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Open accessJournal ArticleDOI: 10.7554/ELIFE.67569

Association of Toll-like receptor 7 variants with life-threatening COVID-19 disease in males: findings from a nested case-control study.

02 Mar 2021-eLife (eLife Sciences Publications Limited)-Vol. 10, pp 1-15
Abstract: Background Recently, loss-of-function variants in TLR7 were identified in two families in which COVID-19 segregates like an X-linked recessive disorder environmentally conditioned by SARS-CoV-2. We investigated whether the two families represent the tip of the iceberg of a subset of COVID-19 male patients. Methods This is a nested case-control study in which we compared male participants with extreme phenotype selected from the Italian GEN-COVID cohort of SARS-CoV-2-infected participants ( Results Overall, we found TLR7 deleterious variants in 2.1% of severely affected males and in none of the asymptomatic participants. The functional gene expression profile analysis demonstrated a reduction in TLR7-related gene expression in patients compared with controls demonstrating an impairment in type I and II IFN responses. Conclusions Young males with TLR7 loss-of-function variants and severe COVID-19 represent a subset of male patients contributing to disease susceptibility in up to 2% of severe COVID-19. Funding Funded by private donors for the Host Genetics Research Project, the Intesa San Paolo for 2020 charity fund, and the Host Genetics Initiative. Clinical trial number NCT04549831.

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30 results found

Open accessJournal ArticleDOI: 10.1126/SCIIMMUNOL.ABL4348
Takaki Asano1, Bertrand Boisson1, Bertrand Boisson2, Bertrand Boisson3  +63 moreInstitutions (15)
19 Aug 2021-Science immunology
Abstract: Autosomal inborn errors of type I IFN immunity and autoantibodies against these cytokines underlie at least 10% of critical COVID-19 pneumonia cases. We report very rare, biochemically deleterious X-linked TLR7 variants in 16 unrelated male individuals aged 7 to 71 years (mean: 36.7 years) from a cohort of 1,202 male patients aged 0.5 to 99 years (mean: 52.9 years) with unexplained critical COVID-19 pneumonia. None of the 331 asymptomatically or mildly infected male individuals aged 1.3 to 102 years (mean: 38.7 years) tested carry such TLR7 variants (p = 3.5 × 10-5). The phenotypes of five hemizygous relatives of index cases infected with SARS-CoV-2 include asymptomatic or mild infection (n=2, 5 and 38 years), or moderate (n=1, 5 years), severe (n=1, 27 years), or critical (n=1, 29 years) pneumonia. Two boys (aged 7 and 12 years) from a cohort of 262 male patients with severe COVID-19 pneumonia (mean: 51.0 years) are hemizygous for a deleterious TLR7 variant. The cumulative allele frequency for deleterious TLR7 variants in the male general population is < 6.5x10-4 We also show that blood B cell lines and myeloid cell subsets from the patients do not respond to TLR7 stimulation, a phenotype rescued by wild-type TLR7 The patients' blood plasmacytoid dendritic cells (pDCs) produce low levels of type I IFNs in response to SARS-CoV-2. Overall, X-linked recessive TLR7 deficiency is a highly penetrant genetic etiology of critical COVID-19 pneumonia, in about 1.8% of male patients below the age of 60 years. Human TLR7 and pDCs are essential for protective type I IFN immunity against SARS-CoV-2 in the respiratory tract.

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Topics: Pneumonia (52%), Population (51%)

32 Citations

Open accessJournal ArticleDOI: 10.3389/FIMMU.2021.622176
Abstract: Coronavirus disease (COVID-19) presents a broad spectrum of clinical manifestations ranging from an asymptomatic to a severe clinical course The host genetic background influence on the susceptibility and outcome of multiples infectious diseases has been previously reported Herein, we aimed to describe relevant identified genetic variants and those potentially related to the inter-individual variability of COVID-19 susceptibility and/or severity considering the physiopathological pathway of the disease The HLA-A*25:01, -B*15:27, -B*46:01, -C*01:02, and -C*07:29 alleles have been associated with COVID-19 susceptibility; while HLA-A*02:02, -B*15:03, and -C*12:03 have been identified as low-risk alleles Variants in cytokine genes such as IL1B, IL1R1, IL1RN, IL6, IL17A, FCGR2A, and TNF could be related to disease susceptibility and cytokine storm, and/or COVID-19 complications (eg, venous thrombosis) Several variants in ACE2 and TMPRSS2 affecting the expression of the receptors related to COVID-19 have been associated with the disease susceptibility and risk factors Finally, two GWAS have identified the loci 3p2131 (LZTFL1, SLC6A20, CCR9, FYCO1, CXCR6, and XCR1) and 9q342 (ABO) with COVID-19 severity Heterogeneous results in the association of genetic variants with COVID-19 susceptibility and severity were observed The mechanism of identified risk-genes and studies in different populations are still warranted

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Topics: Genome-wide association study (56%), Allele (51%)

15 Citations

Open accessJournal ArticleDOI: 10.1016/J.AJHG.2021.05.017
Abstract: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19), a respiratory illness that can result in hospitalization or death. We used exome sequence data to investigate associations between rare genetic variants and seven COVID-19 outcomes in 586,157 individuals, including 20,952 with COVID-19. After accounting for multiple testing, we did not identify any clear associations with rare variants either exome wide or when specifically focusing on (1) 13 interferon pathway genes in which rare deleterious variants have been reported in individuals with severe COVID-19, (2) 281 genes located in susceptibility loci identified by the COVID-19 Host Genetics Initiative, or (3) 32 additional genes of immunologic relevance and/or therapeutic potential. Our analyses indicate there are no significant associations with rare protein-coding variants with detectable effect sizes at our current sample sizes. Analyses will be updated as additional data become available, and results are publicly available through the Regeneron Genetics Center COVID-19 Results Browser.

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Topics: Exome (61%)

14 Citations

Open accessJournal ArticleDOI: 10.3389/FIMMU.2021.719115
Abstract: Introduction: Loss-of-function TLR7 variants have been recently reported in a small number of males to underlie strong predisposition to severe COVID-19. We aimed to determine the presence of these rare variants in young men with severe COVID-19. Methods: We prospectively studied males between 18 and 50 years-old without predisposing comorbidities that required at least high-flow nasal oxygen to treat COVID-19. The coding region of TLR7 was sequenced to assess the presence of potentially deleterious variants. Results: TLR7 missense variants were identified in two out of 14 patients (14.3%). Overall, the median age was 38 (IQR 30-45) years. Both variants were not previously reported in population control databases and were predicted to be damaging by in silico predictors. In a 30-year-old patient a maternally inherited variant [c.644A>G; p.(Asn215Ser)] was identified, co-segregating in his 27-year-old brother who also contracted severe COVID-19. A second variant [c.2797T>C; p.(Trp933Arg)] was found in a 28-year-old patient, co-segregating in his 24-year-old brother who developed mild COVID-19. Functional testing of this variant revealed decreased type I and II interferon responses in peripheral mononuclear blood cells upon stimulation with the TLR7 agonist imiquimod, confirming a loss-of-function effect. Conclusions: This study supports a rationale for the genetic screening for TLR7 variants in young men with severe COVID-19 in the absence of other relevant risk factors. A diagnosis of TLR7 deficiency could not only inform on treatment options for the patient, but also enables pre-symptomatic testing of at-risk male relatives with the possibility of instituting early preventive and therapeutic interventions.

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Topics: Genetic testing (52%)

9 Citations

Open accessJournal ArticleDOI: 10.1038/S41525-021-00220-W
Axel Schmidt1, Sophia Peters1, Alexej Knaus2, Hemmen Sabir1  +14 moreInstitutions (3)
Abstract: Among children, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections are typically mild. Here, we describe the case of a 3.5-year-old girl with an unusually severe presentation of coronavirus disease (COVID-19). The child had an autoinflammatory disorder of unknown etiology, which had been treated using prednisolone and methotrexate, and her parents were half cousins of Turkish descent. After 5 days of nonspecific viral infection symptoms, tonic-clonic seizures occurred followed by acute cardiac insufficiency, multi-organ insufficiency, and ultimate death. Trio exome sequencing identified a homozygous splice-variant in the gene TBK1, and a homozygous missense variant in the gene TNFRSF13B. Heterozygous deleterious variants in the TBK1 gene have been associated with severe COVID-19, and the variant in the TNFRSF13B gene has been associated with common variable immunodeficiency (CVID). We suggest that the identified variants, the autoinflammatory disorder and its treatment, or a combination of these factors probably predisposed to lethal COVID-19 in the present case.

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5 Citations


19 results found

Journal ArticleDOI: 10.1111/J.2517-6161.1996.TB02080.X
Abstract: SUMMARY We propose a new method for estimation in linear models. The 'lasso' minimizes the residual sum of squares subject to the sum of the absolute value of the coefficients being less than a constant. Because of the nature of this constraint it tends to produce some coefficients that are exactly 0 and hence gives interpretable models. Our simulation studies suggest that the lasso enjoys some of the favourable properties of both subset selection and ridge regression. It produces interpretable models like subset selection and exhibits the stability of ridge regression. There is also an interesting relationship with recent work in adaptive function estimation by Donoho and Johnstone. The lasso idea is quite general and can be applied in a variety of statistical models: extensions to generalized regression models and tree-based models are briefly described.

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Topics: Lasso (statistics) (70%), Elastic net regularization (68%), Residual sum of squares (58%) ... read more

36,018 Citations

Open accessJournal ArticleDOI: 10.1001/JAMA.2020.2648
Zunyou Wu1, Jennifer M. McGoogan1Institutions (1)
07 Apr 2020-JAMA
Abstract: Background: Hospitalised COVID-19 patients are frequently elderly subjects with co-morbidities receiving polypharmacy, all of which are known risk factors for d

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Topics: Outbreak (56%)

10,464 Citations

Open accessJournal ArticleDOI: 10.1038/NMETH0410-248
Ivan Adzhubei1, Steffen Schmidt2, Leonid Peshkin3, Vasily Ramensky4  +4 moreInstitutions (5)
01 Apr 2010-Nature Methods
Abstract: To the Editor: Applications of rapidly advancing sequencing technologies exacerbate the need to interpret individual sequence variants. Sequencing of phenotyped clinical subjects will soon become a method of choice in studies of the genetic causes of Mendelian and complex diseases. New exon capture techniques will direct sequencing efforts towards the most informative and easily interpretable protein-coding fraction of the genome. Thus, the demand for computational predictions of the impact of protein sequence variants will continue to grow. Here we present a new method and the corresponding software tool, PolyPhen-2 (, which is different from the early tool PolyPhen1 in the set of predictive features, alignment pipeline, and the method of classification (Fig. 1a). PolyPhen-2 uses eight sequence-based and three structure-based predictive features (Supplementary Table 1) which were selected automatically by an iterative greedy algorithm (Supplementary Methods). Majority of these features involve comparison of a property of the wild-type (ancestral, normal) allele and the corresponding property of the mutant (derived, disease-causing) allele, which together define an amino acid replacement. Most informative features characterize how well the two human alleles fit into the pattern of amino acid replacements within the multiple sequence alignment of homologous proteins, how distant the protein harboring the first deviation from the human wild-type allele is from the human protein, and whether the mutant allele originated at a hypermutable site2. The alignment pipeline selects the set of homologous sequences for the analysis using a clustering algorithm and then constructs and refines their multiple alignment (Supplementary Fig. 1). The functional significance of an allele replacement is predicted from its individual features (Supplementary Figs. 2–4) by Naive Bayes classifier (Supplementary Methods). Figure 1 PolyPhen-2 pipeline and prediction accuracy. (a) Overview of the algorithm. (b) Receiver operating characteristic (ROC) curves for predictions made by PolyPhen-2 using five-fold cross-validation on HumDiv (red) and HumVar3 (light green). UniRef100 (solid ... We used two pairs of datasets to train and test PolyPhen-2. We compiled the first pair, HumDiv, from all 3,155 damaging alleles with known effects on the molecular function causing human Mendelian diseases, present in the UniProt database, together with 6,321 differences between human proteins and their closely related mammalian homologs, assumed to be non-damaging (Supplementary Methods). The second pair, HumVar3, consists of all the 13,032 human disease-causing mutations from UniProt, together with 8,946 human nsSNPs without annotated involvement in disease, which were treated as non-damaging. We found that PolyPhen-2 performance, as presented by its receiver operating characteristic curves, was consistently superior compared to PolyPhen (Fig. 1b) and it also compared favorably with the three other popular prediction tools4–6 (Fig. 1c). For a false positive rate of 20%, PolyPhen-2 achieves the rate of true positive predictions of 92% and 73% on HumDiv and HumVar, respectively (Supplementary Table 2). One reason for a lower accuracy of predictions on HumVar is that nsSNPs assumed to be non-damaging in HumVar contain a sizable fraction of mildly deleterious alleles. In contrast, most of amino acid replacements assumed non-damaging in HumDiv must be close to selective neutrality. Because alleles that are even mildly but unconditionally deleterious cannot be fixed in the evolving lineage, no method based on comparative sequence analysis is ideal for discriminating between drastically and mildly deleterious mutations, which are assigned to the opposite categories in HumVar. Another reason is that HumDiv uses an extra criterion to avoid possible erroneous annotations of damaging mutations. For a mutation, PolyPhen-2 calculates Naive Bayes posterior probability that this mutation is damaging and reports estimates of false positive (the chance that the mutation is classified as damaging when it is in fact non-damaging) and true positive (the chance that the mutation is classified as damaging when it is indeed damaging) rates. A mutation is also appraised qualitatively, as benign, possibly damaging, or probably damaging (Supplementary Methods). The user can choose between HumDiv- and HumVar-trained PolyPhen-2. Diagnostics of Mendelian diseases requires distinguishing mutations with drastic effects from all the remaining human variation, including abundant mildly deleterious alleles. Thus, HumVar-trained PolyPhen-2 should be used for this task. In contrast, HumDiv-trained PolyPhen-2 should be used for evaluating rare alleles at loci potentially involved in complex phenotypes, dense mapping of regions identified by genome-wide association studies, and analysis of natural selection from sequence data, where even mildly deleterious alleles must be treated as damaging.

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Topics: Multiple sequence alignment (54%), Mutation (genetic algorithm) (53%), Sequence analysis (50%) ... read more

10,175 Citations

Open accessJournal ArticleDOI: 10.1093/NAR/GKG509
Pauline C. Ng1, Steven HenikoffInstitutions (1)
Abstract: Single nucleotide polymorphism (SNP) studies and random mutagenesis projects identify amino acid substitutions in protein-coding regions. Each substitution has the potential to affect protein function. SIFT (Sorting Intolerant From Tolerant) is a program that predicts whether an amino acid substitution affects protein function so that users can prioritize substitutions for further study. We have shown that SIFT can distinguish between functionally neutral and deleterious amino acid changes in mutagenesis studies and on human polymorphisms. SIFT is available at

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Topics: Protein methods (51%), Amino acid (51%)

4,494 Citations

Open accessJournal ArticleDOI: 10.1093/NAR/GKY427
Abstract: Homology modelling has matured into an important technique in structural biology, significantly contributing to narrowing the gap between known protein sequences and experimentally determined structures. Fully automated workflows and servers simplify and streamline the homology modelling process, also allowing users without a specific computational expertise to generate reliable protein models and have easy access to modelling results, their visualization and interpretation. Here, we present an update to the SWISS-MODEL server, which pioneered the field of automated modelling 25 years ago and been continuously further developed. Recently, its functionality has been extended to the modelling of homo- and heteromeric complexes. Starting from the amino acid sequences of the interacting proteins, both the stoichiometry and the overall structure of the complex are inferred by homology modelling. Other major improvements include the implementation of a new modelling engine, ProMod3 and the introduction a new local model quality estimation method, QMEANDisCo. SWISS-MODEL is freely available at

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4,178 Citations

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