Project description:The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management.
Project description:Testicular germ cell tumour (TGCT) is the most common cancer in young men. Here we sought to identify risk factors for TGCT by performing whole-exome sequencing on 328 TGCT cases from 153 families, 634 sporadic TGCT cases and 1,644 controls. We search for genes that are recurrently affected by rare variants (minor allele frequency <0.01) with potentially damaging effects and evidence of segregation in families. A total of 8.7% of TGCT families carry rare disruptive mutations in the cilia-microtubule genes (CMG) as compared with 0.5% of controls (P=2.1 × 10-8). The most significantly mutated CMG is DNAAF1 with biallelic inactivation and loss of DNAAF1 expression shown in tumours from carriers. DNAAF1 mutation as a cause of TGCT is supported by a dnaaf1hu255h(+/-) zebrafish model, which has a 94% risk of TGCT. Our data implicate cilia-microtubule inactivation as a cause of TGCT and provide evidence for CMGs as cancer susceptibility genes.
Project description:Host genetic factors have been shown to play an important role in SARS-CoV-2 infection and the course of Covid-19 disease. The genetic contributions of common variants influencing Covid-19 susceptibility and severity have been extensively studied in diverse populations. However, the studies of rare genetic defects arising from inborn errors of immunity (IEI) are relatively few, especially in the Chinese population. To fill this gap, we used a deeply sequenced dataset of nearly 500 patients, all of Chinese descent, to investigate putative functional rare variants. Specifically, we annotated rare variants in our call set and selected likely deleterious missense (LDM) and high-confidence predicted loss-of-function (HC-pLoF) variants. Further, we analyzed LDM and HC-pLoF variants between non-severe and severe Covid-19 patients by (a) performing gene- and pathway-level association analyses, (b) testing the number of mutations in previously reported genes mapped from LDM and HC-pLoF variants, and (c) uncovering candidate genes via protein-protein interaction (PPI) network analysis of Covid-19-related genes and genes defined from LDM and HC-pLoF variants. From our analyses, we found that (a) pathways Tuberculosis (hsa:05152), Primary Immunodeficiency (hsa:05340), and Influenza A (hsa:05164) showed significant enrichment in severe patients compared to the non-severe ones, (b) HC-pLoF mutations were enriched in Covid-19-related genes in severe patients, and (c) several candidate genes, such as IL12RB1, TBK1, TLR3, and IFNGR2, are uncovered by PPI network analysis and worth further investigation. These regions generally play an essential role in regulating antiviral innate immunity responses to foreign pathogens and in responding to many inflammatory diseases. We believe that our identified candidate genes/pathways can be potentially used as Covid-19 diagnostic markers and help distinguish patients at higher risk.
Project description:We have performed whole-genome sequencing to identify the genetic variants potentially contributing to the early-onset semantic dementia phenotype in a patient with family history of dementia and episodic memory deficit accompanied with profound semantic loss. Only very rare variants of unknown significance (VUS) have been identified: a nonsense variant c.366C>A/p.Cys122* in plasminogen activator, urokinase (PLAU) and a missense variant c.944C>T/p.Thr315Met in β-site APP-cleaving enzyme 1 (BACE1)-along with known disease-modifying variants of moderate penetrance. Patient-derived fibroblasts showed reduced PLAU and elevated BACE1 mRNA and protein levels compared to control fibroblasts. Successful rescue of PLAU mRNA levels by nonsense-mediated mRNA decay (NMD) inhibitor (puromycin) confirmed NMD as the underlying mechanism. This is the first report of the PLAU variant with the confirmed haploinsufficiency, associated with semantic dementia phenotype. Our results suggest that rare variants in the PLAU and BACE1 genes should be considered in future studies on early-onset dementias.
Project description:Testicular germ cell tumor (TGCT) is the most common cancer in young men1,2. Here we aimed to identify novel risk factors for TGCT using whole-exome sequencing, which was performed on 328 affected individuals from 153 families, 634 sporadic cases and 1,644 controls. We searched for genes that were recurrently affected by rare variants (minor allele frequency <0.01) with potentially damaging effects and evidence of segregation in families. 8.7% of families carried rare disruptive mutations in the cilia-microtubule genes (CMG) as compared to 0.5% of controls3 (P=2.1x10-8). The most significantly mutated CMG was DNAAF1 with biallelic inactivation and loss of DNAAF1 expression shown in tumors from carriers. DNAAF1 as a cause of TGCT was supported by a DNAAF1Hu255h(+/-) zebrafish model with 94% penetrance for TGCT compared to 14% in wildtype fish. These data implicate cilia-microtubule inactivation as a cause of TGCT development and are the first evidence for CMGs as cancer susceptibility genes.
Project description:The 3p21.31 locus, which locus contains a chemokine receptor (CKR) cluster, is the most robust genomic region associated with COVID-19 severity. We tested expression quantitative trait loci (eQTL) targeting the 3p21.31 CKR cluster linked to COVID-19 hospitalization in Europeans from the COVID-19 HGI meta-analysis. Among these, CCRL2, a key regulator of neutrophil trafficking, was targeted by neutrophil-restricted eQTLs. We confirmed these eQTLs in an Italian COVID-19 cohort. Haplotype analysis revealed a link between an increased CCRL2 expression and COVID-19 severity and hospitalization. By the exposure of neutrophils to a TLR8 ligand, reflecting a viral infection, we revealed specific chromatin domains within the 3p21.31 locus exclusive to neutrophils. In addition, the identified variants mapped within these regions altered the binding motif of neutrophils expressed transcription factors. These results support that CCRL2 eQTL variants contribute to the risk of severe COVID-19 by selectively affecting neutrophil’s function
Project description:How variants with different frequencies contribute to trait variation is a central question in genetics. We use a unique model system to disentangle the contributions of common and rare variants to quantitative traits. We generated ~14,000 progeny from crosses among 16 diverse yeast strains and identified thousands of quantitative trait loci (QTLs) for 38 traits. We combined our results with sequencing data for 1011 yeast isolates to show that rare variants make a disproportionate contribution to trait variation. Evolutionary analyses revealed that this contribution is driven by rare variants that arose recently, and that negative selection has shaped the relationship between variant frequency and effect size. We leveraged the structure of the crosses to resolve hundreds of QTLs to single genes. These results refine our understanding of trait variation at the population level and suggest that studies of rare variants are a fertile ground for discovery of genetic effects.
Project description:Infection with SARS-CoV-2 has highly variable clinical manifestations, ranging from asymptomatic infection through to life-threatening disease. Host whole blood transcriptomics can offer unique insights into the biological processes underpinning infection and disease, as well as severity. We performed whole blood RNA-Sequencing of individuals with varying degrees of COVID-19 severity. We used differential expression analysis and pathway enrichment analysis to explore how the blood transcriptome differs between individuals with mild, moderate, and severe COVID-19, performing pairwise comparisons between groups.
Project description:Understanding how human leukocyte antigen (HLA) polymorphism affects both the susceptibility and severity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection will help to identify individuals at higher risk to better manage and prioritize vaccination at the clinical level and explain the differences in epidemic trends in different regions at the epidemiological level. This study compared the frequencies of HLA class I alleles (HLA-A, B) in 214 coronavirus disease 2019 (COVID-19) patients with different disease severity and 35 healthy controls and analyzed the correlations between specific HLA alleles and disease severity and T cell memory. The results showed no significant difference in HLA allele frequencies between COVID-19 patients and healthy controls (P > 0.05). The allele HLA-B*13:02 was significantly correlated with the disease severity of COVID-19 patients (P = 0.006). After adjustment for age and disease severity, the T cell responses of COVID-19 convalescents with the allele HLA-B*40:01 may be lower at six months (P = 0.044) and 12 months (P = 0.069). Moreover, these results may be due to their rare peptide anchors by analyzing the binding peptide motifs of these HLA alleles. The study may be valuable for investigating the potential association of specific HLA alleles with SARS-CoV-2 infection.
Project description:ObjectiveHeightened inflammation, dysregulated immunity, and thrombotic events are characteristic of hospitalized COVID-19 patients. Given that platelets are key regulators of thrombosis, inflammation, and immunity they represent prime candidates as mediators of COVID-19-associated pathogenesis. The objective of this study was to understand the contribution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to the platelet phenotype via phenotypic (activation, aggregation) and transcriptomic characterization.Approach and resultsIn a cohort of 3915 hospitalized COVID-19 patients, we analyzed blood platelet indices collected at hospital admission. Following adjustment for demographics, clinical risk factors, medication, and biomarkers of inflammation and thrombosis, we find platelet count, size, and immaturity are associated with increased critical illness and all-cause mortality. Bone marrow, lung tissue, and blood from COVID-19 patients revealed the presence of SARS-CoV-2 virions in megakaryocytes and platelets. Characterization of COVID-19 platelets found them to be hyperreactive (increased aggregation, and expression of P-selectin and CD40) and to have a distinct transcriptomic profile characteristic of prothrombotic large and immature platelets. In vitro mechanistic studies highlight that the interaction of SARS-CoV-2 with megakaryocytes alters the platelet transcriptome, and its effects are distinct from the coronavirus responsible for the common cold (CoV-OC43).ConclusionsPlatelet count, size, and maturity associate with increased critical illness and all-cause mortality among hospitalized COVID-19 patients. Profiling tissues and blood from COVID-19 patients revealed that SARS-CoV-2 virions enter megakaryocytes and platelets and associate with alterations to the platelet transcriptome and activation profile.