Skip to content
naulon

No retraction, correction or concern found when last checked on Oct 17, 2026.

X-linked recessive TLR7 deficiency in ~1% of men under 60 years old with life-threatening COVID-19

Takaki Asano, Bertrand Boisson, Fanny Onodi and 97 more

Science Immunology · 2021 · CC BY

doi:10.1126/sciimmunol.abl4348

Abstract

TLR7 and plasmacytoid dendritic cells are essential for type I IFN–dependent immunity to SARS-CoV-2 in the lungs.

Full text

From PubMed Central, U.S. National Library of Medicine, as current on Oct 17, 2026. Paragraph numbers are ours, so an answer can point at one.

INTRODUCTION

Interindividual clinical variability in the course of SARS-CoV-2 infection is vast, ranging from silent infection to lethal disease. The greatest risk factor for life-threatening COVID-19 pneumonia is age, with a doubling in risk every five years from the age of five years onward, and a sharp rise after the age of 65 years. Other epidemiological risk factors, including common genetic variants, have only modest effects, with odds ratios (ORs) < 2 and typically < 1.5 (2). One intriguing observation is the approximately 1.5 times higher risk in men, which seems to be age-independent. The COVID Human Genetic Effort consortium (www.covidhge.com) has enrolled an international cohort of patients, with the aim of investigating genetic and immunological causes of life-threatening COVID-19 pneumonia. We previously tested the hypothesis that critical influenza and critical COVID-19 can be allelic, and showed that life-threatening COVID-19 pneumonia can be caused by rare inborn errors of autosomal genes controlling TLR3- and IRF7-dependent type I interferon (IFN) immunity. These disorders were found in 23 men and women aged 17 to 77 years (mean: 48 years). Remarkably, four unrelated patients aged 25 to 50 years had autosomal recessive IFNAR1 (n=2) or IRF7 (n=2) deficiency. These patients had no previous history of severe viral illness, including influenza pneumonia, implying that these genetic disorders unexpectedly show incomplete penetrance for critical influenza. These findings revealed that TLR3- and IRF7-dependent type I IFN immunity is essential for host defense against SARS-CoV-2 infection in the respiratory tract.

We also found pre-existing neutralizing auto-Abs against type I IFN in at least 10% of the patients from this cohort. These auto-Abs were found in 101 patients, mostly men (95%), and older members of the cohort, which included patients with inborn errors, as they were aged 25 to 87 years (mean: 65 years). These findings have been replicated in five other cohorts. These auto-Abs predated SARS-CoV-2 infection and were highly likely to be causal for critical COVID-19 pneumonia, because (i) they were found in samples drawn before infection in some patients, (ii) they were found in about 0.3% of the general population before the age of 65 years, (iii) they were absent from patients with asymptomatic or paucisymptomatic (mild) SARS-CoV-2 infection, (iv) they were of childhood onset in patients with various disorders — including autoimmune polyendocrinopathy type I (APS-1) — known to be at very high risk of life-threatening COVID-19, and (v) they have been shown to underlie a third of adverse reactions to the live attenuated viral vaccine for yellow fever. Collectively, these studies showed that type I IFNs are essential for protective immunity to SARS-CoV-2 in the respiratory tract, but are otherwise surprisingly redundant. Auto-Abs against type I IFNs also provide a first explanation for both the biased sex ratio and the higher risk of critical COVID-19 in patients over the age of 65 years. Here, we tested the hypothesis that critical and unexplained COVID-19 pneumonia in men may be due to rare variants on the X- chromosome.

Enrichment for very rare TLR7 non-synonymous variants in male patients

We tested the hypothesis of genetic homogeneity for X-linked recessive disorders in male individuals with critical COVID-19 pneumonia (hereafter referred to as “patients”, see Materials and Methods). We analyzed an international cohort of 1,202 unrelated male patients aged 6 months to 99 years (mean: 52.9 years) that possessed no known inborn errors of TLR3- and IRF7-dependent type I IFN immunity and without neutralizing auto-Abs against type I IFNs (reported in an accompanying paper) (Table S1). We also analyzed 331 asymptomatic or paucisymptomatic infected male subjects aged 1.3 to 102 years (mean: 38.7 years), with positive results for PCR and/or serological screening for SARS-CoV-2 infection (hereafter referred to as “controls”) (Table S1). We sequenced the exomes (n=1,035) or genomes (n=498) of these patients and controls. We selected in-frame and out-of-frame non-synonymous variants of protein-coding exons that are very rare, that is, with a minor allele frequency (MAF) below 10−4 in the full gnomAD database (v2.1.1) containing sequences from both male and female individuals. We compared the proportions of patients and controls carrying at least one qualifying variant, by Firth bias-corrected logistic regression adjusted for age and ethnicity (Fig. S1A). We found non-synonymous variants in at least five patients for 226 of 731 genes on the X chromosome, resulting in a Bonferroni-corrected significance threshold of 2.2x10−4 (Data file S1). TLR7 was the highest ranked of these genes (uncorrected P-value = 3.5×10−5) and the only gene that remained significant after correction for multiple testing (corrected P-value =7.8×10−3), with 21 unrelated patients carrying one very rare (n=4 patients), two very rare (n=1 patient), or one private (n=16 patients) non-synonymous variant (Fig. 1A, Table S2). One variant (L988S) was recurrent, found in three patients, including a patient carrying two very rare variants (M854I;L988S). No such variants were found in the controls. The same analysis performed on very rare (MAF<10−4) synonymous TLR7 variants showed no enrichment in patients (one carrier) relative to controls (three carriers).

Human TLR7 is an endosomal receptor of ribonucleic acids expressed by B cells and myeloid subsets, the stimulation of which in plasmacytoid dendritic cells (pDCs) results in the production of large amounts of type I IFN. We observed no significant enrichment for coding non-synonymous variants of the X-linked gene TLR8 (P-value = 0.68, Table S2), the product of which, TLR8, is endosomal and can be stimulated by some synthetic TLR7 agonists, with an expression pattern and signaling pathway overlapping those of TLR7. Unlike TLR7, TLR8 is expressed on granulocytes but not on pDCs, possibly accounting for its gain-of-function mutations underlying a phenotype different from type I interferonopathies. Overall, we found an enrichment in very rare or private non-synonymous TLR7 variants among the male patients with critical COVID-19 pneumonia (n=21, 1.7%) of our cohort (n=1,202), including one man over the age of 60 years.

The TLR7 mutant alleles of 16 of the 21 unrelated patients with critical COVID-19 pneumonia are biochemically deleterious

The 21 unrelated patients carried 20 different TLR7 alleles. We expressed the 20 TLR7 mutant proteins in human embryonic kidney (HEK) 293T cells, which have no endogenous TLR7 and TLR8 expression, by transient transfection with the corresponding cDNAs. Immunoblotting of protein extracts with a TLR7-specific mAb showed an absence of TLR7 protein for p.N158Tfs*11 and p.L227fs* and the presence of truncated proteins for K684* and F670Lfs*8 (Fig. 1B). The other mutant TLR7 proteins were produced in normal amounts (Fig. 1B). We tested their function by cotransfection with an NF-κB-specific luciferase reporter. We measured luciferase activity upon stimulation with R848, an agonist of both TLR7 and TLR8 (Fig. 1C). Twelve of the 20 alleles were loss-of-function (LOF) (including L988S in two patients, and M854I;L988S in another), three (p.L372M, p.I657T and p.P715S) were hypomorphic (activity < 25%), and the remaining five were neutral (Fig. 1C, Data file S2). Similar results were obtained with imiquimod and CL264, two TLR7-specific agonists (Fig. S1B, S1C). We also tested eight other private (p.S301P, p.Q710Rfs*18, p.V795F), very rare (MAF <10−4; p.A288V) or rare (MAF between 10−4 and 10−2; p.V219I, p.A448V, p.R920K, p.A1032T) TLR7 variants previously reported in patients with critical COVID-19. These variants were expressed as truncated or full-length proteins (Fig. S1D). The proteins encoded by the three private variants were found to be LOF, that encoded by the very rare variant (p.A288V) was hypomorphic, and those encoded by the four rare variants were neutral (Fig. 1C, Fig. S1B). Collectively, these findings suggest that 16 of the 21 patients in our cohort (Table 1), as well as only 6 of the previously reported 12 patients carry deleterious TLR7 variants.

The cumulative MAF of deleterious TLR7 alleles is < 6.5x10−4

We also investigated the production and function of all 100 remaining non-synonymous TLR7 variants identified in the general population (141,456 individuals in gnomAD v2.1) that had been reported in men or had a general MAF > 10−5 (Fig. 1D and Fig. S1E, Data file S2). In total, 96 of these variants were missense and three were in-frame small deletions; 10 were weakly expressed, whereas the others had normal levels of expression (Fig. S1F, Data file S2). One variant was a small deletion creating a frameshift found in one man and resulting in an absence of protein production (Fig. S1F, Data file S2). Seven of the 100 variants were LOF and 15 were hypomorphic (< 25% activity) (Data file S2). There were, thus, 24 deleterious TLR7 variants, including the L988S and A288V variants found in four patients with critical COVID-19 pneumonia. Each of these 24 deleterious variants had an individual MAF < 1.3x10−4 in men and their cumulative MAF in men was 6.5 x10−4 (Data file S2, Table S3). The cumulative MAF of strictly LOF TLR7 alleles (excluding hypomorphic alleles) in men is about 2.2 x10−4 (Data file S2). Overall, we found 12 LOF and three hypomorphic TLR7 alleles in 16 unrelated men with critical COVID-19 pneumonia, whereas deleterious alleles were not found in men with asymptomatic or paucisymptomatic infection. Moreover, deleterious TLR7 alleles in the general population had individual and cumulative MAF values in men of < 1.3x10−4 and < 6.5x10−4, respectively (Fig. 1E, Data file S2). The rarity of TLR7 deficiency in the general population is consistent with TLR7 deficiency underlying critical COVID-19. Collectively, these findings suggest that X-linked recessive (XR) TLR7 deficiency is a genetic etiology of life-threatening COVID-19 pneumonia in men.

High clinical penetrance of inherited TLR7 deficiency in the patients’ families

The 16 patients were of three major ethnic origins, as confirmed by principal component analysis (PCA) of their exomes or genomes, and they were resident in seven countries (France n=2, Spain n=3, Italy n=3, Turkey n=2, Sweden n=1, Iran n=4, Colombia n=1) (Fig. 2A, Fig. 2C, Fig. S1, Table 1, Data file S3). The patients were hospitalized for critical COVID-19 between March 2020 and June 2021. Blood samples (diluted 1/10) from these 16 patients contained no auto-Abs neutralizing 10 ng/mL IFN-α2 and/or -ω. The patients were aged 7 to 71 years and their mean age was lower than that of the total cohort (mean age of 34.4 years, versus 52.9 years for the total cohort, in which age ranged from 0.5 to 99 years). TLR7-deficient patients accounted for about 1.8% of the patients below the age of 60 years (15 patients) and 1.3% of the entire cohort (16 patients). Two patients died and 14 survived (Fig. 2A, Table 1). Sanger sequencing of the TLR7 locus in the relatives of these patients identified the deleterious alleles in 16 heterozygous women from eleven families and seven hemizygous men from seven families (Fig. 2A). Based on the ten DNA samples available from the patients’ mothers, only one of the TLR7 variants (L372M) was de novo in the index case. Five of the seven hemizygous relatives of the index cases had antibodies against SARS-CoV-2 (Fig. 2A, Data file S3). One 29-year-old adult (Kindred J, P11) was hospitalized for critical pneumonia, and another 27-year-old adult (L.II.3) was hospitalized for severe pneumonia (with low-flow oxygen (<6L/min)). The remaining three were two five-year-old boys, one of whom had been hospitalized for moderate COVID-19 pneumonia (without oxygen therapy) (D.II.2), the other having no relevant clinical history (M.II.2), and one 38-year-old adult with no relevant clinical history (E.II.4) (Data file S3). The other two male carriers did not report SARS-CoV-2 infection and had negative serological results for antibodies against the SARS-CoV-2 S and N proteins.

Inherited TLR7 deficiency in patients with severe COVID-19 pneumonia

Given these results, we also analyzed 262 other, unrelated male patients with severe (but not critical) COVID-19 pneumonia (mean age: 51.0 years). We identified a new private LOF variant (p.N75H) in two male patients from two Turkish families (P18 and P19), aged 12 and 7 years, respectively, who were subsequently found to be fourth-degree relatives (Fig. 1B, 1C, 1D, Fig. 2B, Fig. S1B, Data file S2, Data file S3). Their mothers are heterozygous for this variant. The clinical penetrance of critical COVID-19 in men is therefore high, but not complete, and TLR7 deficiency can also underlie severe COVID-19. The absence of biochemically deleterious TLR8 variants in our cohort of patients with critical COVID-19 (Fig. S2) and its lack of expression on pDCs suggest that TLR8 is not a modifier of the SARS-CoV-2-related clinical phenotype of TLR7 deficiency, although it is adjacent to TLR7 on the X chromosome and can be stimulated by overlapping molecules. Perhaps more relevant to the understanding of the incomplete penetrance is the age of the patients. Of the 23 male patients carrying deleterious alleles of TLR7 infected with SARS-CoV-2, the 20 patients who developed severe (n=3) or critical (n=17) COVID-19 were aged 7-71 years (mean: 32.4 years) whereas the three patients who developed asymptomatic, mild, or moderate infection were younger: 5, 5, and 38 years (mean: 16 years). Blood pDC counts decrease with age, and this may contribute to the apparent increase in penetrance with age. In addition, a VirScan study of the serum samples of five index cases and three TLR7 hemizygous relatives revealed prior infection with diverse viruses (Fig. S3). None had previously been hospitalized for a severe viral illness, including influenza pneumonia. This cohort of patients thus suggests that TLR7 deficiency does not underlie severe disease caused by common viral infections other than SARS-CoV-2, or if so, with lower penetrance.

Deleterious TLR7 alleles abolish B cell responses to TLR7 agonists

As a first approach to testing the impact of deleterious TLR7 alleles in the patients’ cells, we tested Epstein-Barr virus-transformed B cell lines (EBV-B cells) from healthy controls and patients carrying the hemizygous p.K684* (P12) or p.H781L (P14) variants. The endogenous expression of the p.H781L TLR7 protein was normal, whereas p.K684* generated a truncated protein (Fig. 2D). In response to agonists of TLR7 (imiquimod) or TLR7 plus TLR8 (R848), the EBV-B cell lines carrying these two mutations failed to produce TNF (Fig. 2E, Fig. S4A, S4B). The lentiviral transduction of these TLR7-deficient EBV-B cells (from P12 and P14) with a WT TLR7 cDNA was unsuccessful, despite numerous attempts, and this was also the case for control EBV-B cells, perhaps because the overproduction of TLR7 is toxic in B cells. Consistent with this view, we were able to express this cDNA in IRAK4- or MyD88-deficient EBV-B cells. We therefore investigated whether the addition of an IRAK4 inhibitor (PF06650833) would permit the expression of WT TLR7 in control and TLR7-mutated EBV-B cells. This approach was successful, and WT TLR7 expression restored responses to TLR7 agonists (after removal of the inhibitor) (Fig. 2F, Fig. S4C). Hemizygosity for LOF TLR7 alleles thus abolished responses to TLR7 stimulation in EBV-B cells, a phenotype that was rescued by WT TLR7 expression. Collectively, these findings further suggest that XR TLR7 deficiency is a genetic etiology of severe/critical COVID-19 pneumonia.

The TLR7-mutated patients’ myeloid cells, including pDCs, do not respond to TLR7 agonists

Human TLR7 is known to be expressed and functional only in leukocyte subsets: plasmacytoid and classical dendritic cells (pDCs and mDCs), monocytes (classical, intermediate, and non-classical), and B cells. TLR8 is expressed in mDCs but not pDCs, monocytes but not B cells, and neutrophils (unlike TLR7). Neither TLR7 nor TLR8 mRNAs have been detected in the lung or pulmonary epithelial cells. Deep immunophenotyping by CyTOF in seven patients with TLR7 deficiency revealed no major abnormalities in 18 peripheral blood leukocyte subsets, including pDCs, mDCs, monocytes, and B cells (Fig. 3A, Fig. S5A). We previously reported inherited IRF7 deficiency in a child with critical influenza pneumonia and two unrelated adults with critical COVID-19 pneumonia. This defect disrupts the amplification of type I IFNs in all cell types, including pDCs, which are normally the main producers of type I IFN upon blood cell stimulation with TLR7 agonists or viruses, due to their constitutive expression of IRF7. We hypothesized that TLR7 deficiency in pDCs impairs the production of type I IFN by these cells in response to ssRNA. We confirmed that TLR7 was expressed on pDCs, and that TLR8 was not (Fig. 3B, S5B, S5C). We measured the production of type I IFNs by purified leukocyte subsets (pDCs, mDCs, monocytes, B cells, T cells), in response to TLR7, TLR8 and TLR9 agonists (Fig. 3C, Fig. S5D). We confirmed that pDCs produced 100-1,000 times more type I IFN per cell than other leukocyte subsets upon TLR7 stimulation (Fig. 3C, Fig. S5D). We purified pDCs from P8 and P14 and analyzed their production of type I IFNs in response to CL264 and class C CpG oligonucleotide (CpG-c), relative to that of pDCs from healthy relatives, using a cytometric bead array (CBA) (Fig. 3D). pDCs from P8 and P14 did not produce type I IFNs (or IL-6) upon stimulation with a TLR7 agonist, whereas they responded to a TLR9 agonist (Fig. 3D). Moreover, agonist-induced up-regulation of PD-L1 and CD80 defines the maturation of pDCs into the S1 (PD-L1high/CD80low), S2 (PD-L1high/CD80high), and S3 (PD-L1low/CD80high) subsets. This maturation was not observed in the pDCs of P8 and P14, but was detected in the pDCs of healthy relatives and controls (Fig. 3E, Fig. S5E). Thus, pDCs from patients with TLR7 mutations do not respond to TLR7 agonists in terms of maturation into specialized subsets and type I IFN production.

The TLR7-deficient patients’ pDCs respond poorly to SARS-CoV-2

A plausible mechanism accounting for the severity of COVID-19 in TLR7-deficient patients is the impairment of type I IFN production by pDCs upon stimulation with SARS-CoV-2, which can enter these cells, but cannot replicate productively within them. Indeed, we previously showed that the activation of human pDCs by SARS-CoV-2 depends on IRAK4 and UNC-93B, but not TLR3. We tested the hypothesis that TLR7 is an essential pDC sensor of SARS-CoV-2, upstream from IRAK4 and UNC-93B, by infecting pDCs and pDC-depleted leukocytes from healthy controls and TLR7-deficient patients with SARS-CoV-2 for 24 hours. Control pDC-depleted leukocytes infected with SARS-CoV-2 displayed no significant up- or down-regulation of gene expression (Fig. S6A). By contrast, transcriptomic analysis showed a strong up-regulation of the type I IFN transcriptional module in pDCs from healthy controls, which was greatly reduced in pDCs from TLR7-deficient patients (Fig. 4A). Induction of the 17 type I IFN genes in pDCs from TLR7-deficient patients was 10 to 100 times weaker than that in pDCs from healthy individuals (Fig. 4B, S6B). We also analyzed the functional specialization of pDC subsets (S1-, S2-, and S3-pDC subsets) in response to SARS-CoV-2 activation. pDCs from P14 cultured with SARS-CoV-2 for 24 hours displayed abnormally low levels of maturation into the S1-subset —the pDC subset principally responsible for IFN-α production upon SARS-CoV-2 infection (Fig. S6C). Finally, we evaluated the amount of type I IFNs secreted by SARS-CoV-2-infected pDCs. All 13 individual IFN-α forms were produced in significantly smaller amounts by TLR7-deficient pDCs than by control pDCs (Fig. 4C, S6D). However, IFN-α production by TLR7-deficient pDCs upon SARS-CoV-2 infection was impaired, but not entirely abolished, as in UNC-93B- or IRF7-deficient pDCs, implying that there are also TLR7-independent sensors of SARS-CoV-2 in pDCs and suggesting that TLR9 is involved. The TLR7-deficient pDCs’ normal response to TLR9 agonists (Fig. 3D, 4A, 4B, S6D) is consistent with this hypothesis, while also suggesting that genetic or epigenetic variations of TLR9 responses may contribute to the apparently age-dependent penetrance of TLR7 deficiency. Thus, SARS-CoV-2 triggers type I IFN induction in pDCs in a manner that is dependent on TLR7, but not exclusively so. As pDCs are normally the main leukocytes producing type I IFN in such conditions, and type I IFN is essential for protective immunity to SARS-CoV-2, these findings suggest that XR TLR7 deficiency underlies critical or severe COVID-19 pneumonia by disrupting TLR7-and pDC-dependent type I IFN production.

DISCUSSION

We report XR TLR7 deficiency as a genetic etiology of severe/critical COVID-19 pneumonia in 20 unrelated male patients, aged 7 to 71 years, from seven countries. Only one of these 20 patients (5%) was older than 60 years, consistent with our previous observation that only five of 23 patients (21.7%) with inborn errors of TLR3-dependent type I IFN immunity were older than 60 years. This suggests that these genetic defects are mostly found in the youngest patients. This contrasts with the situation for auto-Abs against type I IFNs, which are found mostly in patients over the age of 60 years. Importantly, patients with these auto-Abs do not overlap with those bearing inborn errors of TLR3- or TLR7-dependent type I IFNs. TLR7-deficient patients accounted for about 1.8% of the unrelated male patients with critical COVID-19 pneumonia below the age of 60 years in our cohort and accounted for 1.3% of the total cohort. This proportion remained around the same when severe COVID-19 pneumonia was also taken into account (1.7% males below 60 years; 1.2% of all the male patients in the total cohort). We also found that six of the 12 previously reported patients with a TLR7 variant had TLR7 deficiency. It would be interesting to test experimentally the undisclosed TLR7 variants reported to be enriched in another study. Our discovery provides an explanation for the higher risk of severe and critical disease in men than in women under the age of 60 years, complementing our previous observation of a much higher frequency of neutralizing auto-Abs against type I IFNs in men than in women with critical COVID-19 pneumonia for patients over the age of 60 years.

Previous reports of patients with critical COVID-19 pneumonia due to inborn errors of TLR3-dependent type I IFN immunity, including autosomal recessive IRF7 or IFNAR1 deficiency, or due to auto-Abs neutralizing type I IFNs, strongly suggest that critical disease in TLR7-deficient patients is a consequence of impaired type I IFN production upon SARS-CoV-2 infection. The absence of biochemically deleterious X-linked TLR8 variants in our cohort of patients suggests that TLR8 is not essential for host defense against SARS-CoV-2. This is consistent with the modest capacity of TLR8 to induce type I IFN and its lack of expression on pDCs, and with the inflammatory phenotype of TLR8 gain-of-function mutations, which do not underlie a type I interferonopathy. Patients with inherited IRAK4 or MyD88 deficiency, whose cells do not respond to the stimulation of IL-1Rs and TLRs other than TLR3, including TLR7, have not been reported to display any severe viral illness over the almost 20 years since the discovery of IRAK-4 deficiency. Moreover, UNC-93B-deficient pDCs produced normal amounts of type I IFN in response to seasonal influenza virus. This was intriguing, as strong negative selection operates at the human TLR7, TLR8, and TLR9 loci. Our study provides an answer to this riddle, by establishing that TLR7 is essential for protective immunity to SARS-CoV-2. Patients with IRAK4, MyD88, or UNC93B deficiency are now predicted to be vulnerable to SARS-CoV-2. Critical COVID-19 and seasonal influenza can be caused by inborn errors of TLR3-dependent type I IFN immunity, but susceptibility to these infections is not allelic at the TLR7 locus. It is, nevertheless, tempting to speculate that TLR7 might also be essential for host defense against more virulent, pandemic viruses, including both coronaviruses and influenza viruses.

Through the discovery of the essential nature of TLR7 for the induction of type I IFN in response to SARS-CoV-2, our study also reveals the essential function of human pDCs in host defense. The constitutively high levels of IRF7 in these cells make them the most potent producers of type I IFN in the blood, and perhaps in the entire human body, and this has long suggested a possible key role in antiviral immunity. However, the essential and redundant roles of this leukocyte subset have yet to be determined, in the absence of human pDC-specific deficiencies causally underlying a clinical phenotype. It has long been suspected, but never proved, that pDCs are essential for host defense in natural conditions. Inherited IRF7 deficiency, which underlies critical influenza or COVID-19 pneumonia, disrupts the production of type I IFNs not only by pDCs, but also by all other cell types, including pulmonary epithelial cells. Likewise, patients with GATA2 deficiency, who are prone to critical influenza, lack pDCs, but these patients also lack many other blood cell subsets. Inherited IFNAR1 deficiency underlies critical COVID-19 probably due to its broad cellular impact. By contrast, inborn errors of the TLR3 pathway underlie critical influenza or COVID-19 pneumonia by impairing the production of type I IFNs by cells other than pDCs, such as pulmonary epithelial cells. Our study indicates that pulmonary epithelial cells are not sufficient for host defense against SARS-CoV-2, as these cells do not express TLR7. Inborn errors of TLR7 are pathogenic by impairing the production of type I IFNs by blood pDCs, which are unique in their production of large amounts of both TLR7 and IRF7. pDCs express other viral sensors, including TLR9 (for DNA), MDA5 and RIG-I (for dsRNA), but TLR7 deficiency impairs their capacity to produce large enough amounts of type I IFN in response to SARS-CoV-2 in the respiratory tract. Overall, by disrupting pDC-dependent type I IFN production, XR TLR7 deficiency accounts for at least 1% of cases of life-threatening COVID-19 pneumonia in men under 60 years.

Study design

We searched for X-linked inborn errors of immunity in male patients with critical SARS-CoV-2 pneumonia. We screened our WES database of 1,202 male patients with critical SARS-CoV-2 pneumonia (‘patients’) and 331 male subjects with asymptomatic or paucisymptomatic infection (‘controls’). We tested the association of X-linked genes with critical SARS-CoV-2 pneumonia using a Firth bias-corrected logistic regression model including the first five principal components of the PCA to account for the ethnic heterogeneity of the cohorts and age in years. We then tested the activity of TLR7 variants in transduced cell lines and of TLR7 genotypes in hemizygous patients’ cell lines. Lastly, we tested the patients’ pDCs for their response to both TLR7 agonists and SARS-CoV-2.

Cohort recruitment and consent

This study included 1,202 male patients with life-threatening COVID-19 pneumonia, defined as patients with pneumonia who developed critical disease, whether pulmonary with high-flow oxygen (> 6L/min) or mechanical ventilation (CPAP, BIPAP, intubation), septic shock, or any other type of organ damage requiring ICU admission. This study also included patients with severe COVID-19 pneumonia, defined as hospitalized patients with pneumonia that required low-flow oxygen (<6L/min); moderate COVID-19 pneumonia, defined as patients with pneumonia but did not require oxygen therapy; and mild COVID-19, defined as patients with mild upper respiratory symptoms but without pneumonia. Patients who developed Kawasaki-like syndrome were excluded. The age of the patients ranged from 0.5-99 years, with a mean age of 52.9 years (SD 16.4 years). Asymptomatic or paucisymptomatic individuals (n= 331) were recruited on the basis of positive PCR or serological tests for SARS-CoV-2 in the absence of symptoms. These individuals were close contacts of patients or were recruited after clinical screening. The age of the asymptomatic or paucisymptomatic individuals ranged from 1.3-102 years, with a mean age of 38.7 years (SD: 17.2 years).

All the enrolled subjects provided written informed consent and were collected through protocols conforming to local ethics requirements. For patients enrolled in the French COVID cohort (clinicaltrials.gov NCT04262921), ethics approval was obtained from the CPP IDF VI (ID RCB: 2020-A00256-33) or the Ethics Committee of Erasme Hospital (P2020/203). For subjects enrolled in the COV-Contact study (clinicaltrials.gov NCT04259892), ethics approval was obtained from the CPP IDF VI (ID RCB: 2020-A00280-39). For patients enrolled in the Italian cohort, ethics approval was obtained from the University of Milano-Bicocca School of Medicine, San Gerardo Hospital, Monza – Ethics Committee of the National Institute of Infectious Diseases Lazzaro Spallanzani (84/2020) (Italy), and the Comitato Etico Provinciale (NP 4000 – Studio CORONAlab). STORM-Health care workers were enrolled in the STudio OsseRvazionale sullo screening dei lavoratori ospedalieri per COVID-19 (STORM-HCW) study, with approval from the local IRB obtained on June 18, 2020. Patients and relatives from San Raffaele Hospital (Milan) were enrolled in protocols COVID-BioB/Gene-COVID and, for additional studies, TIGET-06, which were approved by local ethical committee. For patients enrolled in Spain, the study was approved by the Committee for Ethical Research of the Infanta Leonor University Hospital, code 008-20, Committee for Ethical Research of the University Hospital 12 de Octubre, code 16/368 and the Bellvitge University Hospital code PR127/20, the University Hospital of Gran Canaria Dr. Negrín code 2020-200-1 COVID-19 and the Vall d’Hebron University Hospital, code PR(AMI)388/2016. Anonymized samples were sequenced at the NIAID through USUHS/TAGC under non-human subject research conditions; no additional IRB consent was required at the NIH. For patients enrolled in the Swedish COVID cohort, ethics approval was obtained from the Swedish Ethical Review Agency (2020-01911 05).

Next-generation sequencing

Genomic DNA was extracted from whole blood. For the 1,533 patients included, the whole exome (n=1035) or whole genome (n=498) was sequenced at several sequencing centers, including the Genomics Core Facility of the Imagine Institute (Paris, France), the Yale Center for Genome Analysis (USA), the New-York Genome Center (NY, USA), and the American Genome Center (TAGC, USUHS, Bethesda, USA), and the Genomics Division-ITER of the Canarian Health System sequencing hub (Canary Islands, Spain).

For WES, libraries were generated with the Twist Bioscience kit (Twist Human Core Exome Kit), the xGen Exome Research Panel from Integrated DNA Technologies (IDT xGen), the Agilent SureSelect V7 kit or the SeqCap EZ MedExome kit from Roche, and the Nextera Flex for Enrichment-Exome kit (Illumina). Massively parallel sequencing was performed on a HiSeq4000 or NovaSeq6000 system (Illumina). For WES analysis performed at CNAG Barcelona, Spain, capture was performed with the SeqCap EZ Human Exome Kit v3.0 (Roche Nimblegen, USA) and 100-bp paired-end read sequences were obtained on a HiSeq 2000-4000 platform (Illumina, Inc. USA). For the OSR Italian cohort, WES was performed with the Agilent SureSelect V7 kit on a NovaSeq6000 system (Illumina).

For WGS on patients of the Italian cohort (TAGC), genomic DNA samples were dispensed into the wells of a Covaris 96 microTUBE plate (1,000 ng per well) and sheared with the Covaris LE220 Focused-ultrasonicator, at settings targeting a peak size of 410 bp (t:78; Duty:18; PIP:450; 200 cycles). Sequencing libraries were generated from fragmented DNA with the Illumina TruSeq DNA PCR-Free HT Library Preparation Kit, with minor modifications for automation (Hamilton STAR Liquid Handling System), with IDT for Illumina TruSeq DNA UD Index (96 indices, 96 samples) adapters. Library size distribution was assessed and the absence of free adapters or adapter dimers was checked by automated capillary gel electrophoresis (Advanced Analytical Fragment Analyzer). Library concentration was determined by qPCR with the KAPA qPCR Quantification Kit (Roche Light Cycler 480 Instrument II). Sequencing libraries were normalized and combined as 24-plex pools and quantified as above, before dilution to 2.9 nM and sequencing on an Illumina NovaSeq 6000 with the S4 Reagent Kit (300 cycles) and 151+8+8+151 cycle run parameters. Primary sequencing data were demultiplexed with the Illumina HAS2.2 pipeline and sample-level quality control was performed for base quality, coverage, duplicates and contamination (FREEMIX < 0.05 by VerifyBamID). For patients enrolled in the Swedish COVID cohort, sequencing was performed at the Clinical Genomics Stockholm unit of the SciLifeLab (Stockholm, Sweden).

We used the Genome Analysis Software Kit (GATK) (version 3.4-46 or 4) best-practice pipeline to analyze our WES data. We aligned the reads obtained with the human reference genome (hg19), using the maximum exact matches algorithm in the Burrows–Wheeler Aligner (BWA). PCR duplicates were removed with Picard tools (picard.sourceforge.net). The GATK base quality score recalibrator was applied to correct sequencing artifacts. Genotyping was performed with GATK GenotypeGVCFs in the interval intersecting all the capture kits ± 50 bp. Sample genotypes with a coverage < 8X, a genotype quality (GQ) < 20, or a ratio of reads for the less covered allele (reference or variant allele) over the total number of reads covering the position (minor read ratio, MRR) < 20% were filtered out. We filtered out variant sites (i) with a call rate <50% in gnomAD genomes and exomes, (ii) a non-PASS filter in the gnomAD database, (iii) falling in low-complexity or decoy regions, (iv) that were multi-allelic with more than four alleles, (v) with more than 20% missing genotypes in our cohort, and (vi) spanning more than 20 nucleotides. Variant effects were predicted with the Ensembl Variant Effect Predictor (VEP) and the Ensembl GRCh37.75 reference database, retaining the most deleterious annotation obtained from Ensembl canonical transcripts overlapping with RefSeq transcripts.

Statistical analysis

We performed an enrichment analysis focusing on X chromosome genes on our cohort of 1,202 male patients with life-threatening COVID-19 pneumonia without known inborn errors of TLR3- and IRF7-dependent type I IFN immunity and without neutralizing auto-Abs against type I IFNs, and 331 male individuals with asymptomatic or paucisymptomatic infection (Table S1). We considered variants that were predicted to be loss-of-function or missense, with a MAF below 0.0001 (gnomAD v2.1.1). We compared the proportion of patients and controls carrying at least one non-synonymous using the Firth bias-corrected logistic likelihood ratio test implemented in EPACTS (https://genome.sph.umich.edu/wiki/EPACTS) extended to gene based enrichment analysis. In Firth’s regression, a penalty term is placed on the standard maximum likelihood function used to estimate parameters of a logistic regression model. Firth’s can handle genes with no carriers among cases or controls. With no covariates, this corresponds to adding 0.5 in every cell of a 2x2 table of allele counts versus case-control status. We accounted for the ethnic heterogeneity of the cohorts by including the first five principal components of the PCA in the Firth’s logistic regression model. Analyses were also adjusted for age in years. We checked that our adjusted burden test was well-calibrated by also performing an analysis of enrichment in rare (MAF < 0.0001) synonymous variants. PCA was performed with Plink v1.9 software on whole-exome and whole-genome sequencing data, with the 1000 Genomes (1kG) Project phase 3 public database as a reference, using 18,917 exonic variants with a minor allele frequency > 0.01 and a call rate > 0.99.

Cell culture

EBV-B cell lines derived from the patients were grown in complete RPMI 1640 (Life Technologies) supplemented with 10% heat-inactivated fetal bovine serum (FBS). HEK293T cells, derived from the human embryonic kidney 293 cell line, which expresses a mutant version of the SV40 large T antigen, were grown in complete DMEM (Life Technologies) supplemented with 10% FBS. Cells were incubated at 37°C in the presence of 5% CO2.

Expression vectors and transfection experiments

All the TLR7 variants in our analysis were generated by site-directed mutagenesis (Data file S4). The WT or variant alleles were re-introduced into a Myc-DDK-pCMV6 vector (Origene). HEK293T cells, which have no endogenous TLR7 or TLR8 expression, were transfected with the Myc-DDK-pCMV6 vector, empty or containing the WT or a variant allele, in the presence of X-tremeGENE 9 DNA Transfection Reagent (Sigma-Aldrich), according to the manufacturer’s instructions.

Western blotting

For whole-cell extracts, the cells were lysed by incubation in the following buffer (50 mM Tris-HCl, pH 8.0, 150 mM NaCl, 1% NP40), supplemented with a mixture of protease inhibitors (Sigma-Aldrich), for 30 min at 4°C. The lysates were then centrifuged at 21,000 x g for 20 min at 4°C. The supernatants were processed directly for Western blotting. Western blotting was performed on 10 μg of total extract from transfected HEK293T cells, with monoclonal antibodies specific for the leucine-rich repeats to the N terminus within the human TLR7 protein (Cell Signaling Technology; clone, D7), or for amino-acid 1,000 to the C terminus with the human TLR7 protein (Abcam; clone, EPR2088(2)).

Luciferase reporter assay

HEK293T cells, which have no endogenous TLR7 expression, were transfected with the pCMV6 vector bearing wild-type or variant TLR7 (50 ng), the reporter construct pGL4.32 (100 ng), and an expression vector for Renilla luciferase (10 ng), with the X-tremeGENE 9 DNA Transfection Reagent kit (Sigma-Aldrich). The pGL4.32 [luc2P/NF-κB-RE/Hygo] (Promega) reporter vector contains five copies of the NF-κB-responsive element (NF-κB-RE) linked to the luciferase reporter gene luc2P. After 24 hours, the transfected cells were left unstimulated or were stimulated with 1 μg/mL R848 (Resquimod), for activation via TLR7/8 (Invivogen), or 5 μg/mL R837 (Imiquimod) (Invivogen), or 5 μg/mL CL264 (Invivogen), human TLR7-specific agonists, for 24 hours. Relative luciferase activity was then determined by normalizing the values against the firefly:Renilla luciferase signal ratio.

RNA extraction and reverse transcription-quantitative PCR (RT-qPCR)

Total RNA was extracted with the RNeasy Mini Kit (Qiagen), according to the manufacturer’s instructions. Reverse transcription was performed on 1 μg of RNA with random primers and the SuperScript® III reverse transcriptase (Invitrogen), according to the manufacturer’s protocol. Quantitative PCR was then performed with the TaqMan Fast Universal PCR Master Mix (2X) and the FAM-MGB TaqMan TNF exons 1-2 (Hs99999-43_m1) probes. The VIC-TAMRA probe for GUSB (Applied Biosystems, Cat: 4310888E) was used as an endogenous control. Real-time PCR amplification was monitored with the 7500 Fast Real-Time PCR System (Applied Biosystems). Relative expression levels were determined according to the ΔCt method.

ELISA analysis of TNF production in EBV-B cells

ELISA was performed as previously described. We suspended 1x106 EBV-B cells per well in RPMI 1640 supplemented with 10% FBS. The cells were activated by incubation with 1 μg/mL R848, and 5 μg/mL imiquimod for 24 hours. The supernatants were harvested after 24 hours of activation. ELISA determinations of TNF in cell culture supernatants were performed with a kit (Thermo Fisher Scientific), according to the manufacturer’s instructions.

Stable transduction

The WT coding sequence of TLR7 was inserted into pTRIP-CMV-puro-2A. For lentivirus production, HEK293T cells were transfected with 1.6 μg pTRIP-CMV-puro-2A-TLR7-WT (or Mutant: K684*), 0.2 μg pCMV-VSV-G (Addgene), 0.2 μg pHXB2 (NIH-AIDS Reagent 22 Program) and 1 μg psPAX2 (Addgene), with X-treme gene 9 (Roche), according to the manufacturer's instructions. Supernatants were harvested after 24 hours and 8 μg/mL protamine sulfate was added. The lentiviral suspension obtained was used to transduce 2x105 EBV-B cells by spinoculation at 1,200 x g for 2 hours. The transduced cells were selected by incubation on medium containing 1 μg/mL puromycin for two days. The cells were then selected by incubation for a further two days on medium containing 2 μg/mL puromycin. During viral transduction, the cells were cultured with 5 μM IRAK4 inhibitor (PF06650833) (Bio-techne) to prevent cell death due to the overproduction of TLR7. Selected transduced cells were then stimulated with 1 μg/mL R848 or 5 μg/mL imiquimod for 24 hours without IRAK4 inhibitor. The supernatants were harvested after 24 hours of activation. ELISA determinations of TNF in cell culture supernatants were performed with a kit (Thermo Fisher Scientific), according to the manufacturer’s instructions.

VirScan analysis

Patient serum was analyzed by VirScan in two independent experiments as previously described. Briefly, an oligonucleotide library encoding 56 amino acid peptides tiling across the genomes of 206 viral species was synthesized on a releasable DNA microarray and cloned into T7 phage. Patient serum containing 2 μg of IgG was added to the phage library, and immunoprecipitation was performed with Protein A and G beads. Enriched peptides were identified by PCR and Illumina sequencing of the peptide cassette from the immunoprecipitated phage.

Deep immunophenotyping by mass cytometry (CyTOF)

CyTOF was performed on whole blood with the Maxpar Direct Immune Profiling Assay (Fluidigm), according to the manufacturer’s instructions. Cells were frozen at -80°C after overnight staining to eliminate dead cells, and acquisition was performed on a Helios machine (Fluidigm). All the samples were processed within 24 hours of sampling. Data analysis was performed with OMIQ software. Antibody information is listed in supplemental material (Data file S5).

PBMC enrichment using MACS system

Blood were collected from two healthy individuals and separated by the concentration gradient method with Ficoll®️ Paque Plus (Cytiva). After isolations of PBMCs, leucocyte subset (T cell, B cell, monocyte, pDC, and mDC) were purified by negative selection using MACS beads system (Milteni Biotec). Cells were plated into a U-bottomed 96-well plate at a density of 2×104 cells/well for T cells, B cells, monocytes, pDCs, or mDCs in 200 μL/well RPMI-1640 with GlutaMAX supplemented with 10% FBS or 10×104 cells/well for whole blood and PBMCs. Cells were left unstimulated or stimulated with 1μg/mL CL264, 100ng/ml TL8-506 (Invivogen), 1μg/mL R848, 2μM CpG-c (Invivogen), or 12.5ng/ml PMA and 0.125μM ionomycin for 24 hours. The supernatants were harvested after 24 hours of activation. Cytokines production were determined by ELISA (IFN-α - PBL Assay Science, IFN-β- PBL Assay Science, IFN- λ1 (IL-29) - Invivogen, IFN-ω- Invitrogen or IL-8 - R&D SYSTEMS); according to the manufacturer’s instructions.

Analysis for TLR7 and TLR8 expression pattern in peripheral blood mononuclear cells (PBMCs) by flow cytometry

Freshly thawed PBMCs from healthy donors were dispensed into a V-bottomed 96-well plate at a density of 1×106 cells/well, in 200 μL PBS/well. In brief, cells were stained by incubation with the LIVE/DEAD fixable blue dead-cell staining kit (Thermo Fisher Scientific, 1:800) and FcR blocking reagent (Miltenyi Biotec, 1:25) on ice for 15 min. For surface staining, cells were incubated with anti-γδTCR-BUV611 (BD Biosciences, 1:50), anti-CD183-BV750 (BD Biosciences, 1:20), and anti-CD194-BUV615 (BD Biosciences, 1:20) antibodies on ice for 30 min in 0.1% BSA and 0.01% sodium azide in PBS. They were then incubated with anti-CD141-BB515 (BD Biosciences, 1:40), anti-CD57-FITC (Biolegend, 1:83), anti-TCR Vδ2-PerCP (Biolegend, 1:166), anti-TCR Vα7.2-PerCP/Cyanine5.5 (Biolegend, 1:40), anti-TCR Vδ1-PerCP-Vio 700 (Miltenyi Biotec, 1:100), anti-CD14-Spark Blue 550 (Biolegend, 1:40), anti-CD1c-Alexa Fluor 647 (Biolegend, 1:50), anti-CD38-APC/Fire 810 (Biolegend, 1:30), anti-CD27-APC-H7 (BD Biosciences, 1:50), anti-CD127-APC-R700 (BD Biosciences, 1:50), anti-CD19-Spark NIR 685 (Biolegend, 1:83), anti-CD45RA-BUV395 (BD Biosciences, 1:83), anti-CD16-BUV496 (BD Biosciences, 1:166), anti-CD11b-BUV563 (BD Biosciences, 1:100), anti-CD56-BUV737 (BD Biosciences, 1:83), anti-CD8-BUV805 (BD Biosciences, 1:83), anti-hMR1-BV421 (NIH tetramer facility, 1:100), anti-CD11c-BV480 (BD Biosciences, 1:40), anti-CD45-BV510 (Biolegend, 1:83), anti-CD33-BV570 (Biolegend, 1:83), anti-iNKT-BV605 (Biolegend, 1:25), anti-CD161-BV650 (BD Biosciences, 1:25), anti-CCR6-BV711 (Biolegend, 1:83), anti-CCR7- BV785 (Biolegend, 1:40), anti-CD3-Pacific Blue (Biolegend, 1:83), anti-CD20-Pacific Orange (Life Technologies, 1:50), anti-CD123-Super Bright 436 (Invitrogen, 1:40), anti-CD24-PE-Alexa Fluor 610 (Life Technologies, 1:25), anti-CD25-PE-Alexa Fluor 700 (Life Technologies, 1:25), anti-CD294-Biotin (Invitrogen, 1:50), anti-CD209-PE/Cyanine7 (Biolegend, 1:25), anti-CD117-PE/Dazzle 594 (Biolegend, 1:83), anti-HLA-DR-PE/Fire 810 (Biolegend, 1:50), and anti-CD4-cFluorTM YG584 (Cytek, 1:83) antibodies on ice for at least 30 min. The cells were then washed and stained by incubation with streptavidin-PE/Cy5 (Biolegend, 1:3000) on ice for 30 min. The cells were then fixed and permeabilized for intracellular staining with anti-TLR7-PE (Invitrogen) and anti-TLR8-APC (Biolegend) antibodies, with the eBioscience Foxp3/Transcription Factor Staining Buffer Set (Invitrogen), according to the manufacturer’s instructions. The cells were then washed and acquired with a five-laser Cytek Aurora (Cytek) flow cytometer. Antibody clone information is added in a supplemental material (Data file S6).

pDC activation

Freshly purified pDCs were cultured in 96-well plates at a concentration of 5 × 105 cells per mL in the presence of medium alone (RPMI 1640 Medium with GlutaMAX, 10% FBS, 1% MEM NEAA, 1% sodium pyruvate, and 1% penicillin/streptomycin), CL264 (Invivogen, 1 μg/mL), or the SARS-CoV-2 primary strain 220_95 at a multiplicity of infection (MOI) of 1. After 24 hours of culture, the pDC supernatant was collected for cytokine quantification, and the PDCs were collected for diversification assessment by flow cytometry. In some experiments, RNA was purified from the pDCs were analyzed by RNA-seq (see below).

Flow cytometry analysis for human pDCs

For assessments of pDC diversification, cells were stained with Zombie Violet fixable viability dye (Biolegend), BV711 anti-CD123 (Biolegend, clone 6H6), PE anti-CD80 (BD, clone L307.4), and PerCP-efluor 710 anti-PD-L1 (eBioscience, clone MIH1) antibodies. Data were acquired with an LSR Fortessa (BD Biosciences) flow cytometer and analyzed with FlowJo software (Tree Star). Flow cytometry analyses were performed at the flow cytometry core facility of IRSL (Paris, France).

RNA-Sequencing

We collected cells from five individuals in two families: one patient (P8) and two healthy controls (H.II.2, H.II.3) from family H, and one patient (P14) and one healthy control (M.I.1)) from family M. These cells were stimulated with three conditions: non-stimulation, SARS CoV-2, and CpG-c. Total RNA was extracted from pDC cells with RNeasy Micro kits (QIAGEN). RNA-Seq libraries were prepared with the Illumina SMART-Seq® v4 PLUS Kit (TaKaRa) and sequenced on the Illumina NextSeq 4000 platform with single-end 75 bp configuration. The RNA-Seq fastq raw data were inspected with multiQC v1.10 to ensure the high quality of data. The sequencing reads were mapped onto the human reference genome GRCh38 with STAR aligner v2.7, and the mapped reads were then quantified to determine the gene-level read counts with featureCounts V2.0.2 and GENCODE human gene annotation GRCh38.p13. The gene-level read counts were normalized and log2-transformed by DESeq2, to obtain the gene expression profile of all samples for differential expression analysis. The differential gene expression was analyzed by applying TMM normalization and gene-wise generalized linear model regression with edgeR. The genes displaying significant differential expression were selected on the basis of |log2-FoldChange| ≥ 2 and FDR ≤ 0.05. The gene-level read counts of IFN genes were transformed to RPKM (Reads Per Kilobase of transcript, per Million mapped reads) by our own scripts, to compare the IFN gene expression of different samples under different stimulations.

Determination of secreted inflammatory cytokines

We measured the production, by pDCs, of IFN-α2, IL-8, IL-6, and IP-10, by determining the levels of these cytokines in culture supernatants with the BD cytometric bead array (CBA), according to the manufacturer’s protocol, with a limit of detection of 20 pg/mL. Acquisitions were performed on an LSR Fortessa (BD Biosciences) flow cytometer, and cytokine concentrations were determined with FCAP Array Software (BD Biosciences).

References 79

  1. 1.

    J. L. Casanova, H. C. Su; COVID Human Genetic Effort, A Global Effort to Define the Human Genetics of Protective Immunity to SARS-CoV-2 Infection. Cell 181, 1194–1199 (2020 ).

    Not in our library10.1016/j.cell.2020.05.016

  2. 2.

    Q. Zhang, P. Bastard, A. Bolze, E. Jouanguy, S. Y. Zhang, A. Cobat, L. D. Notarangelo, H. C. Su, L. Abel, J. L. Casanova; COVID Human Genetic Effort, Life-Threatening COVID-19: Defective Interferons Unleash Excessive Inflammation. Med (N Y) 1, 14–20 (2020 ).

    Not in our library10.1016/j.medj.2020.12.001

  3. 3.

    M. O’Driscoll, G. Ribeiro Dos Santos, L. Wang, D. A. T. Cummings, A. S. Azman, J. Paireau, A. Fontanet, S. Cauchemez, H. Salje, Age-specific mortality and immunity patterns of SARS-CoV-2. Nature 590, 140–145 (2021 ).

    Not in our library10.1038/s41586-020-2918-0

  4. 4.

    E. P. Scully, J. Haverfield, R. L. Ursin, C. Tannenbaum, S. L. Klein, Considering how biological sex impacts immune responses and COVID-19 outcomes. Nat. Rev. Immunol. 20, 442–447 (2020 ).

    Not in our library10.1038/s41577-020-0348-8

  5. 5.

    M. J. Ciancanelli, S. X. Huang, P. Luthra, H. Garner, Y. Itan, S. Volpi, F. G. Lafaille, C. Trouillet, M. Schmolke, R. A. Albrecht, E. Israelsson, H. K. Lim, M. Casadio, T. Hermesh, L. Lorenzo, L. W. Leung, V. Pedergnana, B. Boisson, S. Okada, C. Picard, B. Ringuier, F. Troussier, D. Chaussabel, L. Abel, I. Pellier, L. D. Notarangelo, A. García-Sastre, C. F. Basler, F. Geissmann, S. Y. Zhang, H. W. Snoeck, J. L. Casanova, Infectious disease. Life-threatening influenza and impaired interferon amplification in human IRF7 deficiency. Science 348, 448–453 (2015 ).

    Not in our library10.1126/science.aaa1578

  6. 6.

    N. Hernandez, I. Melki, H. Jing, T. Habib, S. S. Y. Huang, J. Danielson, T. Kula, S. Drutman, S. Belkaya, V. Rattina, L. Lorenzo-Diaz, A. Boulai, Y. Rose, N. Kitabayashi, M. P. Rodero, C. Dumaine, S. Blanche, M. N. Lebras, M. C. Leung, L. S. Mathew, B. Boisson, S. Y. Zhang, S. Boisson-Dupuis, S. Giliani, D. Chaussabel, L. D. Notarangelo, S. J. Elledge, M. J. Ciancanelli, L. Abel, Q. Zhang, N. Marr, Y. J. Crow, H. C. Su, J. L. Casanova, Life-threatening influenza pneumonitis in a child with inherited IRF9 deficiency. J. Exp. Med. 215, 2567–2585 (2018 ).

    Not in our library10.1084/jem.20180628

  7. 7.

    H. K. Lim, S. X. L. Huang, J. Chen, G. Kerner, O. Gilliaux, P. Bastard, K. Dobbs, N. Hernandez, N. Goudin, M. L. Hasek, E. J. García Reino, F. G. Lafaille, L. Lorenzo, P. Luthra, T. Kochetkov, B. Bigio, S. Boucherit, F. Rozenberg, C. Vedrinne, M. D. Keller, Y. Itan, A. García-Sastre, M. Celard, J. S. Orange, M. J. Ciancanelli, I. Meyts, Q. Zhang, L. Abel, L. D. Notarangelo, H. W. Snoeck, J. L. Casanova, S. Y. Zhang, Severe influenza pneumonitis in children with inherited TLR3 deficiency. J. Exp. Med. 216, 2038–2056 (2019 ).

    Not in our library10.1084/jem.20181621

  8. 8.

    Q. Zhang, P. Bastard, Z. Liu, J. Le Pen, M. Moncada-Velez, J. Chen, M. Ogishi, I. K. D. Sabli, S. Hodeib, C. Korol, J. Rosain, K. Bilguvar, J. Ye, A. Bolze, B. Bigio, R. Yang, A. A. Arias, Q. Zhou, Y. Zhang, F. Onodi, S. Korniotis, L. Karpf, Q. Philippot, M. Chbihi, L. Bonnet-Madin, K. Dorgham, N. Smith, W. M. Schneider, B. S. Razooky, H. H. Hoffmann, E. Michailidis, L. Moens, J. E. Han, L. Lorenzo, L. Bizien, P. Meade, A. L. Neehus, A. C. Ugurbil, A. Corneau, G. Kerner, P. Zhang, F. Rapaport, Y. Seeleuthner, J. Manry, C. Masson, Y. Schmitt, A. Schlüter, T. Le Voyer, T. Khan, J. Li, J. Fellay, L. Roussel, M. Shahrooei, M. F. Alosaimi, D. Mansouri, H. Al-Saud, F. Al-Mulla, F. Almourfi, S. Z. Al-Muhsen, F. Alsohime, S. Al Turki, R. Hasanato, D. van de Beek, A. Biondi, L. R. Bettini, M. D’Angio’, P. Bonfanti, L. Imberti, A. Sottini, S. Paghera, E. Quiros-Roldan, C. Rossi, A. J. Oler, M. F. Tompkins, C. Alba, I. Vandernoot, J. C. Goffard, G. Smits, I. Migeotte, F. Haerynck, P. Soler-Palacin, A. Martin-Nalda, R. Colobran, P. E. Morange, S. Keles, F. Çölkesen, T. Ozcelik, K. K. Yasar, S. Senoglu, S. N. Karabela, C. Rodríguez-Gallego, G. Novelli, S. Hraiech, Y. Tandjaoui-Lambiotte, X. Duval, C. Laouénan, A. L. Snow, C. L. Dalgard, J. D. Milner, D. C. Vinh, T. H. Mogensen, N. Marr, A. N. Spaan, B. Boisson, S. Boisson-Dupuis, J. Bustamante, A. Puel, M. J. Ciancanelli, I. Meyts, T. Maniatis, V. Soumelis, A. Amara, M. Nussenzweig, A. García-Sastre, F. Krammer, A. Pujol, D. Duffy, R. P. Lifton, S. Y. Zhang, G. Gorochov, V. Béziat, E. Jouanguy, V. Sancho-Shimizu, C. M. Rice, L. Abel, L. D. Notarangelo, A. Cobat, H. C. Su, J. L. Casanova; COVID-STORM Clinicians; COVID Clinicians; Imagine COVID Group; French COVID Cohort Study Group; CoV-Contact Cohort; Amsterdam UMC Covid-19 Biobank; COVID Human Genetic Effort; NIAID-USUHS/TAGC COVID Immunity Group, Inborn errors of type I IFN immunity in patients with life-threatening COVID-19. Science 370, eabd4570 (2020 ).

    Not in our library10.1126/science.abd4570

  9. 9.

    P. Bastard, L. B. Rosen, Q. Zhang, E. Michailidis, H. H. Hoffmann, Y. Zhang, K. Dorgham, Q. Philippot, J. Rosain, V. Béziat, J. Manry, E. Shaw, L. Haljasmägi, P. Peterson, L. Lorenzo, L. Bizien, S. Trouillet-Assant, K. Dobbs, A. A. de Jesus, A. Belot, A. Kallaste, E. Catherinot, Y. Tandjaoui-Lambiotte, J. Le Pen, G. Kerner, B. Bigio, Y. Seeleuthner, R. Yang, A. Bolze, A. N. Spaan, O. M. Delmonte, M. S. Abers, A. Aiuti, G. Casari, V. Lampasona, L. Piemonti, F. Ciceri, K. Bilguvar, R. P. Lifton, M. Vasse, D. M. Smadja, M. Migaud, J. Hadjadj, B. Terrier, D. Duffy, L. Quintana-Murci, D. van de Beek, L. Roussel, D. C. Vinh, S. G. Tangye, F. Haerynck, D. Dalmau, J. Martinez-Picado, P. Brodin, M. C. Nussenzweig, S. Boisson-Dupuis, C. Rodríguez-Gallego, G. Vogt, T. H. Mogensen, A. J. Oler, J. Gu, P. D. Burbelo, J. I. Cohen, A. Biondi, L. R. Bettini, M. D’Angio, P. Bonfanti, P. Rossignol, J. Mayaux, F. Rieux-Laucat, E. S. Husebye, F. Fusco, M. V. Ursini, L. Imberti, A. Sottini, S. Paghera, E. Quiros-Roldan, C. Rossi, R. Castagnoli, D. Montagna, A. Licari, G. L. Marseglia, X. Duval, J. Ghosn, J. S. Tsang, R. Goldbach-Mansky, K. Kisand, M. S. Lionakis, A. Puel, S. Y. Zhang, S. M. Holland, G. Gorochov, E. Jouanguy, C. M. Rice, A. Cobat, L. D. Notarangelo, L. Abel, H. C. Su, J. L. Casanova; HGID Lab; NIAID-USUHS Immune Response to COVID Group; COVID Clinicians; COVID-STORM Clinicians; Imagine COVID Group; French COVID Cohort Study Group; Milieu Intérieur Consortium; CoV-Contact Cohort; Amsterdam UMC Covid-19 Biobank; COVID Human Genetic Effort, Autoantibodies against type I IFNs in patients with life-threatening COVID-19. Science 370, eabd4585 (2020 ).

    Not in our library10.1126/science.abd4585

  10. 10.

    E. Y. Wang, T. Mao, J. Klein, Y. Dai, J. D. Huck, J. R. Jaycox, F. Liu, T. Zhou, B. Israelow, P. Wong, A. Coppi, C. Lucas, J. Silva, J. E. Oh, E. Song, E. S. Perotti, N. S. Zheng, S. Fischer, M. Campbell, J. B. Fournier, A. L. Wyllie, C. B. F. Vogels, I. M. Ott, C. C. Kalinich, M. E. Petrone, A. E. Watkins, C. Dela Cruz, S. F. Farhadian, W. L. Schulz, S. Ma, N. D. Grubaugh, A. I. Ko, A. Iwasaki, A. M. Ring; Yale IMPACT Team, Diverse functional autoantibodies in patients with COVID-19. Nature 595, 283–288 (2021 ).

    Not in our library10.1038/s41586-021-03631-y

  11. 11.

    R. Koning, P. Bastard, J. L. Casanova, M. C. Brouwer, D. van de Beek; with the Amsterdam U.M.C. COVID-19 Biobank Investigators, Autoantibodies against type I interferons are associated with multi-organ failure in COVID-19 patients. Intensive Care Med. 47, 704–706 (2021 ).

    Not in our library10.1007/s00134-021-06392-4

  12. 12.

    J. Troya, P. Bastard, L. Planas-Serra, P. Ryan, M. Ruiz, M. de Carranza, J. Torres, A. Martínez, L. Abel, J. L. Casanova, A. Pujol, Neutralizing Autoantibodies to Type I IFNs in >10% of Patients with Severe COVID-19 Pneumonia Hospitalized in Madrid, Spain. J. Clin. Immunol. 41, 914–922 (2021 ).

    Not in our library10.1007/s10875-021-01036-0

  13. 13.

    G. David, M. Mehdi, B. Paul, P. Magali, S. Kahina, F. Nicole, P. Rémi, L. Christine, W. Thierry, C. Jean-Laurent, B. Alexandre, R. Jean-Christophe, T.-A. Sophie, Antibodies against type-I Interferon: detection and association with severe clinical outcome in COVID-19 patients. medRxiv, 2021.2004.2002.21253262 (2021 ).

    Not in our library

  14. 14.

    M. G. P. van der Wijst, S. E. Vazquez, G. C. Hartoularos, P. Bastard, T. Grant, R. Bueno, D. S. Lee, J. R. Greenland, Y. Sun, R. Perez, A. Ogorodnikov, A. Ward, S. A. Mann, K. L. Lynch, C. Yun, D. V. Havlir, G. Chamie, C. Marquez, B. Greenhouse, M. S. Lionakis, P. J. Norris, L. J. Dumont, K. Kelly, P. Zhang, Q. Zhang, A. Gervais, T. L. Voyer, A. Whatley, Y. Si, A. Byrne, A. J. Combes, A. A. Rao, Y. S. Song, Longitudinal single-cell epitope and RNA-sequencing reveals the immunological impact of type 1 interferon autoantibodies in critical COVID-19. bioRxiv: the preprint server for biology, (2021).

    Not in our library

  15. 15.

    S. E. Vazquez, P. Bastard, K. Kelly, A. Gervais, P. J. Norris, L. J. Dumont, J. L. Casanova, M. S. Anderson, J. L. DeRisi, Neutralizing Autoantibodies to Type I Interferons in COVID-19 Convalescent Donor Plasma. J. Clin. Immunol. 41, 1169–1171 (2021 ).

    Not in our library10.1007/s10875-021-01060-0

  16. 16.

    P. Bastard, E. Orlova, L. Sozaeva, R. Lévy, A. James, M. M. Schmitt, S. Ochoa, M. Kareva, Y. Rodina, A. Gervais, T. Le Voyer, J. Rosain, Q. Philippot, A. L. Neehus, E. Shaw, M. Migaud, L. Bizien, O. Ekwall, S. Berg, G. Beccuti, L. Ghizzoni, G. Thiriez, A. Pavot, C. Goujard, M. L. Frémond, E. Carter, A. Rothenbuhler, A. Linglart, B. Mignot, A. Comte, N. Cheikh, O. Hermine, L. Breivik, E. S. Husebye, S. Humbert, P. Rohrlich, A. Coaquette, F. Vuoto, K. Faure, N. Mahlaoui, P. Kotnik, T. Battelino, K. Trebušak Podkrajšek, K. Kisand, E. M. N. Ferré, T. DiMaggio, L. B. Rosen, P. D. Burbelo, M. McIntyre, N. Y. Kann, A. Shcherbina, M. Pavlova, A. Kolodkina, S. M. Holland, S. Y. Zhang, Y. J. Crow, L. D. Notarangelo, H. C. Su, L. Abel, M. S. Anderson, E. Jouanguy, B. Neven, A. Puel, J. L. Casanova, M. S. Lionakis, Preexisting autoantibodies to type I IFNs underlie critical COVID-19 pneumonia in patients with APS-1. J. Exp. Med. 218, e20210554 (2021 ).

    Not in our library10.1084/jem.20210554

  17. 17.

    P. Bastard, E. Michailidis, H. H. Hoffmann, M. Chbihi, T. Le Voyer, J. Rosain, Q. Philippot, Y. Seeleuthner, A. Gervais, M. Materna, P. M. N. de Oliveira, M. L. S. Maia, A. P. Dinis Ano Bom, T. Azamor, D. Araújo da Conceição, E. Goudouris, A. Homma, G. Slesak, J. Schäfer, B. Pulendran, J. D. Miller, R. Huits, R. Yang, L. B. Rosen, L. Bizien, L. Lorenzo, M. Chrabieh, L. V. Erazo, F. Rozenberg, M. M. Jeljeli, V. Béziat, S. M. Holland, A. Cobat, L. D. Notarangelo, H. C. Su, R. Ahmed, A. Puel, S. Y. Zhang, L. Abel, S. J. Seligman, Q. Zhang, M. R. MacDonald, E. Jouanguy, C. M. Rice, J. L. Casanova, Auto-antibodies to type I IFNs can underlie adverse reactions to yellow fever live attenuated vaccine. J. Exp. Med. 218, e20202486 (2021 ).

    Not in our library10.1084/jem.20202486

  18. 18.

    D. Firth, Bias reduction of maximum likelihood estimates. Biometrika 80, 27–38 (1993 ).

    Not in our library10.1093/biomet/80.1.27

  19. 19.

    H. Hemmi, T. Kaisho, O. Takeuchi, S. Sato, H. Sanjo, K. Hoshino, T. Horiuchi, H. Tomizawa, K. Takeda, S. Akira, Small anti-viral compounds activate immune cells via the TLR7 MyD88-dependent signaling pathway. Nat. Immunol. 3, 196–200 (2002 ).

    Not in our library10.1038/ni758

  20. 20.

    S. S. Diebold, T. Kaisho, H. Hemmi, S. Akira, C. Reis e Sousa, Innate antiviral responses by means of TLR7-mediated recognition of single-stranded RNA. Science 303, 1529–1531 (2004 ).

    Not in our library10.1126/science.1093616

  21. 21.

    F. Heil, H. Hemmi, H. Hochrein, F. Ampenberger, C. Kirschning, S. Akira, G. Lipford, H. Wagner, S. Bauer, Species-specific recognition of single-stranded RNA via toll-like receptor 7 and 8. Science 303, 1526–1529 (2004 ).

    Not in our library10.1126/science.1093620

  22. 22.

    J. M. Lund, L. Alexopoulou, A. Sato, M. Karow, N. C. Adams, N. W. Gale, A. Iwasaki, R. A. Flavell, Recognition of single-stranded RNA viruses by Toll-like receptor 7. Proc. Natl. Acad. Sci. U.S.A. 101, 5598–5603 (2004 ).

    Not in our library10.1073/pnas.0400937101

  23. 23.

    B. Beutler, Inferences, questions and possibilities in Toll-like receptor signalling. Nature 430, 257–263 (2004 ).

    Not in our library10.1038/nature02761

  24. 24.

    M. Colonna, G. Trinchieri, Y. J. Liu, Plasmacytoid dendritic cells in immunity. Nat. Immunol. 5, 1219–1226 (2004 ).

    Not in our library10.1038/ni1141

  25. 25.

    M. Gilliet, W. Cao, Y. J. Liu, Plasmacytoid dendritic cells: Sensing nucleic acids in viral infection and autoimmune diseases. Nat. Rev. Immunol. 8, 594–606 (2008 ).

    Not in our library10.1038/nri2358

  26. 26.

    B. Reizis, Plasmacytoid Dendritic Cells: Development, Regulation, and Function. Immunity 50, 37–50 (2019 ).

    Not in our library10.1016/j.immuni.2018.12.027

  27. 27.

    A. T. Bender, E. Tzvetkov, A. Pereira, Y. Wu, S. Kasar, M. M. Przetak, J. Vlach, T. B. Niewold, M. A. Jensen, S. L. Okitsu, TLR7 and TLR8 Differentially Activate the IRF and NF-κB Pathways in Specific Cell Types to Promote Inflammation. Immunohorizons 4, 93–107 (2020 ).

    Not in our library10.4049/immunohorizons.2000002

  28. 28.

    K. Maeda, S. Akira, TLR7 Structure: Cut in Z-Loop. Immunity 45, 705–707 (2016 ).

    Not in our library10.1016/j.immuni.2016.10.003

  29. 29.

    J. Aluri, A. Bach, S. Kaviany, L. Chiquetto Paracatu, M. Kitcharoensakkul, M. A. Walkiewicz, C. D. Putnam, M. Shinawi, N. Saucier, E. M. Rizzi, M. T. Harmon, M. P. Keppel, M. Ritter, M. Similuk, E. Kulm, M. Joyce, A. A. de Jesus, R. Goldbach-Mansky, Y. S. Lee, M. Cella, P. L. Kendall, M. C. Dinauer, J. J. Bednarski, C. Bemrich-Stolz, S. W. Canna, S. M. Abraham, M. M. Demczko, J. Powell, S. M. Jones, A. M. Scurlock, S. S. De Ravin, J. J. Bleesing, J. A. Connelly, V. K. Rao, L. G. Schuettpelz, M. A. Cooper, Immunodeficiency and bone marrow failure with mosaic and germline TLR8 gain of function. Blood 137, 2450–2462 (2021 ).

    Not in our library10.1182/blood.2020009620

  30. 30.

    C. Uggenti, A. Lepelley, Y. J. Crow, Self-Awareness: Nucleic Acid-Driven Inflammation and the Type I Interferonopathies. Annu. Rev. Immunol. 37, 247–267 (2019 ).

    Not in our library10.1146/annurev-immunol-042718-041257

  31. 31.

    B. Boisson, J. L. Casanova, TLR8 gain of function: A tall surprise. Blood 137, 2420–2422 (2021 ).

    Not in our library10.1182/blood.2020010463

  32. 32.

    M. Uhlen, M. J. Karlsson, W. Zhong, A. Tebani, C. Pou, J. Mikes, T. Lakshmikanth, B. Forsström, F. Edfors, J. Odeberg, A. Mardinoglu, C. Zhang, K. von Feilitzen, J. Mulder, E. Sjöstedt, A. Hober, P. Oksvold, M. Zwahlen, F. Ponten, C. Lindskog, Å. Sivertsson, L. Fagerberg, P. Brodin, A genome-wide transcriptomic analysis of protein-coding genes in human blood cells. Science 366, eaax9198 (2019 ).

    Not in our library10.1126/science.aax9198

  33. 33.
  34. 34.

    C. I. van der Made, A. Simons, J. Schuurs-Hoeijmakers, G. van den Heuvel, T. Mantere, S. Kersten, R. C. van Deuren, M. Steehouwer, S. V. van Reijmersdal, M. Jaeger, T. Hofste, G. Astuti, J. Corominas Galbany, V. van der Schoot, H. van der Hoeven, W. Hagmolen Of Ten Have, E. Klijn, C. van den Meer, J. Fiddelaers, Q. de Mast, C. P. Bleeker-Rovers, L. A. B. Joosten, H. G. Yntema, C. Gilissen, M. Nelen, J. W. M. van der Meer, H. G. Brunner, M. G. Netea, F. L. van de Veerdonk, A. Hoischen, Presence of Genetic Variants Among Young Men With Severe COVID-19. JAMA 324, 663–673 (2020 ).

    Not in our library10.1001/jama.2020.13719

  35. 35.

    A. Belkadi, V. Pedergnana, A. Cobat, Y. Itan, Q. B. Vincent, A. Abhyankar, L. Shang, J. El Baghdadi, A. Bousfiha, A. Alcais, B. Boisson, J. L. Casanova, L. Abel; Exome/Array Consortium, Whole-exome sequencing to analyze population structure, parental inbreeding, and familial linkage. Proc. Natl. Acad. Sci. U.S.A. 113, 6713–6718 (2016 ).

    Not in our library10.1073/pnas.1606460113

  36. 36.

    M. Shodell, F. P. Siegal, Circulating, interferon-producing plasmacytoid dendritic cells decline during human ageing. Scand. J. Immunol. 56, 518–521 (2002 ).

    Not in our library10.1046/j.1365-3083.2002.01148.x

  37. 37.

    Y. Jing, E. Shaheen, R. R. Drake, N. Chen, S. Gravenstein, Y. Deng, Aging is associated with a numerical and functional decline in plasmacytoid dendritic cells, whereas myeloid dendritic cells are relatively unaltered in human peripheral blood. Hum. Immunol. 70, 777–784 (2009 ).

    Not in our library10.1016/j.humimm.2009.07.005

  38. 38.

    M. V. Splunter, O. Perdijk, H. Fick-Brinkhof, E. G. Floris-Vollenbroek, B. Meijer, S. Brugman, H. F. J. Savelkoul, E. van Hoffen, R. J. Joost van Neerven, Plasmacytoid dendritic cell and myeloid dendritic cell function in ageing: A comparison between elderly and young adult women. PLOS ONE 14, e0225825 (2019 ).

    Not in our library10.1371/journal.pone.0225825

  39. 39.

    N. V. Giltiay, C. P. Chappell, X. Sun, N. Kolhatkar, T. H. Teal, A. E. Wiedeman, J. Kim, L. Tanaka, M. B. Buechler, J. A. Hamerman, T. Imanishi-Kari, E. A. Clark, K. B. Elkon, Overexpression of TLR7 promotes cell-intrinsic expansion and autoantibody production by transitional T1 B cells. J. Exp. Med. 210, 2773–2789 (2013 ).

    Not in our library10.1084/jem.20122798

  40. 40.

    J. Lonsdale, J. Thomas, M. Salvatore, R. Phillips, E. Lo, S. Shad, R. Hasz, G. Walters, F. Garcia, N. Young, B. Foster, M. Moser, E. Karasik, B. Gillard, K. Ramsey, S. Sullivan, J. Bridge, H. Magazine, J. Syron, J. Fleming, L. Siminoff, H. Traino, M. Mosavel, L. Barker, S. Jewell, D. Rohrer, D. Maxim, D. Filkins, P. Harbach, E. Cortadillo, B. Berghuis, L. Turner, E. Hudson, K. Feenstra, L. Sobin, J. Robb, P. Branton, G. Korzeniewski, C. Shive, D. Tabor, L. Qi, K. Groch, S. Nampally, S. Buia, A. Zimmerman, A. Smith, R. Burges, K. Robinson, K. Valentino, D. Bradbury, M. Cosentino, N. Diaz-Mayoral, M. Kennedy, T. Engel, P. Williams, K. Erickson, K. Ardlie, W. Winckler, G. Getz, D. DeLuca, D. MacArthur, M. Kellis, A. Thomson, T. Young, E. Gelfand, M. Donovan, Y. Meng, G. Grant, D. Mash, Y. Marcus, M. Basile, J. Liu, J. Zhu, Z. Tu, N. J. Cox, D. L. Nicolae, E. R. Gamazon, H. K. Im, A. Konkashbaev, J. Pritchard, M. Stevens, T. Flutre, X. Wen, E. T. Dermitzakis, T. Lappalainen, R. Guigo, J. Monlong, M. Sammeth, D. Koller, A. Battle, S. Mostafavi, M. McCarthy, M. Rivas, J. Maller, I. Rusyn, A. Nobel, F. Wright, A. Shabalin, M. Feolo, N. Sharopova, A. Sturcke, J. Paschal, J. M. Anderson, E. L. Wilder, L. K. Derr, E. D. Green, J. P. Struewing, G. Temple, S. Volpi, J. T. Boyer, E. J. Thomson, M. S. Guyer, C. Ng, A. Abdallah, D. Colantuoni, T. R. Insel, S. E. Koester, A. R. Little, P. K. Bender, T. Lehner, Y. Yao, C. C. Compton, J. B. Vaught, S. Sawyer, N. C. Lockhart, J. Demchok, H. F. Moore; GTEx Consortium, The Genotype-Tissue Expression (GTEx) project. Nat. Genet. 45, 580–585 (2013 ).

    Not in our library10.1038/ng.2653

  41. 41.

    K. J. Travaglini, A. N. Nabhan, L. Penland, R. Sinha, A. Gillich, R. V. Sit, S. Chang, S. D. Conley, Y. Mori, J. Seita, G. J. Berry, J. B. Shrager, R. J. Metzger, C. S. Kuo, N. Neff, I. L. Weissman, S. R. Quake, M. A. Krasnow, A molecular cell atlas of the human lung from single-cell RNA sequencing. Nature 587, 619–625 (2020 ).

    Not in our library10.1038/s41586-020-2922-4

  42. 42.

    M. Cella, D. Jarrossay, F. Facchetti, O. Alebardi, H. Nakajima, A. Lanzavecchia, M. Colonna, Plasmacytoid monocytes migrate to inflamed lymph nodes and produce large amounts of type I interferon. Nat. Med. 5, 919–923 (1999 ).

    Not in our library10.1038/11360

  43. 43.

    F. P. Siegal, N. Kadowaki, M. Shodell, P. A. Fitzgerald-Bocarsly, K. Shah, S. Ho, S. Antonenko, Y. J. Liu, The nature of the principal type 1 interferon-producing cells in human blood. Science 284, 1835–1837 (1999 ).

    Not in our library10.1126/science.284.5421.1835

  44. 44.

    K. Honda, T. Taniguchi, IRFs: Master regulators of signalling by Toll-like receptors and cytosolic pattern-recognition receptors. Nat. Rev. Immunol. 6, 644–658 (2006 ).

    Not in our library10.1038/nri1900

  45. 45.

    F. Onodi, L. Bonnet-Madin, L. Meertens, L. Karpf, J. Poirot, S. Y. Zhang, C. Picard, A. Puel, E. Jouanguy, Q. Zhang, J. Le Goff, J. M. Molina, C. Delaugerre, J. L. Casanova, A. Amara, V. Soumelis, SARS-CoV-2 induces human plasmacytoid predendritic cell diversification via UNC93B and IRAK4. J. Exp. Med. 218, e20201387 (2021 ).

    Not in our library10.1084/jem.20201387

  46. 46.

    L. Cervantes-Barragan, A. Vanderheiden, C. J. Royer, M. E. Davis-Gardner, P. Ralfs, T. Chirkova, L. J. Anderson, A. Grakoui, M. S. Suthar, Plasmacytoid dendritic cells produce type I interferon and reduce viral replication in airway epithelial cells after SARS-CoV-2 infection. bioRxiv: the preprint server for biology, 2021.2005.2012.443948 (2021).

    Not in our library

  47. 47.

    S. G. Alculumbre, V. Saint-André, J. Di Domizio, P. Vargas, P. Sirven, P. Bost, M. Maurin, P. Maiuri, M. Wery, M. S. Roman, L. Savey, M. Touzot, B. Terrier, D. Saadoun, C. Conrad, M. Gilliet, A. Morillon, V. Soumelis, Diversification of human plasmacytoid predendritic cells in response to a single stimulus. Nat. Immunol. 19, 63–75 (2018 ).

    Not in our library10.1038/s41590-017-0012-z

  48. 48.

    J. A. Kosmicki, J. E. Horowitz, N. Banerjee, R. Lanche, A. Marcketta, E. Maxwell, X. Bai, D. Sun, J. D. Backman, D. Sharma, F. S. P. Kury, H. M. Kang, C. O’Dushlaine, A. Yadav, A. J. Mansfield, A. H. Li, K. Watanabe, L. Gurski, S. E. McCarthy, A. E. Locke, S. Khalid, S. O’Keeffe, J. Mbatchou, O. Chazara, Y. Huang, E. Kvikstad, A. O’Neill, P. Nioi, M. M. Parker, S. Petrovski, H. Runz, J. D. Szustakowski, Q. Wang, E. Wong, A. Cordova-Palomera, E. N. Smith, S. Szalma, X. Zheng, S. Esmaeeli, J. W. Davis, Y.-P. Lai, X. Chen, A. E. Justice, J. B. Leader, T. Mirshahi, D. J. Carey, A. Verma, G. Sirugo, M. D. Ritchie, D. J. Rader, G. Povysil, D. B. Goldstein, K. Kiryluk, E. Pairo-Castineira, K. Rawlik, D. Pasko, S. Walker, A. Meynert, A. Kousathanas, L. Moutsianas, A. Tenesa, M. Caulfield, R. Scott, J. F. Wilson, J. K. Baillie, G. Butler-Laporte, T. Nakanishi, M. Lathrop, J. B. Richards, M. Jones, S. Balasubramanian, W. Salerno, A. R. Shuldiner, J. Marchini, J. D. Overton, L. Habegger, M. N. Cantor, J. G. Reid, A. Baras, G. R. Abecasis, M. A. R. Ferreira; Regeneron Genetics Center; UKB Exome Sequencing Consortium, Pan-ancestry exome-wide association analyses of COVID-19 outcomes in 586,157 individuals. Am. J. Hum. Genet. 108, 1350–1355 (2021 ).

    Not in our library10.1016/j.ajhg.2021.05.017

  49. 49.

    K. Yang, A. Puel, S. Zhang, C. Eidenschenk, C. L. Ku, A. Casrouge, C. Picard, H. von Bernuth, B. Senechal, S. Plancoulaine, S. Al-Hajjar, A. Al-Ghonaium, L. Maródi, D. Davidson, D. Speert, C. Roifman, B. Z. Garty, A. Ozinsky, F. J. Barrat, R. L. Coffman, R. L. Miller, X. Li, P. Lebon, C. Rodriguez-Gallego, H. Chapel, F. Geissmann, E. Jouanguy, J. L. Casanova, Human TLR-7-, -8-, and -9-mediated induction of IFN-alpha/beta and -lambda Is IRAK-4 dependent and redundant for protective immunity to viruses. Immunity 23, 465–478 (2005 ).

    Not in our library10.1016/j.immuni.2005.09.016

  50. 50.

    C. L. Ku, H. von Bernuth, C. Picard, S. Y. Zhang, H. H. Chang, K. Yang, M. Chrabieh, A. C. Issekutz, C. K. Cunningham, J. Gallin, S. M. Holland, C. Roifman, S. Ehl, J. Smart, M. Tang, F. J. Barrat, O. Levy, D. McDonald, N. K. Day-Good, R. Miller, H. Takada, T. Hara, S. Al-Hajjar, A. Al-Ghonaium, D. Speert, D. Sanlaville, X. Li, F. Geissmann, E. Vivier, L. Maródi, B. Z. Garty, H. Chapel, C. Rodriguez-Gallego, X. Bossuyt, L. Abel, A. Puel, J. L. Casanova, Selective predisposition to bacterial infections in IRAK-4-deficient children: IRAK-4-dependent TLRs are otherwise redundant in protective immunity. J. Exp. Med. 204, 2407–2422 (2007 ).

    Not in our library10.1084/jem.20070628

  51. 51.

    J. L. Casanova, L. Abel, L. Quintana-Murci, Human TLRs and IL-1Rs in host defense: Natural insights from evolutionary, epidemiological, and clinical genetics. Annu. Rev. Immunol. 29, 447–491 (2011 ).

    Not in our library10.1146/annurev-immunol-030409-101335

  52. 52.

    B. Boisson, The genetic basis of pneumococcal and staphylococcal infections: Inborn errors of human TLR and IL-1R immunity. Hum. Genet. 139, 981–991 (2020 ).

    Not in our library10.1007/s00439-020-02111-z

  53. 53.
  54. 54.

    H. von Bernuth, C. Picard, Z. Jin, R. Pankla, H. Xiao, C. L. Ku, M. Chrabieh, I. B. Mustapha, P. Ghandil, Y. Camcioglu, J. Vasconcelos, N. Sirvent, M. Guedes, A. B. Vitor, M. J. Herrero-Mata, J. I. Aróstegui, C. Rodrigo, L. Alsina, E. Ruiz-Ortiz, M. Juan, C. Fortuny, J. Yagüe, J. Antón, M. Pascal, H. H. Chang, L. Janniere, Y. Rose, B. Z. Garty, H. Chapel, A. Issekutz, L. Maródi, C. Rodriguez-Gallego, J. Banchereau, L. Abel, X. Li, D. Chaussabel, A. Puel, J. L. Casanova, Pyogenic bacterial infections in humans with MyD88 deficiency. Science 321, 691–696 (2008 ).

    Not in our library10.1126/science.1158298

  55. 55.

    C. Picard, A. Puel, M. Bonnet, C. L. Ku, J. Bustamante, K. Yang, C. Soudais, S. Dupuis, J. Feinberg, C. Fieschi, C. Elbim, R. Hitchcock, D. Lammas, G. Davies, A. Al-Ghonaium, H. Al-Rayes, S. Al-Jumaah, S. Al-Hajjar, I. Z. Al-Mohsen, H. H. Frayha, R. Rucker, T. R. Hawn, A. Aderem, H. Tufenkeji, S. Haraguchi, N. K. Day, R. A. Good, M. A. Gougerot-Pocidalo, A. Ozinsky, J. L. Casanova, Pyogenic bacterial infections in humans with IRAK-4 deficiency. Science 299, 2076–2079 (2003 ).

    Not in our library10.1126/science.1081902

  56. 56.

    A. Casrouge, S. Y. Zhang, C. Eidenschenk, E. Jouanguy, A. Puel, K. Yang, A. Alcais, C. Picard, N. Mahfoufi, N. Nicolas, L. Lorenzo, S. Plancoulaine, B. Sénéchal, F. Geissmann, K. Tabeta, K. Hoebe, X. Du, R. L. Miller, B. Héron, C. Mignot, T. B. de Villemeur, P. Lebon, O. Dulac, F. Rozenberg, B. Beutler, M. Tardieu, L. Abel, J. L. Casanova, Herpes simplex virus encephalitis in human UNC-93B deficiency. Science 314, 308–312 (2006 ).

    Not in our library10.1126/science.1128346

  57. 57.

    Y. J. Liu, Dendritic cell subsets and lineages, and their functions in innate and adaptive immunity. Cell 106, 259–262 (2001 ).

    Not in our library10.1016/s0092-8674(01)00456-1

  58. 58.

    M. Swiecki, M. Colonna, Unraveling the functions of plasmacytoid dendritic cells during viral infections, autoimmunity, and tolerance. Immunol. Rev. 234, 142–162 (2010 ).

    Not in our library10.1111/j.0105-2896.2009.00881.x

  59. 59.

    F. J. Barrat, L. Su, A pathogenic role of plasmacytoid dendritic cells in autoimmunity and chronic viral infection. J. Exp. Med. 216, 1974–1985 (2019 ).

    Not in our library10.1084/jem.20181359

  60. 60.

    I. Sologuren, M. T. Martínez-Saavedra, J. Solé-Violán, E. de Borges de Oliveira Jr., E. Betancor, I. Casas, C. Oleaga-Quintas, M. Martínez-Gallo, S. Y. Zhang, J. Pestano, R. Colobran, E. Herrera-Ramos, C. Pérez, M. López-Rodríguez, J. J. Ruiz-Hernández, N. Franco, J. M. Ferrer, C. Bilbao, M. Andújar-Sánchez, M. Álvarez Fernández, M. J. Ciancanelli, F. Rodríguez de Castro, J. L. Casanova, J. Bustamante, C. Rodríguez-Gallego, Lethal Influenza in Two Related Adults with Inherited GATA2 Deficiency. J. Clin. Immunol. 38, 513–526 (2018 ).

    Not in our library10.1007/s10875-018-0512-0

  61. 61.

    D. C. Vinh, S. Y. Patel, G. Uzel, V. L. Anderson, A. F. Freeman, K. N. Olivier, C. Spalding, S. Hughes, S. Pittaluga, M. Raffeld, L. R. Sorbara, H. Z. Elloumi, D. B. Kuhns, M. L. Turner, E. W. Cowen, D. Fink, D. Long-Priel, A. P. Hsu, L. Ding, M. L. Paulson, A. R. Whitney, E. P. Sampaio, D. M. Frucht, F. R. DeLeo, S. M. Holland, Autosomal dominant and sporadic monocytopenia with susceptibility to mycobacteria, fungi, papillomaviruses, and myelodysplasia. Blood 115, 1519–1529 (2010 ).

    Not in our library10.1182/blood-2009-03-208629

  62. 62.

    R. E. Dickinson, H. Griffin, V. Bigley, L. N. Reynard, R. Hussain, M. Haniffa, J. H. Lakey, T. Rahman, X. N. Wang, N. McGovern, S. Pagan, S. Cookson, D. McDonald, I. Chua, J. Wallis, A. Cant, M. Wright, B. Keavney, P. F. Chinnery, J. Loughlin, S. Hambleton, M. Santibanez-Koref, M. Collin, Exome sequencing identifies GATA-2 mutation as the cause of dendritic cell, monocyte, B and NK lymphoid deficiency. Blood 118, 2656–2658 (2011 ).

    Not in our library10.1182/blood-2011-06-360313

  63. 63.

    M. Pasquet, C. Bellanné-Chantelot, S. Tavitian, N. Prade, B. Beaupain, O. Larochelle, A. Petit, P. Rohrlich, C. Ferrand, E. Van Den Neste, H. A. Poirel, T. Lamy, M. Ouachée-Chardin, V. Mansat-De Mas, J. Corre, C. Récher, G. Plat, F. Bachelerie, J. Donadieu, E. Delabesse, High frequency of GATA2 mutations in patients with mild chronic neutropenia evolving to MonoMac syndrome, myelodysplasia, and acute myeloid leukemia. Blood 121, 822–829 (2013 ).

    Not in our library10.1182/blood-2012-08-447367

  64. 64.

    V. Bigley, U. Cytlak, M. Collin, Human dendritic cell immunodeficiencies. Semin. Cell Dev. Biol. 86, 50–61 (2019 ).

    Not in our library10.1016/j.semcdb.2018.02.020

  65. 65.

    D. Gao, M. J. Ciancanelli, P. Zhang, O. Harschnitz, V. Bondet, M. Hasek, J. Chen, X. Mu, Y. Itan, A. Cobat, V. Sancho-Shimizu, B. Bigio, L. Lorenzo, G. Ciceri, J. McAlpine, E. Anguiano, E. Jouanguy, D. Chaussabel, I. Meyts, M. S. Diamond, L. Abel, S. Hur, G. A. Smith, L. Notarangelo, D. Duffy, L. Studer, J. L. Casanova, S. Y. Zhang, TLR3 controls constitutive IFN-β antiviral immunity in human fibroblasts and cortical neurons. J. Clin. Invest. 131, e134529 (2021 ).

    Not in our library10.1172/jci134529

  66. 66.

    N. Kadowaki, S. Ho, S. Antonenko, R. W. Malefyt, R. A. Kastelein, F. Bazan, Y. J. Liu, Subsets of human dendritic cell precursors express different toll-like receptors and respond to different microbial antigens. J. Exp. Med. 194, 863–869 (2001 ).

    Not in our library10.1084/jem.194.6.863

  67. 67.

    K. Honda, Y. Ohba, H. Yanai, H. Negishi, T. Mizutani, A. Takaoka, C. Taya, T. Taniguchi, Spatiotemporal regulation of MyD88-IRF-7 signalling for robust type-I interferon induction. Nature 434, 1035–1040 (2005 ).

    Not in our library10.1038/nature03547

  68. 68.

    Y. Wang, M. Swiecki, S. A. McCartney, M. Colonna, dsRNA sensors and plasmacytoid dendritic cells in host defense and autoimmunity. Immunol. Rev. 243, 74–90 (2011 ).

    Not in our library10.1111/j.1600-065x.2011.01049.x

  69. 69.

    M. A. DePristo, E. Banks, R. Poplin, K. V. Garimella, J. R. Maguire, C. Hartl, A. A. Philippakis, G. del Angel, M. A. Rivas, M. Hanna, A. McKenna, T. J. Fennell, A. M. Kernytsky, A. Y. Sivachenko, K. Cibulskis, S. B. Gabriel, D. Altshuler, M. J. Daly, A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat. Genet. 43, 491–498 (2011 ).

    Not in our library10.1038/ng.806

  70. 70.

    H. Li, R. Durbin, Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25, 1754–1760 (2009 ).

    Not in our library10.1093/bioinformatics/btp324

  71. 71.
  72. 72.
  73. 73.

    A. Dobin, C. A. Davis, F. Schlesinger, J. Drenkow, C. Zaleski, S. Jha, P. Batut, M. Chaisson, T. R. Gingeras, STAR: Ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013 ).

    Not in our library10.1093/bioinformatics/bts635

  74. 74.

    Y. Liao, G. K. Smyth, W. Shi, featureCounts: An efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923–930 (2014 ).

    Not in our library10.1093/bioinformatics/btt656

  75. 75.

    J. Harrow, A. Frankish, J. M. Gonzalez, E. Tapanari, M. Diekhans, F. Kokocinski, B. L. Aken, D. Barrell, A. Zadissa, S. Searle, I. Barnes, A. Bignell, V. Boychenko, T. Hunt, M. Kay, G. Mukherjee, J. Rajan, G. Despacio-Reyes, G. Saunders, C. Steward, R. Harte, M. Lin, C. Howald, A. Tanzer, T. Derrien, J. Chrast, N. Walters, S. Balasubramanian, B. Pei, M. Tress, J. M. Rodriguez, I. Ezkurdia, J. van Baren, M. Brent, D. Haussler, M. Kellis, A. Valencia, A. Reymond, M. Gerstein, R. Guigó, T. J. Hubbard, GENCODE: The reference human genome annotation for The ENCODE Project. Genome Res. 22, 1760–1774 (2012 ).

    Not in our library10.1101/gr.135350.111

  76. 76.
  77. 77.

    M. D. Robinson, D. J. McCarthy, G. K. Smyth, edgeR: A Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139–140 (2010 ).

    Not in our library10.1093/bioinformatics/btp616

  78. 78.

    G. J. Xu, T. Kula, Q. Xu, M. Z. Li, S. D. Vernon, T. Ndung’u, K. Ruxrungtham, J. Sanchez, C. Brander, R. T. Chung, K. C. O’Connor, B. Walker, H. B. Larman, S. J. Elledge, Comprehensive serological profiling of human populations using a synthetic human virome. Science 348, aaa0698 (2015 ).

    Not in our library10.1126/science.aaa0698

  79. 79.

Cited by papers we hold 13

Reads

Read by people on this page

None yet.

Checked or read by AI through naulon

None yet.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.

Are you an author?

Is this your paper?

Claim it to add your note and be paid when agents cite it. Free.