Although we inherit the vast majority of genomic variants from our parents, a small fraction of variants arises de novo during parental gametogenesis or after zygosis (Acuna-Hidalgo et al., 2016). The biological rate at which these variants develop in humans translates to an average of 50-100 de novo single nucleotide variants (SNVs) per genome per generation, only one or two of which affect coding regions (Acuna-Hidalgo et al., 2016; Lynch, 2010). De novo variants (DNVs) are often very rare or unique (absent from population databases) and have a higher a priori chance to be pathogenic than inherited variants (Meyts et al., 2016; Veltman and Brunner, 2012). In contrast to inherited variants, DNVs emerge between two generations and are subjected to minimal evolutionary selection pressure that would normally purify damaging mutations (Acuna-Hidalgo et al., 2016). DNVs affecting nucleotides or genes that have been targeted by strong purifying selection can therefore be highly damaging to their respective non-redundant biological functions, as has for example been shown for genes involved in innate immunity, an ancient host defence mechanism that developed under constant environmental selection pressure by microorganisms (Veltman and Brunner, 2012; Quintana-Murci and Clark, 2013).

Therefore, DNVs are important candidates to pursue as a cause for disease, particularly in rare, sporadic phenotypes (Lynch, 2010; Veltman and Brunner, 2012; Vissers et al., 2010). The presence of such candidate DNVs can be assessed by trio-based sequencing, in which the patient is sequenced together with the (healthy) parents (Acuna-Hidalgo et al., 2016). Most experience with the systematic diagnostic assessment of DNVs has been gained in the field of developmental disorders, in which DNVs have been shown to constitute up to 50% of disease-causing mutations (Vissers et al., 2010; Martin et al., 2018; Kaplanis et al., 2020). However, the contribution of DNVs in the pathogenesis of other disorders such as inborn errors of immunity (IEI) is less clear.

DNVs as the underlying cause in IEI patients have been widely reported in literature, but most of these mutations were determined to be de novo through subsequent segregation analysis and not by trio-based sequencing (Stray-Pedersen et al., 2017; Arts et al., 2019; Rudilla et al., 2019; Bradshaw et al., 2018; Liu et al., 2011). IEI can present at different stages of life with a variable phenotype ranging from recurrent, life-threatening infections to immune dysregulation and cancer (Arts et al., 2019; Bousfiha et al., 2020). Particularly in IEI patients with early-onset and severe complex phenotypes, there is an increased chance for an underlying causative DNV (Veltman and Brunner, 2012; Vorsteveld et al., 2021). Moreover, DNVs that arise post-zygotically or somatically are recognized as an important underlying cause for IEI patients with autoinflammatory disease (Labrousse et al., 2018; de Inocencio et al., 2015; Mensa-Vilaro et al., 2016; Kawasaki et al., 2017; Holzelova et al., 2004; Aluri et al., 2021; Beck et al., 2020; van der Made et al., 2022; Zhou et al., 2012). The potentially added value of systematic DNV assessment in IEI patients is supported by the findings of an international cohort study, which reported a diagnosis in 44% of cases after patient-parent trio sequencing, compared to 36% by single whole exome sequencing (WES) (Stray-Pedersen et al., 2017). However, trio-based sequencing has not yet been implemented as part of the routine diagnostic procedure of IEI patients.

The current study has aimed to explore the potential added value of systematic assessment of DNVs in a retrospective cohort of 123 patients with a suspected, sporadic IEI that underwent trio-based WES.

We investigated the potential benefit of trio-based whole exome sequencing (WES) over routine single WES analysis in a retrospective cohort of 123 patients with suspected, sporadic inborn errors of immunity (IEI). Systematic analysis of de novo SNVs and small insertion-deletions (indels) led to the identification of 14 candidate de novo variants (DNVs), of which two were in known IEI genes and classified as pathogenic (NLRP3, RELA). Of the 12 variants in potentially novel candidate genes for IEI, four were considered to be most likely pathogenic (PSMB10, DDX1, KMT2C, FBXW11) based on gene and variant level metrics. Additionally, we have provided functional evidence that the FBXW11 splice site DNV led to skipping of exon 12 resulting in the transcription of an altered protein product and subsequent downstream activation of NF-κB signalling with higher IL-1β production capacity.

We have performed a systematic DNV analysis in patients with a suspected, sporadic IEI. On average, these patients carried 1.4 DNVs in coding regions, a rate comparable to other, larger studies, indicating that DNV enrichment or depletion in IEI patients is unlikely (Kaplanis et al., 2020). Based on gene and variant level information, 14 DNVs (11.4%) were considered potential disease-causing candidates. Six of the candidate DNVs (4.9%) were considered likely or possibly pathogenic variants, while the consequence of the other eight DNVs (6.5%) was uncertain.

Two DNVs were in IEI genes (NLRP3, RELA) listed in the most recent IUIS classification and were classified as pathogenic (Richards et al., 2015; Wallis et al., 2013; Tangye et al., 2020). The heterozygous NLRP3 variant in patient 59 (p.Thr350Met) with Muckle-Wells syndrome had been reported in patients with a similar phenotype (Dodé et al., 2002; Jiménez-Treviño et al., 2013). Moreover, the canonical splice site DNV affecting RELA in patient 119 with mucocutaneous ulceration was predicted to lead to a loss of the splice acceptor site and a subsequent frameshift. Heterozygous loss-of-function (LoF) mutations causing RelA haploinsufficiency have been reported as a cause of chronic mucocutaneous ulceration and familial Behçet’s disease (Badran et al., 2017; Adeeb et al., 2021). Badran et al. reported a family of four affected family members with mucocutaneous ulceration harbouring a mutation in the canonical donor splice site of exon 6 (NM_021975:c.559+1 G>A), likely leading to a premature stop codon and haploinsufficiency (Badran et al., 2017). The DNV in RELA was not picked up in our diagnostic in silico IEI gene panel (Radboudumc, 2021), because evidence was considered insufficient at the time. Based on the matching phenotype and similar mutational mechanism this DNV has now been classified as pathogenic, which could potentially carry implications for therapy with anti-tumour necrosis factor alpha (TNFα) inhibitors (Adeeb et al., 2021).

Moreover, DNVs in the potentially novel IEI genes PSMB10, DDX1, KMT2C, and FBXW11 were considered the most promising candidate DNVs based on the predicted variant effect and immunological function of the respective gene. The private missense DNV in PSMB10 was found in a patient with clinically diagnosed Omenn syndrome and showed high scores for pathogenicity. The presumed deleterious effect was further supported by the extremely rare occurrence of revertant mosaicism in this patient (unpublished data), that is, somatic and recurrent uniparental disomy 16q overlapping the PSMB10 locus, suggesting a strong (cellular) effect of this variant. A homozygous missense variant in PSMB10 has been shown previously in a 3-year-old Algerian female with autoinflammatory signs suggestive of proteasome-associated autoinflammatory syndrome (PRAAS), leading to disturbed formation of the 20S proteasome (Sarrabay et al., 2020). In addition, it has been shown in mice that another homozygous PSMB10 variant (p.Gly170Trp) could induce severe combined immunodeficiency (SCID) and systemic autoinflammation, while heterozygous mice only had a T cell defect (Treise et al., 2018). PRAAS is predominantly caused by autosomal recessive or digenic heterozygous mutations in proteasome subunit genes or their chaperone proteins, although heterozygous (de novo) mutations have also been shown to underlie PRAAS (Sarrabay et al., 2020; Agarwal et al., 2010; Brehm et al., 2015). A de novo missense variant in the b1i-subunit PSMB9 (NM_002800; c.467 G>A; p.G156D) was found in three unrelated infants with a type I interferonopathy with immunodeficiency (PRAAS-ID). This variant resulted in impaired maturation and activity of the immunoproteasome in patient-derived B lymphoblastoid cell lines (Kanazawa et al., 2021; Kataoka et al., 2021), a phenotype that was mirrored in mice (Kanazawa et al., 2021). It is interesting to consider that the PSMB10 DNV could act through a similar autosomal dominant mutational mechanism by affecting the formation of the immunoproteasome, as has been shown in mice harbouring a mutation affecting an amino acid in close proximity to the identified DNV in the patient (Treise et al., 2018). However, the functional consequence and pathogenic relevance of the candidate DNV in PSMB10 remain to be confirmed.

In addition, a de novo frameshift variant in the highly intolerant DDX1 (pLI 0.994) was identified in a patient with hypogammaglobulinemia, hematopoietic cell lineage abnormalities and recurrent infections. Although DDX1 plays a role in NF-κB signalling, type I interferon responses and the regulation of hematopoietic stem and progenitor cell homeostasis (Zhang et al., 2011; Wang et al., 2021), a causal genotype-phenotype relationship remains unclear. Furthermore, the de novo frameshift variant in KMT2C was detected in a patient with combined immunodeficiency and a neurodevelopmental phenotype, displaying partial phenotypic overlap with Kleefstra syndrome type 2 that has already been associated with de novo LoF mutations in KMT2C (Koemans et al., 2017). Two of the six individuals described by Koemans et al. were reported to have recurrent respiratory infections (Koemans et al., 2017). The occurrence of immunological symptoms in patients with mutations in chromatin-regulating genes is increasingly being recognised in the field of intellectual disability (ID) (Ehrlich et al., 2008; Hoffman et al., 2005). Therefore, more in-depth characterisation of patients with KMT2C mutations and predominant ID phenotypes might indicate (mild) immunological phenotypes that overlap with the phenotype of our patient, in support of pathogenicity of the observed DNV.

Another candidate DNV in a potentially novel IEI gene was identified in the highly conserved FBXW11 (pLI 0.976). This DNV affected the canonical splice acceptor site preceding exon 12 and was shown to create a splice defect leading to exon skipping with a shortened transcript that retained expression at the RNA level. Exon 12 encodes component 7 of the WD40 repeat domain (WD7), which is involved in substrate recognition (Skaar et al., 2013). De novo missense and nonsense variants in FBXW11 have been previously described in patients with a neurodevelopmental syndrome with abnormalities of the digits, jaw and eyes (Holt et al., 2019). These variants were located in WD1, WD4, and WD6 and have been shown to compromise substrate recognition or binding of the Wnt and Hedgehog signalling developmental pathways. We hypothesised a specific functional effect on NF-κB signalling in our patient with a distinct autoinflammatory phenotype. In peripheral blood mononuclear cells (PBMC) extracted from the patient, we demonstrated that the phosphorylation of the NF-κB subunit p65 was constitutively higher in monocytes and CD8+ T cells as compared to a healthy control, which suggests a functional effect of the FBXW11 variant. This effect is further substantiated by the observation of increased p65 phosphorylation and downstream production of IL-1β after stimulation with pathogens and a TLR3 ligand in the patient. However, a note of caution should be made regarding n=1 studies, as we cannot exclude that the difference is due to normal inter-individual biological variability. These results suggest that NF-κB signalling was aberrantly increased in the patient, a mechanism that has been shown to be involved in the pathogenesis of other monogenic autoinflammatory disorders known as relopathies (van der Made et al., 2020). However, the exact mutational mechanism that explains the different phenotype compared to the previous cases with neurodevelopmental disease remains unclear. The most likely explanation would be a differential effect on the specific functions of the SCF complex that could be cell-type dependent rather than a difference in tissue-specific isoform expression, since the DNV affects all three high quality protein-coding transcripts that produce the most abundant isoforms (Consortium, 2020). Further experiments addressing the effect of this DNV on IκBα degradation, substrate recognition and TrCP protein abundance should be undertaken to provide conclusive evidence.

To our knowledge, two other cohort studies have systematically performed trio-based sequencing in IEI patients as part of their study design, although patients were not pre-selected based on sporadic phenotypes (Stray-Pedersen et al., 2017; Simon et al., 2020). Stray-Pedersen et al. conducted a large international cohort study to investigate the benefit of WES in IEI patients from 278 families, which included 39 patient-parent trios (Stray-Pedersen et al., 2017). The authors reported a molecular diagnosis in 40% of the patients, including 15 (13.6%) de novo mutations, of which 4 were identified by trio-based analysis and 11 after segregation analysis. The additional value of trio-based sequencing is indicated by the higher detection rate compared to that of the single cases followed by segregation analysis of candidate variants (44 vs 36%), as well as the discovery of potentially novel IEI genes or expansion of the immunological phenotype. Furthermore, Simon et al. performed WES in a cohort of 106 IEI patients with a consanguineous background, including 26 patient-parent trios (Simon et al., 2020). A molecular diagnosis was established in 70% of the patients, including 13 (17.6%) de novo mutations, although it is unclear whether these variants were identified through trio-based sequencing or the segregation analysis that was performed for each variant. The authors conclude that trio-based sequencing does not lead to additional diagnostic benefit, although it should be argued that this is also not expected in a cohort of predominantly consanguineous patients (62.2%) with a higher a priori chance of autosomal recessive (AR) disease.

Multiple studies have highlighted the potential benefits of routine trio-based sequencing in IEI patients over single WES (Meyts et al., 2016; Arts et al., 2019; Vorsteveld et al., 2021; Chinn et al., 2020). These advantages apply mostly to patients with sporadic, severe phenotypes in particular, as has been shown for other rare diseases such as neurodevelopmental disorders (Kaplanis et al., 2020). Trio-based sequencing constitutes an unbiased way to identify rare, coding DNVs that are by definition strong candidate variants. It could therefore improve candidate variant prioritisation both during in silico gene panel analysis as part of routine diagnostics, as well as for research-based exome-wide analysis. Furthermore, targeted DNV analysis could improve the detection of somatic variants, which is especially relevant in the field of monogenic autoinflammatory disorders (van der Made et al., 2022). Somatic variants can be successfully identified by trio-based WES (de Koning et al., 2015). However, this specific DNV subtype can be missed during routine analysis especially if the variant allele fraction (VAF) is below the set threshold during standard variant filtering, which is not required to filter out false-positive variants for a condensed set of potential DNVs. In this study, no candidate DNVs with a VAF below the set threshold of 20% were found in established IEI genes. Another advantage of trio-based sequencing is that it provides direct segregation of inherited variants and enables determination of autosomal recessive compound heterozygosity or X-linked recessive disease as the causative disease mechanism.

Based on the results of this study as well as evidence from other studies including those from other rare disease fields, we suggest that trio-based sequencing should be part of the routine evaluation of patients with a sporadic IEI phenotype (Box 1). An exome-wide analysis should be conducted to identify potentially novel disease genes in cases with a negative diagnostic WES result in whom a strong clinical suspicion for an underlying monogenic cause remains. Thus far, the relative proportion of DNVs among IEI patients with a genetic diagnosis, estimated to be around 6–14%, seems modest compared to other rare disease fields (i.e. >80% in neurodevelopmental disorders (NDDs)) (Brunet et al., 2021). There are several explanations for this difference that suggest that the true contribution of DNVs is higher than currently appreciated. Most importantly, much more experience has been gained with DNV assessment in the field of NDDs. Despite a steep increase in the total diagnostic rate (Vissers et al., 2010; de Ligt et al., 2012; Deciphering Developmental Disorders Study, 2017) and the identification of 285 developmental disorder (DD)-associated DNVs, modelling suggests that more than 1000 DD-associated genes still remain to be discovered (Kaplanis et al., 2020). As more trio-based sequencing data will be generated from suspected IEI patients, the field should undertake larger-scale analyses that leverage existing statistical models from the field of NDDs/DDs, including models for gene/exon level enrichment and the identification of gain-of-function nucleotide clusters (Kaplanis et al., 2020). Moreover, there is still a bias towards AR disease genes in the IEI field, while this imbalance is shifting with the discovery of an increasing number of autosomal dominant (AD) disease genes (van der Made et al., 2020). Trio-based sequencing could accelerate the discovery of mutations in novel AD IEI genes.

Inborn errors of immunity constitute a large group of heterogeneous disorders with differences in the expected contribution of DNVs. The a priori probability for the identification of a DNV will be highest in patients with early-onset, severe phenotypes, such as the combined immunodeficiencies (CID), especially CIDs with syndromic features, and patients with autoinflammatory syndromes and/or immune dysregulation with autoimmunity (Box 1). Although most of the reported genes underlying CIDs follow AR inheritance patterns, many genes following AD and X-linked (dominant) inheritance patterns have been described in recent years (Tangye et al., 2020). The genes affected in these disorders possess high intolerance for loss-of-function mutations and essential biological functions. As expected, the DNVs in this category reported to date act through mechanisms of haploinsufficiency (i.e. RELA, pLI 0.999), dominant-negative interference (i.e. IKZF1, pLI 0.999 Kuehn et al., 2016; STAT3, pLI 1.000 Holland et al., 2007) or complete deficiency in hemizygotic males (i.e. WAS, pLI 0.999 Howard et al., 2016; IL2RG, pLI 0.992 Moya-Quiles et al., 2014). Some heterozygous DNVs can also cause CID through hypermorphic effects at protein level (i.e. RAC2, pLI 0.966 Hsu et al., 2019). Trio-based sequencing should also be considered in patients with sporadic autoinflammatory syndromes and/or autoimmunity, even when presenting at an adult age that could suggest somatic de novo mutations. In these patients, various pathogenic DNVs in different genes have already been described, originating both from the germline (PLCG2, STAT1) and soma (i.e. NLRP3, UBA1, TLR8) (Liu et al., 2011; Mensa-Vilaro et al., 2016; Aluri et al., 2021; Beck et al., 2020; van der Made et al., 2022; Zhou et al., 2012). These genes do not necessarily have high constraint for LoF mutations, but they possess nucleotide clusters that are highly conserved and intolerant to variation, encoding protein domains with important regulatory functions.

This explorative study has a number of limitations. First, the sample size precludes a reliable estimation of the prevalence of DNVs among patients with sporadic IEIs. Furthermore, the strict diagnostic rate of both inherited variants and (likely) pathogenic DNVs in our cohort is limited compared to other studies. It has been previously reported that the diagnostic yield of WES for IEI patients varies widely from 10 to 79% (Vorsteveld et al., 2021). This study reports (likely) pathogenic variants in 22 cases (17.9%), of which 10 (8.1%) received a definitive molecular diagnosis for their immunological phenotype. In addition to inherent technical shortcomings of WES, including uneven coverage of coding regions and GC bias and also the inability to explore the non-coding space (Meyts et al., 2016), the most likely explanation for a relatively low diagnostic yield in our study is the patient selection and the primary focus on DNVs, which constitute only a fraction of disease-causing variants. We excluded patients with suspected inherited disease but chose not to apply any other selection criteria in order to study a representative cross-section of suspected IEI patients in our centre in whom WES was performed. As a result, patients were included even if the a priori chance of an IEI was limited but to be ruled out in the differential diagnosis (i.e. new-born screening shows low T cell receptor excision circles (TRECs)). Moreover, compared to other cohorts, the percentage of patients with syndromal CIDs, autoinflammatory syndromes and immune dysregulation was relatively high and could influence the generalisability of our results. Lastly, the functional effect of most candidate DNVs were not evaluated. As DNVs have a high chance of being deleterious, functional experiments should always be attempted to validate the predicted effect. The candidate DNVs in potentially novel IEI genes were shared on GeneMatcher in order to find similar cases that could motivate further investigation into the underlying mechanisms (Acuna-Hidalgo et al., 2016; Sobreira et al., 2015).

In conclusion, we applied trio-based WES in a retrospective cohort of 123 patients with suspected, sporadic IEI, leading to the identification of 14 DNVs with a possible or likely chance of pathogenicity. Amongst the candidate DNVs in potentially novel IEI genes, additional functional evidence was provided in support of a pathogenic role for the DNV in FBXW11 in a patient with an autoinflammatory phenotype. We advocate the structural implementation of trio-based sequencing in the diagnostic evaluation of patients with sporadic IEI. With decreasing costs of exome sequencing, this approach could improve the diagnostic rate of IEI and advance IEI gene discovery.

The code used to filter DNA sequencing data for candidate de novo mutations (DNMs) and to generate output files is provided in Figure 1—source code 1. Source data linked to Figure 1—figure supplement 1 is provided as an additional, numerical data file. Source data for candidate DNM evaluation is provided in Figure 1—source data 2. Source data linked to Figure 2—figure supplement 1A is an uncropped, raw gel image used to create this figure. Source data linked to Figure 2B–D is provided as an additional, numerical data file. Raw DNA sequencing data of patients are not publicly available as it is confidential human subject data that would compromise anonymity. Researchers that are interested to access the sequencing data of our cohort are advised to contact the corresponding author, A Hoischen (alexander.hoischen@radboudumc.nl). Anonymized subject data will be shared on request from qualified investigators for the purposes of replicating procedures and results, and for other non-commercial research purposes within the limits of participants' consent. Any data sharing will also require evaluation of the request by the regional Arnhem and Nijmegen Ethics Committee and the signature of a data transfer agreement (DTA).

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Author details

1. Anne Hebert

   Department of Human Genetics, Radboud Institute of Molecular Life Sciences (RIMLS), Radboud University Medical Center, Nijmegen, Netherlands

   Contribution

   Data curation, Formal analysis, Investigation, Visualization, Methodology, Writing – original draft, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-8945-015X

2. Annet Simons

   Department of Human Genetics, Radboud Institute of Molecular Life Sciences (RIMLS), Radboud University Medical Center, Nijmegen, Netherlands

   Contribution

   Data curation, Formal analysis, Investigation, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

3. Janneke HM Schuurs-Hoeijmakers

   Department of Human Genetics, Radboud Institute of Molecular Life Sciences (RIMLS), Radboud University Medical Center, Nijmegen, Netherlands

   Contribution

   Resources, Writing – review and editing

   Competing interests

   No competing interests declared

4. Hans JPM Koenen

   Department of Laboratory Medicine, Laboratory for Medical Immunology, Radboud University Medical Center, Nijmegen, Netherlands

   Contribution

   Resources, Formal analysis, Visualization, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

5. Evelien Zonneveld-Huijssoon

   Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, Netherlands

   Contribution

   Resources, Writing – review and editing

   Competing interests

   No competing interests declared

6. Stefanie SV Henriet

   Department of Pediatric Infectious Diseases and Immunology, Amalia Children’s Hospital, Radboud Center for Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, Netherlands

   Contribution

   Resources, Writing – review and editing

   Competing interests

   No competing interests declared

7. Ellen JH Schatorjé

   Department of Pediatric Rheumatology and Immunology, Amalia Children’s Hospital, Radboud University Medical Center, Nijmegen, Netherlands

   Contribution

   Resources, Writing – review and editing

   Competing interests

   No competing interests declared

8. Esther PAH Hoppenreijs

   Department of Pediatric Rheumatology and Immunology, Amalia Children’s Hospital, Radboud University Medical Center, Nijmegen, Netherlands

   Contribution

   Resources, Writing – review and editing

   Competing interests

   No competing interests declared

9. Erika KSM Leenders

   Department of Human Genetics, Radboud Institute of Molecular Life Sciences (RIMLS), Radboud University Medical Center, Nijmegen, Netherlands

   Contribution

   Resources, Writing – review and editing

   Competing interests

   No competing interests declared

10. Etienne JM Janssen

    Department of Clinical Genetics, Maastricht University Medical Center+, Maastricht, Netherlands

    Contribution

    Resources, Writing – review and editing

    Competing interests

    No competing interests declared

11. Gijs WE Santen

    Center for Human and Clinical Genetics, Leiden University Medical Center, Leiden, Netherlands

    Contribution

    Resources, Writing – review and editing

    Competing interests

    No competing interests declared

12. Sonja A de Munnik

    Department of Human Genetics, Radboud Institute of Molecular Life Sciences (RIMLS), Radboud University Medical Center, Nijmegen, Netherlands

    Contribution

    Resources, Writing – review and editing

    Competing interests

    No competing interests declared

13. Simon V van Reijmersdal

    Department of Human Genetics, Radboud Institute of Molecular Life Sciences (RIMLS), Radboud University Medical Center, Nijmegen, Netherlands

    Contribution

    Investigation, Methodology, Writing – review and editing

    Competing interests

    No competing interests declared

14. Esther van Rijssen

    Department of Laboratory Medicine, Laboratory for Medical Immunology, Radboud University Medical Center, Nijmegen, Netherlands

    Contribution

    Resources, Investigation, Methodology, Writing – review and editing

    Competing interests

    No competing interests declared

15. Simone Kersten

    Department of Human Genetics, Radboud Institute of Molecular Life Sciences (RIMLS), Radboud University Medical Center, Nijmegen, Netherlands

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-0251-5564

16. Mihai G Netea

    1. Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, Netherlands
    2. Department for Immunology and Metabolism, Life and Medical Sciences Institute (LIMES), University of Bonn, Bonn, Germany

    Contribution

    Supervision, Funding acquisition, Methodology, Writing – review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0003-2421-6052

17. Ruben L Smeets

    1. Department of Laboratory Medicine, Laboratory for Medical Immunology, Radboud University Medical Center, Nijmegen, Netherlands
    2. Department of Laboratory Medicine, Laboratory for Diagnostics, Radboud University Medical Center, Nijmegen, Netherlands

    Contribution

    Resources, Formal analysis, Methodology, Writing – review and editing

    Competing interests

    No competing interests declared

18. Frank L van de Veerdonk

    Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, Netherlands

    Contribution

    Supervision, Funding acquisition, Writing – review and editing

    Competing interests

    Reviewing editor, eLife

    "This ORCID iD identifies the author of this article:" 0000-0002-1121-4894

19. Alexander Hoischen

    1. Department of Human Genetics, Radboud Institute of Molecular Life Sciences (RIMLS), Radboud University Medical Center, Nijmegen, Netherlands
    2. Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, Netherlands

    Contribution

    Conceptualization, Formal analysis, Supervision, Funding acquisition, Investigation, Writing – original draft, Project administration, Writing – review and editing

    For correspondence

    alexander.hoischen@radboudumc.nl

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-8072-4476

20. Caspar I van der Made

    1. Department of Human Genetics, Radboud Institute of Molecular Life Sciences (RIMLS), Radboud University Medical Center, Nijmegen, Netherlands
    2. Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, Netherlands

    Contribution

    Conceptualization, Data curation, Formal analysis, Supervision, Investigation, Visualization, Methodology, Writing – original draft, Project administration, Writing – review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0003-0763-4017

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