival than those without past CCC infection. Such study provided evidence of the possible protective factor of preexisting T-cell immunity against SARS-CoV-2. The mechanisms in which prior T-cell immunity may provide a protective effect is under investigation. Current models propose cross-reactive CD4+ memory T cells reducing lung viral load or possibly accelerating antibody development [3]. Moreover, some have postulated recent CCC infection may alter expression of receptors needed for SARS-CoV-2 cellular entry which include angiotensin-converting enzyme-2 (ACE2) and transmembrane serine protease 2 (TMPRSS2) [5]. In the case of the homozygous twins, while genetically, demographically, and behaviorally they may be the same, the ascertainment whether twin 1 was afflicted with a seasonal common cold coronavirus while twin 2 was not, remains unclear. The presence and absence of a pre-existing T-cell immunity may be another avenue of investigation for the contrasting hospital courses of the homozygous twins. Lazzeroni D, Concari P, Moderato L. Simultaneous COVID-19 in Homozygous Twins. Ann Intern Med. 2020 Dec 8. Lipsitch M, Grad YH, Sette A, Crotty S. Cross-reactive memory T cells and herd immunity to SARS-CoV-2. Nat Rev Immunol. 2020 Nov;20(11):709-713 Mateus J, Grifoni A, Tarke A et al. Selective and cross-reactive SARS-CoV-2 T cell epitopes in unexposed humans. Science. 2020 Oct 2;270(6512):89-94 Sagar M, Reifler K, Rossi M, et al. Recent endemic coronavirus infection is associated with less severe COVID-19. J Clin Invest. 2020 Sep 30:143380 Meyerholz DK, Perlman S. Does common cold coronavirus infection protect against severe SARS-CoV2 disease? J Clin Invest. 2020 Nov 20:144807 Author, Article, and Disclosure InformationAuthors: Davide Lazzeroni, MD; Pietro Concari, MD; Luca Moderato, PhDAffiliations: IRCCS Fondazione Don Carlo Gnocchi, Milan, ItalySuzzara Hospital, Mantova, ItalyGuglielmo da Saliceto Hospital, Piacenza, ItalyDisclosures: Authors have disclosed no conflicts of interest. Forms can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=L20-1207.Corresponding Author: Davide Lazzeroni, MD, IRCCS Fondazione Don Carlo Gnocchi, ONLUS, Piazzale dei Servi, n°3. 43121, Parma, Italy; e-mail, davide.lazzeroni@gmail.com.Correction: This article was corrected on 26 January 2021 to replace the term "homozygous" with "monozygotic" and to remove information about the patients' marital status from the Table.This article was published at Annals.org on 8 December 2020. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoCorrection: Simultaneous COVID-19 in Monozygotic Twins Metrics Cited byEffects of Multidisciplinary Rehabilitation Enhanced with Neuropsychological Treatment on Post-acute SARS-CoV-2 Cognitive Impairment (Brain Fog): An Observational StudyCardiovascular Post-Acute COVID-19 Syndrome: Definition, Clinical Scenarios, Diagnosis, and ManagementGenetics, shared environment, or individual experience? A cross-sectional study of the health status following SARS-CoV-2 infection in monozygotic and dizygotic twinsA Tale of Two Twins: Discordant Presentation of COVID-19 in Identical TwinsDo Males Affect Twinning Events? A Review of Current Findings/Twin Research Reviews: Monozygotic Twins Discordant for Parkinson's Disease; Fetal Loss in Twin Pregnancies Following Prenatal Diagnosis; Uterine Rupture and Repair in an Early Twin Pregnancy; Twin Study of Affectionate Communication/Human Interest: Conjoined Twins in a Triplet Set; Identical Twin Nurses Deliver Identical Twins; Identical Twins Discordant for COVID-19 Recovery Course; Identical Twins Pass Away from COVID-19; Archeological Finds of Oldest Identical TwinsCorrection: Simultaneous COVID-19 in Monozygotic Twins May 2021Volume 174, Issue 5 Page: 717-719 Keywords Cardiovascular disease risk Chronic kidney disease COVID-19 Hospitalizations Intensive care units Lungs Medical risk factors Thorax Twins Viral load ePublished: 8 December 2020 Issue Published: May 2021 Copyright & PermissionsCopyright © 2020 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,011 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».