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Casanova, J.-L.

Publications and source records attributed to Casanova, J.-L..

At least 19 recordsLinked to original sources

A flow cytometry-based assay to quantify the binding of transmembrane ligands to their cognate receptors using fluorescent virus-like particles

The binding of transmembrane (TM) ligands to their cognate TM receptors on neighboring cells governs intercellular adhesion and direct cell-cell communication. However, these interactions are difficult to study in vitro because they depend on membrane presentation, ligand orientation, receptor clustering, and avidity, features often not captured by soluble recombinant ligands or cell-free assays. Here, we describe a flow cytometry-based assay using fluorescent, lentiviral-derived virus-like particles (VLPs) displaying TM ligands to quantify binding to their receptors on target cells. Fluorescent VLPs are generated in-house by plasmid transfection in HEK293T cells and enable direct fluorescent detection without fluorochrome-conjugated secondary antibodies. The system is modular and readily accommodates engineered ligand constructs, including patient-derived variants. We applied this platform to generate ICAM-1-displaying fluorescent VLPs and to study human LFA-1 function in patient-derived leukocytes. This protocol provides a detailed workflow for VLP production and in vitro binding assays, offering a simple, quantitative, and cost-effective approach for studying TM ligand-receptor interactions in a membrane context. The system is well suited for mechanistic studies, functional assessment of patient-derived variants, and direct binding assays using patient-derived cells. Integrating the assay into multicolor flow cytometry panels enables simultaneous immunophenotyping and quantification of up to four ligand-receptor interactions at single-cell resolution. Key featuresO_LIQuantifies TM ligand-receptor binding in a membrane context using fluorescent VLPs and flow cytometry. C_LIO_LIFully in-house, modular system based on plasmid transfection in HEK293T cells, without reliance on recombinant ligands or fluorochrome-conjugated secondary antibodies. C_LIO_LISupports testing of engineered ligand variants, including patient-derived alleles, and direct functional studies on patient-derived cells. C_LIO_LICompatible with multicolor flow cytometry panels, enabling simultaneous immunophenotyping and quantification of up to four ligand-receptor interactions at single-cell resolution. C_LI Graphical overview O_FIG O_LINKSMALLFIG WIDTH=197 HEIGHT=200 SRC="FIGDIR/small/725198v1_ufig1.gif" ALT="Figure 1"> View larger version (55K): org.highwire.dtl.DTLVardef@a43069org.highwire.dtl.DTLVardef@166491borg.highwire.dtl.DTLVardef@49c7d4org.highwire.dtl.DTLVardef@1de36a0_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

Human iPSC derived alveolar macrophages reveal macrophage subtype specific functions of itaconate in M. tuberculosis host defense

Mycobacterium tuberculosis (Mtb) must survive within multiple macrophage populations during infection, including alveolar macrophages (AM) and recruited inflammatory macrophages. In mice, itaconate, produced in macrophages by ACOD1 mediated decarboxylation of aconitate, has direct antimicrobial activity, modulates inflammatory cytokines, and is required for resistance to M. tuberculosis (Mtb) infection. The role of itaconate in human macrophages is less clear and whether itaconate mediates distinct effects in macrophage subtypes is unknown. Here, we investigated the role of itaconate in human iPSC-derived macrophages, either induced by GM-CSF to resemble alveolar macrophages (AM-Like cells), or treated with M-CSF to generate control macrophages (MCDM cells). Both types of human macrophages produce substantially less itaconate than mouse macrophages and AM-Ls produced 4-fold less itaconate than MCDMs. Surprisingly, ACOD1 deficient AM-L macrophages, but not MCDM macrophages, were permissive for Mtb growth. Moreover, itaconate functioned to dampen the Mtb induced inflammatory response in MCDMs, but not AM-L macrophages, affecting both the Type I IFN and TNF pathways. These results indicate that itaconate is involved in human macrophage responses to TB, with distinct roles in different macrophage subsets. These results also show that genetically tractable hiPSC-derived macrophages are a robust and versatile model to dissect cellular host pathogen interactions.

immunology↗

ARAP2 regulates responses to interferon-gamma by restricting SOCS1

Interferon-gamma (IFN{gamma}) is critical for immunity against intra-macrophagic pathogens, signaling through the JAK-STAT pathway to induce a tyrosine-phosphorylation cascade that ensures a potent immune response. Excessive JAK-STAT signaling can drive hyperinflammation and autoimmunity, and thus signaling is tightly and selectively regulated by the IFN{gamma}-inducible protein, Suppressor of Cytokine Signaling 1 (SOCS1). SOCS1 inhibits signaling by directly blocking JAK kinase activity. Here we identified a SOCS1-interacting partner, ARAP2 that fine-tunes SOCS1 function. We report that tyrosine 415 in ARAP2 binds the SOCS1-Src Homology 2 (SH2) domain and limits the ability of SOCS1 to inhibit IFN{gamma} signaling. Our findings show that ARAP2 promotes the IFN{gamma} response through a phosphorylation dependent interaction with the negative regulator SOCS1.

cell biology↗

Elevated levels of intracellular RNA lariats suppress the antiviral response

Recent studies report the genetic loss of the lariat debranching enzyme (DBR1) activity increases susceptibility to viral infection. Here, we show that more than 25% of human introns contain large hairpin structures created by the folding of two Alu elements inserted in opposite orientation. In wildtype cells, this large reservoir of endogenous dsRNA is efficiently degraded. In DBR1-null cells, lariats accumulate in the cytosol and dsRNA becomes enriched. We demonstrate how the chronic exposure to these lariats attenuates the dsRNA sensors, reducing the response of the MDA5, RIG-I, RNase L and PKR sensing pathways. We observe evidence for both attenuation and endogenous dsRNA in anti-viral response and viral evasion. Lariats are transiently elevated during infection (e.g. HSV-1, influenza, KSHV). The HSV-1 genome expresses multiple, stable lariats that may attenuate dsRNA sensors during latency. HIGHLIGHTSO_LIIntronic inverted repeat Alu elements constitute largest source of endogenous dsRNA. C_LIO_LIIn the absence of DBR1, lariats accumulate in the cytoplasm and form dsRNA. C_LIO_LIChronic exposure to endogenous dsRNA in a DBR1-depleted environment desensitizes the dsRNA sensing pathway. C_LIO_LIICP0 intron 1 of HSV-1 has a highly-structured stable lariat. C_LI GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=196 HEIGHT=200 SRC="FIGDIR/small/627371v1_ufig1.gif" ALT="Figure 1"> View larger version (49K): org.highwire.dtl.DTLVardef@3698bborg.highwire.dtl.DTLVardef@654727org.highwire.dtl.DTLVardef@1229245org.highwire.dtl.DTLVardef@b10622_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

Polyunsaturated fatty acid-derived lipid mediator networks characterize COVID-19 severity and risk for critical illness

Severe COVID-19, caused by SARS-CoV-2 infection, is characterized by excessive inflammation leading to the development of pneumonia and acute respiratory distress syndrome. Bioactive lipid mediators (LMs) derived from {omega}6 and {omega}3 polyunsaturated fatty acids are central to the regulation of inflammation, controlling both its initiation and resolution. Still, their role in COVID-19 remains underexplored. By employing a holistic approach involving the analysis of white blood cell transcriptomes, targeted lipidomics, cytokine and immune cell profiling, across the spectrum of disease severity groups, including mild non-hospitalized patients and healthy individuals, we now show that LM networks are profoundly altered in COVID-19, correlate with inflammatory patterns, and stratify patients according to disease severity. Central to this are CYP450-derived LMs such as 20-HETE, lipid peroxidation metabolites such as iPF2a-VI, and lipoxygenase-derived LMs such as 12-HETE, all of which are major vasoactive mediators of inflammation. Among them, 20-HETE appears to be a promising prognostic biomarker for ICU admission and a potential therapeutic target for severe COVID-19 disease. Our study thus underscores the significance of LM networks in COVID-19 pathophysiology and sheds light into the broader mechanisms driving viral pneumonia in humans. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=158 SRC="FIGDIR/small/610123v1_ufig1.gif" ALT="Figure 1"> View larger version (69K): org.highwire.dtl.DTLVardef@6e406dorg.highwire.dtl.DTLVardef@47c9deorg.highwire.dtl.DTLVardef@1162488org.highwire.dtl.DTLVardef@b86ba3_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

Mechanism of neurodegeneration mediated by clonal inflammatory microglia

Langerhans cell Histiocytosis (LCH) and Erdheim-Chester disease (ECD) are clonal myeloid disorders, associated with MAP-Kinase activating mutations and an increased risk of neurodegeneration. Surprisingly, we found pervasive PU.1+ microglia mutant clones across the brain of LCH and ECD patients with and without neurological symptoms, associated with microgliosis, reactive astrocytosis, and neuronal loss. The disease predominated in the grey nuclei of the rhombencephalon, a topography attributable to a local proliferative advantage of mutant microglia. Presence of clinical symptoms was associated with a longer evolution of the disease and a larger size of PU.1+ clones (p= 0.0003). Genetic lineage tracing of PU.1+ clones suggest a resident macrophage lineage or a bone marrow precursor origin depending on patients. Finally, a CSF1R-inhibitor depleted mutant microglia and limited neuronal loss in mice suggesting an alternative to MAPK inhibitors. These studies characterize a progressive neurodegenerative disease, caused by clonal proliferation of inflammatory microglia (CPIM), with a decade(s)-long preclinical stage of incipient disease that represent a therapeutic window for prevention of neuronal death.

immunology↗

A Genome-Wide Arrayed CRISPR Screen Reveals PLSCR1 as an Intrinsic Barrier to SARS-CoV-2 Entry

Interferons (IFNs) play a crucial role in the regulation and evolution of host-virus interactions. Here, we conducted a genome-wide arrayed CRISPR knockout screen in the presence and absence of IFN to identify human genes that influence SARS-CoV-2 infection. We then performed an integrated analysis of genes interacting with SARS-CoV-2, drawing from a selection of 67 large-scale studies, including our own. We identified 28 genes of high relevance in both human genetic studies of COVID-19 patients and functional genetic screens in cell culture, with many related to the IFN pathway. Among these was the IFN-stimulated gene PLSCR1. PLSCR1 did not require IFN induction to restrict SARS-CoV-2 and did not contribute to IFN signaling. Instead, PLSCR1 specifically restricted spike-mediated SARS-CoV-2 entry. The PLSCR1-mediated restriction was alleviated by TMPRSS2 over-expression, suggesting that PLSCR1 primarily restricts the endocytic entry route. In addition, recent SARS-CoV-2 variants have adapted to circumvent the PLSCR1 barrier via currently undetermined mechanisms. Finally, we investigate the functional effects of PLSCR1 variants present in humans and discuss an association between PLSCR1 and severe COVID-19 reported recently.

immunology↗

A microglia clonal inflammatory disorder in Alzheimer's Disease

Somatic genetic heterogeneity resulting from post-zygotic DNA mutations is widespread in human tissues and can cause diseases, however few studies have investigated its role in neurodegenerative processes such as Alzheimers Disease (AD). Here we report the selective enrichment of microglia clones carrying pathogenic variants, that are not present in neuronal, glia/stromal cells, or blood, from patients with AD in comparison to age-matched controls. Notably, microglia-specific AD-associated variants preferentially target the MAPK pathway, including recurrent CBL ring-domain mutations. These variants activate ERK and drive a microglia transcriptional program characterized by a strong neuro-inflammatory response, both in vitro and in patients. Although the natural history of AD-associated microglial clones is difficult to establish in human, microglial expression of a MAPK pathway activating variant was previously shown to cause neurodegeneration in mice, suggesting that AD-associated neuroinflammatory microglial clones may contribute to the neurodegenerative process in patients. One-Sentence SummaryA subset of Alzheimer Disease patients carry mutant microglia somatic clones which promote neuro-inflammation.

neuroscience↗

Environmental and genetic drivers of population differences in SARS-CoV-2 immune responses

Humans display vast clinical variability upon SARS-CoV-2 infection1-3, partly due to genetic and immunological factors4. However, the magnitude of population differences in immune responses to SARS-CoV-2 and the mechanisms underlying such variation remain unknown. Here we report single-cell RNA-sequencing data for peripheral blood mononuclear cells from 222 healthy donors of various ancestries stimulated with SARS-CoV-2 or influenza A virus. We show that SARS-CoV-2 induces a weaker, but more heterogeneous interferon-stimulated gene activity than influenza A virus, and a unique pro-inflammatory signature in myeloid cells. We observe marked population differences in transcriptional responses to viral exposure that reflect environmentally induced cellular heterogeneity, as illustrated by higher rates of cytomegalovirus infection, affecting lymphoid cells, in African-descent individuals. Expression quantitative trait loci and mediation analyses reveal a broad effect of cell proportions on population differences in immune responses, with genetic variants having a narrower but stronger effect on specific loci. Additionally, natural selection has increased immune response differentiation across populations, particularly for variants associated with SARS-CoV-2 responses in East Asians. We document the cellular and molecular mechanisms through which Neanderthal introgression has altered immune functions, such as its impact on the myeloid response in Europeans. Finally, colocalization analyses reveal an overlap between the genetic architecture of immune responses to SARS-CoV-2 and COVID-19 severity. Collectively, these findings suggest that adaptive evolution targeting immunity has also contributed to current disparities in COVID-19 risk.

genomics↗

Genetic adaptation to pathogens and increased risk of inflammatory disorders in post-Neolithic Europe

Ancient genomics can directly detect human genetic adaptation to environmental cues. However, it remains unclear how pathogens have exerted selective pressures on human genome diversity across different epochs and affected present-day inflammatory disease risk. Here, we use an ancestry-aware approximate Bayesian computation framework to estimate the nature, strength, and time of onset of selection acting on 2,879 ancient and modern European genomes from the last 10,000 years. We found that the bulk of genetic adaptation occurred after the start of the Bronze Age, <4,500 years ago, and was enriched in genes relating to host-pathogen interactions. Furthermore, we detected directional selection acting on specific leukocytic lineages and experimentally demonstrated that the strongest negatively selected immunity gene variant -- the lipopolysaccharide-binding protein gene (LBP) D283G -- is hypomorphic. Finally, our analyses suggest that the risk of inflammatory disorders has progressively increased in post-Neolithic Europeans, partly due to antagonistic pleiotropy following genetic adaptation to pathogens.

genetics↗

Genome-wide detection of human variants that disrupt intronic branchpoints

Pre-mRNA splicing is initiated with the recognition of a single-nucleotide intronic branchpoint (BP) within a BP motif by spliceosome elements. Fifty-six rare variants in 44 human genes have been reported to alter splicing and cause disease by disrupting BP. However, until now, no computational approach has been available to efficiently detect such variants in next-generation sequencing (NGS) data. We established a comprehensive human genome-wide BP database by integrating existing BP data, and by generating new BP data from RNA-seq of lariat debranching enzyme DBR1-mutated patients and from machine-learning predictions. We in-depth characterize multiple features of BP in major and minor introns, and find that BP and BP-2 (two-nucleotides upstream of BP) positions exhibit a lower rate of variation in human populations and higher evolutionary conservation than the intronic background, whilst being comparable to the exonic background. We develop BPHunter as a genome-wide computational approach to systematically and efficiently detect intronic variants that may disrupt BP recognition in NGS data. BPHunter retrospectively identifies 48 of the 56 known pathogenic BP mutations in which we summarize a strategy for prioritizing BP mutation candidates, and the remaining 8 all create AG dinucleotides between BP and acceptor site which is probably the reason for mis-splicing. We demonstrate the utility of BPHunter prospectively by using it to identify a novel germline heterozygous BP variant of STAT2 in a patient with critical COVID-19 pneumonia, and a novel somatic intronic 59-nucleotide deletion of ITPKB in a lymphoma patient, both of which we validate experimentally. BPHunter is publicly available from https://hgidsoft.rockefeller.edu/BPHunter and https://github.com/casanova-lab/BPHunter.

genetics↗

Autoantibody discovery across monogenic, acquired, and COVID19-associated autoimmunity with scalable PhIP-Seq

Phage Immunoprecipitation-Sequencing (PhIP-Seq) allows for unbiased, proteome-wide autoantibody discovery across a variety of disease settings, with identification of disease-specific autoantigens providing new insight into previously poorly understood forms of immune dysregulation. Despite several successful implementations of PhIP-Seq for autoantigen discovery, including our previous work (Vazquez et al. 2020), current protocols are inherently difficult to scale to accommodate large cohorts of cases and importantly, healthy controls. Here, we develop and validate a high throughput extension of PhIP-seq in various etiologies of autoimmune and inflammatory diseases, including APS1, IPEX, RAG1/2 deficiency, Kawasaki Disease (KD), Multisystem Inflammatory Syndrome in Children (MIS-C), and finally, mild and severe forms of COVID19. We demonstrate that these scaled datasets enable machine-learning approaches that result in robust prediction of disease status, as well as the ability to detect both known and novel autoantigens, such as PDYN in APS1 patients, and intestinally expressed proteins BEST4 and BTNL8 in IPEX patients. Remarkably, BEST4 antibodies were also found in 2 patients with RAG1/2 deficiency, one of whom had very early onset IBD. Scaled PhIP-Seq examination of both MIS-C and KD demonstrated rare, overlapping antigens, including CGNL1, as well as several strongly enriched putative pneumonia-associated antigens in severe COVID19, including the endosomal protein EEA1. Together, scaled PhIP-Seq provides a valuable tool for broadly assessing both rare and common autoantigen overlap between autoimmune diseases of varying origins and etiologies.

immunology↗

A monocyte/dendritic cell molecular signature of SARS-CoV2-related multisystem inflammatory syndrome in children (MIS-C) with severe myocarditis

SARS-CoV-2 infection in children is generally milder than in adults, yet a proportion of cases result in hyperinflammatory conditions often including myocarditis. To better understand these cases, we applied a multi-parametric approach to the study of blood cells of 56 children hospitalized with suspicion of SARS-CoV-2 infection. The most severe forms of MIS-C (multisystem inflammatory syndrome in children related to SARS-CoV-2), that resulted in myocarditis, were characterized by elevated levels of pro-angiogenesis cytokines and several chemokines. Single-cell transcriptomic analyses identified a unique monocyte/dendritic cell gene signature that correlated with the occurrence of severe myocarditis, characterized by sustained NF-{kappa}B activity, TNF- signaling, associated with decreased gene expression of NF-{kappa}B inhibitors. We also found a weak response to type-I and type-II interferons, hyperinflammation and response to oxidative stress related to increased HIF-1 and VEGF signaling. These results provide potential for a better understanding of disease pathophysiology.

immunology↗

Basal Expression of Interferon-Stimulated Genes Drives Population Differences in Monocyte Susceptibility to Influenza Infection

There is considerable inter-individual and inter-population variability in response to viruses. The potential of monocytes to elicit type-I interferon responses has attracted attention to their role in viral infections. Here, we use an ex vivo model to characterize the role of cellular heterogeneity in human variation of monocyte responses to influenza A virus (IAV) exposure. Using single-cell RNA-sequencing, we show widespread inter-individual variability in the percentage of IAV-infected monocytes. We show that cells escaping viral infection display increased mRNA expression of type-I interferon stimulated genes and decreased expression of ribosomal genes, relative to both infected cells and those never exposed to IAV. While this host defense strategy is shared between CD16+/CD16- monocytes, we also uncover CD16+-specific mRNA expression of IL6 and TNF in response to IAV, and a stronger resistance of CD16+ monocytes to IAV infection. Notably, individuals with high cellular susceptibility to IAV are characterized by a lower activation at basal state of an IRF/STAT-induced transcriptional network, which includes antiviral genes such as IFITM3, MX1, and OAS3. Finally, using flow cytometry and bulk RNA-sequencing across 200 individuals of African and European ancestry, we observe a higher number of CD16+ monocytes and lower susceptibility to IAV infection among monocytes from individuals of African-descent. Collectively, our results reveal the effects of IAV infection on the transcriptional landscape of human monocytes and highlight previously unappreciated differences in cellular susceptibility to IAV infection between individuals of African and European ancestry, which may account for the greater susceptibility of Africans to severe influenza. Significance StatementMonocytes may play a critical role during severe viral infections. Our study tackles how heterogeneity in monocyte subsets and activation contributes to shape individual differences in the transcriptional response to viral infections. Using single-cell RNA-sequencing, we reveal heterogeneity in monocyte susceptibility to IAV infection, both between CD16+/CD16- monocytes and across individuals, driven by differences in basal activation of an IRF/STAT-induced antiviral program. Furthermore, we show a decreased ability of IAV to infect and replicate in monocytes from African-ancestry individuals, with possible implications for antigen presentation and lymphocyte activation. These results highlight the importance of early cellular activation in determining an individuals innate immune response to viral infection.

genomics↗

Detection of homozygous and hemizygous partial exon deletions by whole-exome sequencing

The detection of copy number variations (CNVs) in whole-exome sequencing (WES) data is important, as CNVs may underlie a number of human genetic disorders. The recently developed HMZDelFinder algorithm can detect rare homozygous and hemizygous (HMZ) deletions in WES data more effectively than other widely used tools. Here, we present HMZDelFinder_opt, an approach that outperforms HMZDelFinder for the detection of HMZ deletions, including partial exon deletions in particular, in typical laboratory cohorts that are generated over time under different experimental conditions. We show that using an optimized reference control set of WES data, based on a PCA-derived Euclidean distance for coverage, strongly improves the detection of HMZ deletions both in real patients carrying validated disease-causing deletions and in simulated data. Furthermore, we develop a sliding window approach enabling HMZDelFinder-opt to identify HMZ partial deletions of exons that are otherwise undiscovered by HMZDelFinder. HMZDelFinder_opt is a timely and powerful approach for detecting HMZ deletions, particularly partial exon deletions, in laboratory cohorts, which are typically heterogeneous.

bioinformatics↗

Multi-batch cytometry data integration for optimal immunophenotyping

We describe the integration of multi-batch cytometry datasets (iMUBAC), a flexible, robust, and scalable computational framework for unsupervised cell-type identification across multiple batches of high-dimensional cytometry datasets. After overlaying cells from healthy controls across multiple batches, iMUBAC learns batch-specific cell-type classification boundaries and identifies aberrant immunophenotypes in patient samples. We illustrate unbiased and streamlined immunophenotyping, using both in-house and public mass and flow cytometry datasets.

bioinformatics↗

Controlling for Human Population Stratification in Rare Variant Association Studies

Population stratification is a strong confounding factor in human genetic association studies. In analyses of rare variants, the main correction strategies based on principal components (PC) and linear mixed models (LMM), may yield conflicting conclusions, due to both the specific type of structure induced by rare variants and the particular statistical features of association tests. Studies evaluating these approaches generally focused on specific situations with limited types of simulated structure and large sample sizes. We investigated the properties of several correction methods in the context of a large simulation study using real exome data, and several within- and between- continent stratification scenarios. We also considered different sample sizes, with situations including as few as 50 cases, to account for the analysis of rare disorders. In this context, we focused on a genetic model with a phenotype driven by rare deleterious variants well suited for a burden test. For analyses of large samples, we found that accounting for stratification was more difficult with a continental structure than with a worldwide structure. LMM failed to maintain a correct type I error in many scenarios, whereas PCs based on common variants failed only in the presence of extreme continental stratification. When a sample of 50 cases was considered, an inflation of type I errors was observed with PC for small numbers of controls ([&le;]100), and with LMM for large numbers of controls ([&ge;]1000). We also tested a promising novel adapted local permutation method (LocPerm), which maintained a correct type I error in all situations. All approaches capable of correcting for stratification properly had similar powers for detecting actual associations pointing out that the key issue is to properly control type I errors. Finally, we found that adding a large panel of external controls (e.g. extracted from publicly available databases) was an efficient way to increase the power of analyses including small numbers of cases, provided an appropriate stratification correction was used. Author SummaryGenetic association studies focusing on rare variants using next generation sequencing (NGS) data have become a common strategy to overcome the shortcomings of classical genome-wide association studies for the analysis of rare and common diseases. The issue of population stratification remains however a substantial question that has not been fully resolved when analyzing NGS data. In this work, we propose a comprehensive evaluation of the main strategies to account for stratification, that are principal components and linear mixed model, along with a novel approach based on local permutations (LocPerm). We compared these correction methods in many different settings, considering several types of population structures, sample sizes or types of variants. Our results highlighted important limitations of some classical methods as those using principal components (in particular in small samples) and linear mixed models (in several situations). In contrast, LocPerm maintained a correct type I error in all situations. Also, we showed that adding a large panel of external controls, e.g coming from publicly available databases, is an efficient strategy to increase the power of an analysis including a low number of cases, as long as an appropriate stratification correction is used. Our findings provide helpful guidelines for many researchers working on rare variant association studies.

genetics↗

Negative selection on human genes causing severe inborn errors depends on disease outcome and both the mode and mechanism of inheritance

BackgroundGenetic variants underlying severe diseases are less likely to be transmitted to the next generation, and are thus gradually and selectively eliminated from the population through negative selection. Here, we study the determinants of this evolutionary process in genes underlying severe diseases in humans. ResultsWe propose a novel approach, CoNeS, integrating known negative selection scores through principal component projection. We compare evidence for negative selection at 319 genes underlying inborn errors of immunity (IEI), which are life-threatening monogenic disorders. We find that genes underlying autosomal dominant (AD) or X-linked IEI are under stronger negative selection than those underlying autosomal recessive (AR) IEI, which are under no stronger selection than genes not known to be disease-causing. However, we find that genes with mutations causing AR IEI that are lethal before reproductive maturity and that display complete penetrance are under stronger negative selection than other genes underlying AR IEI. We also find that genes underlying AD IEI by haploinsufficiency are under stronger negative selection than other genes underlying AD IEI. Finally, we replicate these results in a study of 1,140 genes causing inborn errors of neurodevelopment. ConclusionsThese findings collectively show that the clinical outcomes of inborn errors, together with the mode and mechanism of inheritance of these errors, determine the strength of negative selection acting on severe disease-causing genes. These findings suggest that estimating the intensity of negative selection with CoNeS may facilitate the selection of candidate genes in patients suspected to carry an inborn error.

genetics↗