Trio-based whole exome sequencing in patients with suspected sporadic inborn errors of immunity: a retrospective cohort study
preprint
OA: gold
CC-BY-4.0
Abstract
Background D e novo variants (DNVs) are currently not routinely evaluated as part of diagnostic whole exome sequencing (WES) analysis in patients with suspected inborn errors of immunity (IEI). Methods This study explored the potential added value of systematic assessment of DNVs in a retrospective cohort of 123 patients with a suspected sporadic IEI who underwent patient-parent trio-based WES. Results A likely molecular diagnosis for (part) of the immunological phenotype was achieved in 12 patients with the diagnostic in silico IEI WES gene panel. Exome-wide evaluation of rare, non-synonymous DNVs affecting coding or splice site regions led to the identification of 14 candidate DNVs in genes with an annotated immune function. DNVs were identified in IEI genes ( NLRP3 and RELA ) and potentially novel candidate genes, including PSMB10 , DDX1 , KMT2C and FBXW11 . The FBXW11 canonical splice site DNV, in a patient with autoinflammatory disease, was shown to lead to defective RNA splicing, increased NF-κB p65 signalling, and elevated IL-1β production in primary immune cells. Conclusions This retrospective cohort study advocates the implementation of trio-based sequencing in routine diagnostics of patients with sporadic IEI. Furthermore, we have provided functional evidence supporting a causal role for FBXW11 loss-of-function mutations in autoinflammatory disease. Funding This research was supported by grants from the European Union, ZonMW and the Radboud Institute for Molecular Life Sciences.
My notes (saved in your browser only)
Citation neighborhood (no data yet)
We don't have any in-corpus citations linked to this paper yet. The paper's references may be in our DB but unresolved to ``paper_id`` (resolution happens at ingest when the cited DOI matches a row we already have). Run the cross-source citation reconcile pass to retry.
References (82)
- doi:10.1186/s13059-015-0866-z via crossref
- doi:10.1073/pnas.0912629107 via crossref
- doi:10.1016/j.jaci.2016.08.003 via crossref
- doi:10.1038/nrg3241 via crossref
- doi:10.1038/nri3421 via crossref
- doi:10.1038/ng.712 via crossref
- doi:10.1126/science.aar6731 via crossref
- doi:10.1038/s41586-020-2832-5 via crossref
- doi:10.1016/j.jaci.2016.05.042 via crossref
- doi:10.1186/s13073-019-0649-3 via crossref
- doi:10.3389/fimmu.2019.02325 via crossref
- doi:10.3389/fimmu.2018.00420 via crossref
- doi:10.1084/jem.20110958 via crossref
- doi:10.1007/s10875-020-00758-x via crossref
- doi:10.1007/s12016-021-08838-5 via crossref
- doi:10.1080/10408363.2018.1488805 via crossref
- doi:10.1016/j.jaci.2014.12.1941 via crossref
- doi:10.1002/art.39770 via crossref
- doi:10.1002/art.39960 via crossref
- doi:10.1056/nejmoa040036 via crossref
- doi:10.1182/blood.2020009620 via crossref
- doi:10.1056/nejmoa2026834 via crossref
- doi:10.1016/j.jaci.2021.05.014 via crossref
- doi:10.1016/j.ajhg.2012.08.006 via crossref
- doi:10.1001/jama.2013.281053 via crossref
- doi:10.1038/s41436-019-0585-z via crossref
- doi:10.1111/j.1365-2133.2008.08497.x via crossref
- doi:10.1038/nn.4352 via crossref
- doi:10.1093/bioinformatics/btp698 via crossref
- doi:10.1101/gr.107524.110 via crossref
- doi:10.1101/gr.138115.112 via crossref
- doi:10.1038/s41586-020-2308-7 via crossref
- doi:10.1101/gr.9.8.677 via crossref
- doi:10.1038/gim.2015.30 via crossref
- doi:10.1038/nature19057 via crossref
- doi:10.1038/ejhg.2013.118 via crossref
- doi:10.1002/humu.23892 via crossref
- doi:10.1093/bioinformatics/btz482 via crossref
- doi:10.1093/nar/gkw865 via crossref
- doi:10.1007/bf00279094 via crossref
- doi:10.1016/j.chom.2016.10.006 via crossref
- doi:10.1086/340786 via crossref
- doi:10.1136/annrheumdis-2012-202913 via crossref
- doi:10.1084/jem.20160724 via crossref
- doi:10.1002/art.41531 via crossref
- doi:10.1007/s10875-019-00737-x via crossref
- doi:10.1038/s41598-018-24199-0 via crossref
- doi:10.1016/j.jaci.2019.11.024 via crossref
- doi:10.1016/j.jdermsci.2017.03.018 via crossref
- doi:10.1016/j.clim.2012.12.013 via crossref
- doi:10.1016/j.celrep.2015.05.038 via crossref
- doi:10.1016/j.ajpath.2015.10.028 via crossref
- doi:10.1038/ni.3272 via crossref
- doi:10.1073/pnas.0407180101 via crossref
- doi:10.1016/j.immuni.2011.03.027 via crossref
- doi:10.1371/journal.pgen.1006864 via crossref
- doi:10.1038/s41419-018-0440-1 via crossref
- doi:10.1101/mcs.a004044 via crossref
- doi:10.1016/j.ajhg.2010.10.031 via crossref
- doi:10.1172/jci81260 via crossref
- doi:10.1182/blood.2021011314 via crossref
- doi:10.1080/08916930802024202 via crossref
- doi:10.1111/j.1600-065x.2012.01098.x via crossref
- doi:10.1128/mcb.00857-14 via crossref
- doi:10.1038/25159 via crossref
- doi:10.1038/nrm3582 via crossref
- doi:10.1016/j.ajhg.2019.07.005 via crossref
- doi:10.3390/biomedicines7020040 via crossref
- doi:10.1111/imr.12898 via crossref
- doi:10.1016/j.clim.2020.108376 via crossref
- doi:10.1016/j.jaci.2019.09.009 via crossref
- doi:10.1016/j.jaci.2014.07.050 via crossref
- doi:10.1182/blood-2004-02-0675 via crossref
- doi:10.1111/cge.13946 via crossref
- doi:10.1056/nejmoa1206524 via crossref
- doi:10.1038/nature21062 via crossref
- doi:10.1056/nejmoa1512234 via crossref
- doi:10.1056/nejmoa073687 via crossref
- doi:10.1097/mph.0000000000000479 via crossref
- doi:10.1111/cge.12208 via crossref
- doi:10.1182/blood-2018-11-886028 via crossref
- doi:10.1002/humu.22844 via crossref
Source provenance
- crossref
- last seen: 2026-06-06T01:00:27.852702+00:00
- europepmc
- last seen: 2026-05-19T01:45:01.086888+00:00
- unpaywall
- last seen: 2026-05-21T02:00:01.467718+00:00
License: CC-BY-4.0