Prenatal exome sequencing analysis in fetal structural anomalies detected by ultrasonography (PAGE): a cohort study

Background: Fetal structural anomalies, which are detected by ultrasonography, have a range of genetic causes, including chromosomal aneuploidy, copy number variations (CNVs; which are detectable by chromosomal microarrays), and pathogenic sequence variants in developmental genes. Testing for aneuploidy and CNVs is routine during the investigation of fetal structural anomalies, but there is little information on the clinical usefulness of genome-wide next-generation sequencing in the prenatal setting. We therefore aimed to evaluate the proportion of fetuses with structural abnormalities that had identifiable variants in genes associated with developmental disorders when assessed with whole-exome sequencing (WES). Methods: In this prospective cohort study, two groups in Birmingham and London recruited patients from 34 fetal medicine units in England and Scotland. We used whole-exome sequencing (WES) to evaluate the presence of genetic variants in developmental disorder genes (diagnostic genetic variants) in a cohort of fetuses with structural anomalies and samples from their parents, after exclusion of aneuploidy and large CNVs. Women were eligible for inclusion if they were undergoing invasive testing for identified nuchal translucency or structural anomalies in their fetus, as detected by ultrasound after 11 weeks of gestation. The partners of these women also had to consent to participate. Sequencing results were interpreted with a targeted virtual gene panel for developmental disorders that comprised 1628 genes. Genetic results related to fetal structural anomaly phenotypes were then validated and reported postnatally. The primary endpoint, which was assessed in all fetuses, was the detection of diagnostic genetic variants considered to have caused the fetal developmental anomaly. Findings: The cohort was recruited between Oct 22, 2014, and June 29, 2017, and clinical data were collected until March 31, 2018. After exclusion of fetuses with aneuploidy and CNVs, 610 fetuses with structural anomalies and 1202 matched parental samples (analysed as 596 fetus-parental trios, including two sets of twins, and 14 fetus-parent dyads) were analysed by WES. After bioinformatic filtering and prioritisation according to allele frequency and effect on protein and inheritance pattern, 321 genetic variants (representing 255 potential diagnoses) were selected as potentially pathogenic genetic variants (diagnostic genetic variants), and these variants were reviewed by a multidisciplinary clinical review panel. A diagnostic genetic variant was identified in 52 (8·5%; 95% CI 6·4–11·0) of 610 fetuses assessed and an additional 24 (3·9%) fetuses had a variant of uncertain significance that had potential clinical usefulness. Detection of diagnostic genetic variants enabled us to distinguish between syndromic and non-syndromic fetal anomalies (eg, congenital heart disease only vs a syndrome with congenital heart disease and learning disability). Diagnostic genetic variants were present in 22 (15·4%) of 143 fetuses with multisystem anomalies (ie, more than one fetal structural anomaly), nine (11·1%) of 81 fetuses with cardiac anomalies, and ten (15·4%) of 65 fetuses with skeletal anomalies; these phenotypes were most commonly associated with diagnostic variants. However, diagnostic genetic variants were least common in fetuses with isolated increased nuchal translucency (≥4·0 mm) in the first trimester (in three [3·2%] of 93 fetuses). Interpretation: WES facilitates genetic diagnosis of fetal structural anomalies, which enables more accurate predictions of fetal prognosis and risk of recurrence in future pregnancies. However, the overall detection of diagnostic genetic variants in a prospectively ascertained cohort with a broad range of fetal structural anomalies is lower than that suggested by previous smaller-scale studies of fewer phenotypes. WES improved the identification of genetic disorders in fetuses with structural abnormalities; however, before clinical implementation, careful consideration should be given to case selection to maximise clinical usefulness.The PAGE study is supported by a Health Innovation Challenge from the UK Department of Health and Wellcome Trust (no. HICF-R7-396). Additionally, LSC is partially funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at Great Ormond Street Hospital and ERM acknowledges support from NIHR Cambridge Biomedical Research Centre (an NIHR Senior Investigator Award). The University of Cambridge has received salary support with regard to ERM from the UK National Health Service (NHS) in the east of England through the Clinical Academic Reserve

Detecting cryptic clinically relevant structural variation in exome-sequencing data increases diagnostic yield for developmental disorders.

Structural variation (SV) describes a broad class of genetic variation greater than 50 bp in size. SVs can cause a wide range of genetic diseases and are prevalent in rare developmental disorders (DDs). Individuals presenting with DDs are often referred for diagnostic testing with chromosomal microarrays (CMAs) to identify large copy-number variants (CNVs) and/or with single-gene, gene-panel, or exome sequencing (ES) to identify single-nucleotide variants, small insertions/deletions, and CNVs. However, individuals with pathogenic SVs undetectable by conventional analysis often remain undiagnosed. Consequently, we have developed the tool InDelible, which interrogates short-read sequencing data for split-read clusters characteristic of SV breakpoints. We applied InDelible to 13,438 probands with severe DDs recruited as part of the Deciphering Developmental Disorders (DDD) study and discovered 63 rare, damaging variants in genes previously associated with DDs missed by standard SNV, indel, or CNV discovery approaches. Clinical review of these 63 variants determined that about half (30/63) were plausibly pathogenic. InDelible was particularly effective at ascertaining variants between 21 and 500 bp in size and increased the total number of potentially pathogenic variants identified by DDD in this size range by 42.9%. Of particular interest were seven confirmed de novo variants in MECP2, which represent 35.0% of all de novo protein-truncating variants in MECP2 among DDD study participants. InDelible provides a framework for the discovery of pathogenic SVs that are most likely missed by standard analytical workflows and has the potential to improve the diagnostic yield of ES across a broad range of genetic diseases

Contribution of retrotransposition to developmental disorders.

Mobile genetic Elements (MEs) are segments of DNA which can copy themselves and other transcribed sequences through the process of retrotransposition (RT). In humans several disorders have been attributed to RT, but the role of RT in severe developmental disorders (DD) has not yet been explored. Here we identify RT-derived events in 9738 exome sequenced trios with DD-affected probands. We ascertain 9 de novo MEs, 4 of which are likely causative of the patient's symptoms (0.04%), as well as 2 de novo gene retroduplications. Beyond identifying likely diagnostic RT events, we estimate genome-wide germline ME mutation rate and selective constraint and demonstrate that coding RT events have signatures of purifying selection equivalent to those of truncating mutations. Overall, our analysis represents a comprehensive interrogation of the impact of retrotransposition on protein coding genes and a framework for future evolutionary and disease studies

Genomic and Genic Deletions of the FOX Gene Cluster on 16q24.1 and Inactivating Mutations of FOXF1 Cause Alveolar Capillary Dysplasia and Other Malformations

Alveolar capillary dysplasia with misalignment of pulmonary veins (ACD/MPV) is a rare, neonatally lethal developmental disorder of the lung with defining histologic abnormalities typically associated with multiple congenital anomalies (MCA). Using array CGH analysis, we have identified six overlapping microdeletions encompassing the FOX transcription factor gene cluster in chromosome 16q24.1q24.2 in patients with ACD/MPV and MCA. Subsequently, we have identified four different heterozygous mutations (frameshift, nonsense, and no-stop) in the candidate FOXF1 gene in unrelated patients with sporadic ACD/MPV and MCA. Custom-designed, high-resolution microarray analysis of additional ACD/MPV samples revealed one microdeletion harboring FOXF1 and two distinct microdeletions upstream of FOXF1, implicating a position effect. DNA sequence analysis revealed that in six of nine deletions, both breakpoints occurred in the portions of Alu elements showing eight to 43 base pairs of perfect microhomology, suggesting replication error Microhomology-Mediated Break-Induced Replication (MMBIR)/Fork Stalling and Template Switching (FoSTeS) as a mechanism of their formation. In contrast to the association of point mutations in FOXF1 with bowel malrotation, microdeletions of FOXF1 were associated with hypoplastic left heart syndrome and gastrointestinal atresias, probably due to haploinsufficiency for the neighboring FOXC2 and FOXL1 genes. These differences reveal the phenotypic consequences of gene alterations in cis

A spatially resolved atlas of the human lung characterizes a gland-associated immune niche

Single-cell transcriptomics has allowed unprecedented resolution of cell types/states in the human lung, but their spatial context is less well defined. To (re)define tissue architecture of lung and airways, we profiled five proximal-to-distal locations of healthy human lungs in depth using multi-omic single cell/nuclei and spatial transcriptomics (queryable at lungcellatlas.org ). Using computational data integration and analysis, we extend beyond the suspension cell paradigm and discover macro and micro-anatomical tissue compartments including previously unannotated cell types in the epithelial, vascular, stromal and nerve bundle micro-environments. We identify and implicate peribronchial fibroblasts in lung disease. Importantly, we discover and validate a survival niche for IgA plasma cells in the airway submucosal glands (SMG). We show that gland epithelial cells recruit B cells and IgA plasma cells, and promote longevity and antibody secretion locally through expression of CCL28, APRIL and IL-6. This new 'gland-associated immune niche' has implications for respiratory health

COVID-19 progression and convalescence in common variable immunodeficiency patients shows incomplete adaptive responses and persistent inflammasome activation

Patients with common variable immunodeficiency (CVID), the most prevalent symptomatic primary immunodeficiency, are characterized by hypogammaglobulinemia, poorly protective vaccine titers and increased susceptibility to infections. New pathogens such as the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), might constitute a particular threat to these immunocompromised patients since many of them experience a slower recovery and do not achieve full response to SARS-CoV-2 vaccines. To define the molecular basis of the altered immune responses caused by SARS-CoV-2 infection in CVID patients, we generated longitudinal single-cell datasets of peripheral blood immune cells along viral infection and recovery. We sampled the same individuals before, during and after SARS-CoV-2 infection to model their specific immune response dynamics while removing donor variability. We observed that COVID-19 CVID patients show defective canonical NF-κB pathway activation and dysregulated expression of BCR-related genes in naïve B cells, as well as enhanced cytotoxic activity but incomplete cytokine response in NK and T cells. Moreover, monocytes from COVID-19 CVID patients show persistent activation of several inflammasome-related genes, including the pyrin and NLRC4 inflammasomes. Our results shed light on the molecular basis of the prolonged clinical manifestations observed in these immunodeficient patients upon SARS-CoV-2 infection, which might illuminate the development of tailored treatments for COVID-19 CVID patients.We thank the CERCA Program/Generalitat de Catalunya and the Josep Carreras Foundation for institutional support. This publication is part of the Human Cell Atlas: www.humancellatlas.org/publications. This study was funded by ”la Caixa” Foundation under the grant agreement LCF/PR/HR22/52420002, Spanish Ministry of Science and Innovation (grant number PID2020-117212RB-I00/AEI/10.13038/501100011033) (E.B.), by the Wellcome Trust Grant 206194 and 108413/A/15/D (R.V.-T.), Instituto de Salud Carlos III (ISCIII), Ref. AC18/00057, associated with i-PAD project (ERARE European Union program) (E.B.), and the Chan Zuckerberg Initiative (grant 2020-216799) (R.V.-T. and E.B.). This publication has also been supported by the Unstoppable campaign of the Josep Carreras Leukaemia Foundation. We are indebted to the donors for participating in this research.N

Making new genetic diagnoses with old data:iterative reanalysis and reporting from genome-wide data in 1,133 families with developmental disorders

Purpose Given the rapid pace of discovery in rare disease genomics, it is likely that improvements in diagnostic yield can be made by systematically reanalyzing previously generated genomic sequence data in light of new knowledge. Methods We tested this hypothesis in the United Kingdom–wide Deciphering Developmental Disorders study, where in 2014 we reported a diagnostic yield of 27% through whole-exome sequencing of 1,133 children with severe developmental disorders and their parents. We reanalyzed existing data using improved variant calling methodologies, novel variant detection algorithms, updated variant annotation, evidence-based filtering strategies, and newly discovered disease-associated genes. Results We are now able to diagnose an additional 182 individuals, taking our overall diagnostic yield to 454/1,133 (40%), and another 43 (4%) have a finding of uncertain clinical significance. The majority of these new diagnoses are due to novel developmental disorder–associated genes discovered since our original publication. Conclusion This study highlights the importance of coupling large-scale research with clinical practice, and of discussing the possibility of iterative reanalysis and recontact with patients and health professionals at an early stage. We estimate that implementing parent–offspring whole-exome sequencing as a first-line diagnostic test for developmental disorders would diagnose >50% of patients.</p

Single cell derived mRNA signals across human kidney tumors.

Funder: Department of HealthTumor cells may share some patterns of gene expression with their cell of origin, providing clues into the differentiation state and origin of cancer. Here, we study the differentiation state and cellular origin of 1300 childhood and adult kidney tumors. Using single cell mRNA reference maps of normal tissues, we quantify reference "cellular signals" in each tumor. Quantifying global differentiation, we find that childhood tumors exhibit fetal cellular signals, replacing the presumption of "fetalness" with a quantitative measure of immaturity. By contrast, in adult cancers our assessment refutes the suggestion of dedifferentiation towards a fetal state in most cases. We find an intimate connection between developmental mesenchymal populations and childhood renal tumors. We demonstrate the diagnostic potential of our approach with a case study of a cryptic renal tumor. Our findings provide a cellular definition of human renal tumors through an approach that is broadly applicable to human cancer

Single-cell multi-omics analysis of the immune response in COVID-19

Peer reviewedPublisher PD

Discovery of four recessive developmental disorders using probabilistic genotype and phenotype matching among 4,125 families.

Discovery of most autosomal recessive disease-associated genes has involved analysis of large, often consanguineous multiplex families or small cohorts of unrelated individuals with a well-defined clinical condition. Discovery of new dominant causes of rare, genetically heterogeneous developmental disorders has been revolutionized by exome analysis of large cohorts of phenotypically diverse parent-offspring trios. Here we analyzed 4,125 families with diverse, rare and genetically heterogeneous developmental disorders and identified four new autosomal recessive disorders. These four disorders were identified by integrating Mendelian filtering (selecting probands with rare, biallelic and putatively damaging variants in the same gene) with statistical assessments of (i) the likelihood of sampling the observed genotypes from the general population and (ii) the phenotypic similarity of patients with recessive variants in the same candidate gene. This new paradigm promises to catalyze the discovery of novel recessive disorders, especially those with less consistent or nonspecific clinical presentations and those caused predominantly by compound heterozygous genotypes