Phenotype characterisation of TBX4 mutation and deletion carriers with neonatal and paediatric pulmonary hypertension

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Abstract

Rare variants in the T-box transcription factor 4 gene ( TBX4) have recently been recognised as an emerging cause of paediatric pulmonary hypertension (PH). Their pathophysiology and contribution to persistent pulmonary hypertension in neonates (PPHN) are unknown. We sought to define the spectrum of clinical manifestations and histopathology associated with TBX4 variants in neonates and children with PH.

We assessed clinical data and lung tissue in 19 children with PH, including PPHN, carrying TBX4 rare variants identified by next-generation sequencing and copy number variation arrays.

Variants included six 17q23 deletions encompassing the entire TBX4 locus and neighbouring genes, and 12 likely damaging mutations. 10 infants presented with neonatal hypoxic respiratory failure and PPHN, and were subsequently discharged home. PH was diagnosed later in infancy or childhood. Three children died and two required lung transplantation. Associated anomalies included patent ductus arteriosus, septal defects, foot anomalies and developmental disability, the latter with a higher prevalence in deletion carriers. Histology in seven infants showed abnormal distal lung development and pulmonary hypertensive remodelling.

TBX4 mutations and 17q23 deletions underlie a new form of developmental lung disease manifesting with severe, often biphasic PH at birth and/or later in infancy and childhood, often associated with skeletal anomalies, cardiac defects, neurodevelopmental disability and other anomalies.

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Sue Richards, Nazneen Aziz, Sherri Bale … (2015)

The American College of Medical Genetics and Genomics (ACMG) previously developed guidance for the interpretation of sequence variants. 1 In the past decade, sequencing technology has evolved rapidly with the advent of high-throughput next generation sequencing. By adopting and leveraging next generation sequencing, clinical laboratories are now performing an ever increasing catalogue of genetic testing spanning genotyping, single genes, gene panels, exomes, genomes, transcriptomes and epigenetic assays for genetic disorders. By virtue of increased complexity, this paradigm shift in genetic testing has been accompanied by new challenges in sequence interpretation. In this context, the ACMG convened a workgroup in 2013 comprised of representatives from the ACMG, the Association for Molecular Pathology (AMP) and the College of American Pathologists (CAP) to revisit and revise the standards and guidelines for the interpretation of sequence variants. The group consisted of clinical laboratory directors and clinicians. This report represents expert opinion of the workgroup with input from ACMG, AMP and CAP stakeholders. These recommendations primarily apply to the breadth of genetic tests used in clinical laboratories including genotyping, single genes, panels, exomes and genomes. This report recommends the use of specific standard terminology: ‘pathogenic’, ‘likely pathogenic’, ‘uncertain significance’, ‘likely benign’, and ‘benign’ to describe variants identified in Mendelian disorders. Moreover, this recommendation describes a process for classification of variants into these five categories based on criteria using typical types of variant evidence (e.g. population data, computational data, functional data, segregation data, etc.). Because of the increased complexity of analysis and interpretation of clinical genetic testing described in this report, the ACMG strongly recommends that clinical molecular genetic testing should be performed in a CLIA-approved laboratory with results interpreted by a board-certified clinical molecular geneticist or molecular genetic pathologist or equivalent.

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Summary Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. We describe the aggregation and analysis of high-quality exome (protein-coding region) sequence data for 60,706 individuals of diverse ethnicities generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of truncating variants with 72% having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human “knockout” variants in protein-coding genes.

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A general framework for estimating the relative pathogenicity of human genetic variants

Martin Kircher, Daniela M. Witten, Preti Jain … (2014)

Our capacity to sequence human genomes has exceeded our ability to interpret genetic variation. Current genomic annotations tend to exploit a single information type (e.g. conservation) and/or are restricted in scope (e.g. to missense changes). Here, we describe Combined Annotation Dependent Depletion (CADD), a framework that objectively integrates many diverse annotations into a single, quantitative score. We implement CADD as a support vector machine trained to differentiate 14.7 million high-frequency human derived alleles from 14.7 million simulated variants. We pre-compute “C-scores” for all 8.6 billion possible human single nucleotide variants and enable scoring of short insertions/deletions. C-scores correlate with allelic diversity, annotations of functionality, pathogenicity, disease severity, experimentally measured regulatory effects, and complex trait associations, and highly rank known pathogenic variants within individual genomes. The ability of CADD to prioritize functional, deleterious, and pathogenic variants across many functional categories, effect sizes and genetic architectures is unmatched by any current annotation.