Evidence map›Paper›PMID 37328761›Full record

ArticleRespiratory research2023

Ultra-rare RTEL1 gene variants associate with acute severity of COVID-19 and evolution to pulmonary fibrosis as a specific long COVID disorder.

Laura Bergantini, Margherita Baldassarri, Miriana d'Alessandro, Giulia Brunelli, Gaia Fabbri, Kristina Zguro, Andrea Degl'Innocenti, GEN-COVID Multicenter study, Chiara Fallerini, Elena Bargagli and 1 more

Registry-linked trialOpen access · goldAbstract readMulticenter Study
In one paragraph

Article in Respiratory research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04549831 (Identification of the Genetic Bases Determining COVID-19 Clinical Variability in the Italian Population), which is not on this map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.3field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT04549831 unknown statusnot on this map

Identification of the Genetic Bases Determining COVID-19 Clinical Variability in the Italian Population

TypeobservationalSponsorUniversity of SienaRan2020 to 2026Enrolled2,000ConditionsCOVID-19ArmsMassive parallel sequencing of host genome
3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Article
  3. Long COVID-19: A Concept Analysis.Infectious disease reports · 2025
    Article
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  5. Article
  6. Article
  7. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 20 institutions in 1 country.

Laura Bergantini *Respiratory Disease Unit, Department of Medical Sciences, University Hospital of Siena (Azienda Ospedaliera Universitaria Senese, AOUS), Policlinico Le Scotte, Viale Bracci, 2, 53100, Siena, Italy.
Margherita Baldassarri *Medical Genetics Unit, University of Siena, Policlinico Le Scotte, Viale Bracci, 2, 53100, Siena, Italy.
Miriana d'AlessandroRespiratory Disease Unit, Department of Medical Sciences, University Hospital of Siena (Azienda Ospedaliera Universitaria Senese, AOUS), Policlinico Le Scotte, Viale Bracci, 2, 53100, Siena, Italy.
Giulia BrunelliMedical Genetics Unit, University of Siena, Policlinico Le Scotte, Viale Bracci, 2, 53100, Siena, Italy.
Gaia FabbriRespiratory Disease Unit, Department of Medical Sciences, University Hospital of Siena (Azienda Ospedaliera Universitaria Senese, AOUS), Policlinico Le Scotte, Viale Bracci, 2, 53100, Siena, Italy.
Kristina ZguroMedical Genetics Unit, University of Siena, Policlinico Le Scotte, Viale Bracci, 2, 53100, Siena, Italy.
Andrea Degl'InnocentiMedical Genetics Unit, University of Siena, Policlinico Le Scotte, Viale Bracci, 2, 53100, Siena, Italy.
GEN-COVID Multicenter study
Chiara FalleriniMedical Genetics Unit, University of Siena, Policlinico Le Scotte, Viale Bracci, 2, 53100, Siena, Italy.
Elena BargagliRespiratory Disease Unit, Department of Medical Sciences, University Hospital of Siena (Azienda Ospedaliera Universitaria Senese, AOUS), Policlinico Le Scotte, Viale Bracci, 2, 53100, Siena, Italy. bargagli2@unisi.it.
Alessandra RenieriMedical Genetics Unit, University of Siena, Policlinico Le Scotte, Viale Bracci, 2, 53100, Siena, Italy. alessandra.renieri@unisi.it.
University of Siena · ITUniversity of Padua · ITAzienda Ospedaliera Universitaria Senese · ITAzienda Usl Toscana Centro · ITOspedale San Donato · ITCa' Foncello Hospital · ITOspedale Misericordia - Grosseto · ITIstituti di Ricovero e Cura a Carattere Scientifico · ITUniversity of Milan · ITUniversity of Modena and Reggio Emilia · ITUniversity of Pavia · ITUniversity of Perugia · ITAzienda Usl 8 Arezzo · ITASST Fatebenefratelli Sacco · ITAzienda Ospedaliera Ospedale Maggiore · ITAzienda ULSS 9 TREVISO · ITAziende Socio Sanitarie Territoriale di CremaCasa Sollievo della Sofferenza · ITLuigi Sacco Hospital · ITOspedale San Paolo · IT

Funding

Azienda Ospedaliero-Universitaria Senese Bando Ricerca COVID-19 ToscanaEU project H2020-SC1-FA-DTS-2018-2020 International consortium for integrative genomics prediction (INTERVENE) Grant Agreement No. 101016775Intesa San Paolo 2020 charity fund N B/2020/0119 "Identificazione delle basi genetiche determinanti la variabilità clinica della risposta a COVID-19 nella popolazione italianaIstituto Buddista Italiano Soka Gakkai "PAT-COVID: Host genetics and pathogenetic mechanisms of COVID-19" (ID n. 2020-2016_RIC_3)Italian Ministry of University and Research Bando FISR 2020 "Editing dell'RNA contro il SARS-CoV-2: hackerare il virus per identificare bersagli molecolari e attenuare l'infezione - HACKTHECOV"
6 · The paper itself

Abstract

backgroundSevere Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a novel coronavirus that caused an ongoing pandemic of a pathology termed Coronavirus Disease 19 (COVID-19). Several studies reported that both COVID-19 and RTEL1 variants are associated with shorter telomere length, but a direct association between the two is not generally acknowledged. Here we demonstrate that up to 8.6% of severe COVID-19 patients bear RTEL1 ultra-rare variants, and show how this subgroup can be recognized.

methodsA cohort of 2246 SARS-CoV-2-positive subjects, collected within the GEN-COVID Multicenter study, was used in this work. Whole exome sequencing analysis was performed using the NovaSeq6000 System, and machine learning methods were used for candidate gene selection of severity. A nested study, comparing severely affected patients bearing or not variants in the selected gene, was used for the characterisation of specific clinical features connected to variants in both acute and post-acute phases.

resultsOur GEN-COVID cohort revealed a total of 151 patients carrying at least one RTEL1 ultra-rare variant, which was selected as a specific acute severity feature. From a clinical point of view, these patients showed higher liver function indices, as well as increased CRP and inflammatory markers, such as IL-6. Moreover, compared to control subjects, they present autoimmune disorders more frequently. Finally, their decreased diffusion lung capacity for carbon monoxide after six months of COVID-19 suggests that RTEL1 variants can contribute to the development of SARS-CoV-2-elicited lung fibrosis.

conclusionRTEL1 ultra-rare variants can be considered as a predictive marker of COVID-19 severity, as well as a marker of pathological evolution in pulmonary fibrosis in the post-COVID phase. This notion can be used for a rapid screening in hospitalized infected people, for vaccine prioritization, and appropriate follow-up assessment for subjects at risk. Trial Registration NCT04549831 ( www. CLINICALTRIAL: org ).

Indexed as

COVID-19DNA HelicasesPost-Acute COVID-19 SyndromePulmonary FibrosisHumansLungSARS-CoV-2DNA HelicasesRTEL1 protein, humanCOVID-19Long COVIDPulmonary fibrosisRTEL1

Identifiers

PMID37328761
PMCPMC10276396
OpenAlexW4380885278

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.