A Survey of Compound Heterozygous Variants in Pediatric Cancers and Structural Birth Defects

Investigation of Recessive Effects of Coding Variants on Common Clinical Phenotypes in Exome-Sequenced UK Biobank Participants

INTRODUCTION

Previous studies have demonstrated effects of rare coding variants on common, clinically relevant phenotypes although the additive burden of these variants makes only a small contribution to overall trait variance. Although recessive effects of individual homozygous variants have been studied, little work has been done to elucidate the impact of rare coding variants occurring together as compound heterozygotes.

METHODS

In this study, attempts were made to identify pairs of variants likely to be occurring as compound heterozygotes using 200,000 exome-sequenced subjects from the UK Biobank. Pairs of variants, which were seen together in the same subject more often than would be expected by chance, were excluded as it was assumed that these might be present in the same haplotype. Attention was restricted to variants with minor allele frequency ≤0.05 and to those predicted to alter amino acid sequence or prevent normal gene expression. For each gene, compound heterozygotes were assigned scores based on the rarity and predicted functional consequences of the constituent variants and the scores were used in a logistic regression analysis to test for association with hypertension, hyperlipidaemia, and type 2 diabetes.

RESULTS

No statistically significant associations were observed and the results conformed to the distribution, which would be expected under the null hypothesis. The average number of apparently compound heterozygous subjects for each gene was only 282.2.

CONCLUSION

It seems difficult to detect an effect of compound heterozygotes on the risk of these phenotypes. Even if recessive effects from compound heterozygotes do occur, they would only affect a small number of people and overall would not make a substantial contribution to phenotypic variance. This research has been conducted using the UK Biobank Resource.

Using existing pediatric cancer data from the Gabriella Miller Kids First Data Resource Program

Childhood cancer and birth defects are leading causes of childhood mortality, and studies suggest that birth defects increase pediatric cancer risk. The Gabriella Miller Kids First Pediatric Research Program (Kids First) seeks to alleviate these conditions by building an expansive resource of genetic and clinical data from patients with pediatric cancer and birth defects and their families. This article describes the data and support provided by the Kids First Data Resource Center and the Kids First Data Resource Center Data Resource Portal, which enables the public to review Kids First studies and request access to individual data. The Kids First Portal contains data from more than 34 000 participants and connects with CAVATICA (Seven Bridges Genomics, Inc, now part of Velsera), a cloud-based analysis and sharing platform. Researchers have used Kids First data to investigate a variety of cancers and further funding opportunities are available. The Kids First Portal is a unique resource that unites pediatric cancer and birth defects to uncover their genetic etiology and improve patients' lives.

Genomics in the long-read sequencing era

Long-read sequencing (LRS) technologies have provided extremely powerful tools to explore genomes. While in the early years these methods suffered technical limitations, they have recently made significant progress in terms of read length, throughput, and accuracy and bioinformatics tools have strongly improved. Here, we aim to review the current status of LRS technologies, the development of novel methods, and the impact on genomics research. We will explore the most impactful recent findings made possible by these technologies focusing on high-resolution sequencing of genomes and transcriptomes and the direct detection of DNA and RNA modifications. We will also discuss how LRS methods promise a more comprehensive understanding of human genetic variation, transcriptomics, and epigenetics for the coming years.

Accurate rare variant phasing of whole-genome and whole-exome sequencing data in the UK Biobank

Phasing involves distinguishing the two parentally inherited copies of each chromosome into haplotypes. Here, we introduce SHAPEIT5, a new phasing method that quickly and accurately processes large sequencing datasets and applied it to UK Biobank (UKB) whole-genome and whole-exome sequencing data. We demonstrate that SHAPEIT5 phases rare variants with low switch error rates of below 5% for variants present in just 1 sample out of 100,000. Furthermore, we outline a method for phasing singletons, which, although less precise, constitutes an important step towards future developments. We then demonstrate that the use of UKB as a reference panel improves the accuracy of genotype imputation, which is even more pronounced when phased with SHAPEIT5 compared with other methods. Finally, we screen the UKB data for loss-of-function compound heterozygous events and identify 549 genes where both gene copies are knocked out. These genes complement current knowledge of gene essentiality in the human genome.

Polygenic risk scores of endo-phenotypes identify the effect of genetic background in congenital heart disease

Congenital heart disease (CHD) is a rare structural defect that occurs in ∼1% of live births. Studies on CHD genetic architecture have identified pathogenic single-gene mutations in less than 30% of cases. Single-gene mutations often show incomplete penetrance and variable expressivity. Therefore, we hypothesize that genetic background may play a role in modulating disease expression. Polygenic risk scores (PRSs) aggregate effects of common genetic variants to investigate whether, cumulatively, these variants are associated with disease penetrance or severity. However, the major limitations in this field have been in generating sufficient sample sizes for these studies. Here we used CHD-phenotype matched genome-wide association study (GWAS) summary statistics from the UK Biobank (UKBB) as our base study and whole-genome sequencing data from the CHD cohort (n₁ = 711 trios, n₂ = 362 European trios) of the Gabriella Miller Kids First dataset as our target study to develop PRSs for CHD. PRSs estimated using a GWAS for heart valve problems and heart murmur explain 2.5% of the variance in case-control status of CHD (all SNVs, p = 7.90 × 10^-3; fetal cardiac SNVs, p = 8.00 × 10^-3) and 1.8% of the variance in severity of CHD (fetal cardiac SNVs, p = 6.20 × 10^-3; all SNVs, p = 0.015). These results show that common variants captured in CHD phenotype-matched GWASs have a modest but significant contribution to phenotypic expression of CHD. Further exploration of the cumulative effect of common variants is necessary for understanding the complex genetic etiology of CHD and other rare diseases.

Computational methods to assist in the discovery of pharmacological chaperones for rare diseases

Pharmacological chaperones are chemical compounds able to bind proteins and stabilize them against denaturation and following degradation. Some pharmacological chaperones have been approved, or are under investigation, for the treatment of rare inborn errors of metabolism, caused by genetic mutations that often can destabilize the structure of the wild-type proteins expressed by that gene. Given that, for rare diseases, there is a general lack of pharmacological treatments, many expectations are poured out on this type of compounds. However, their discovery is not straightforward. In this review, we would like to focus on the computational methods that can assist and accelerate the search for these compounds, showing also examples in which these methods were successfully applied for the discovery of promising molecules belonging to this new category of pharmacologically active compounds.

Clinical Phenotypes and Outcomes in Monogenic Versus Non-monogenic Very Early Onset Inflammatory Bowel Disease

BACKGROUND AND AIMS

Over 80 monogenic causes of very early onset inflammatory bowel disease [VEOIBD] have been identified. Prior reports of the natural history of VEOIBD have not considered monogenic disease status. The objective of this study is to describe clinical phenotypes and outcomes in a large single-centre cohort of patients with VEOIBD and universal access to whole exome sequencing [WES].

METHODS

Patients receiving IBD care at a single centre were prospectively enrolled in a longitudinal data repository starting in 2012. WES was offered with enrollment. Enrolled patients were filtered by age of diagnosis <6 years to comprise a VEOIBD cohort. Monogenic disease was identified by filtering proband variants for rare, loss-of-function, or missense variants in known VEOIBD genes inherited according to standard Mendelian inheritance patterns.

RESULTS

This analysis included 216 VEOIBD patients, followed for a median of 5.8 years. Seventeen patients [7.9%] had monogenic disease. Patients with monogenic IBD were younger at diagnosis and were more likely to have Crohn's disease phenotype with higher rates of stricturing and penetrating disease and extraintestinal manifestations. Patients with monogenic disease were also more likely to experience outcomes of intensive care unit [ICU] hospitalisation, gastrostomy tube, total parenteral nutrition use, stunting at 3-year follow-up, haematopoietic stem cell transplant, and death. A total of 41 patients [19.0%] had infantile-onset disease. After controlling for monogenic disease, patients with infantile-onset IBD did not have increased risk for most severity outcomes.

CONCLUSIONS

Monogenic disease is an important driver of disease severity in VEOIBD. WES is a valuable tool in prognostication and management of VEOIBD.

trioPhaser: using Mendelian inheritance logic to improve genomic phasing of trios

BACKGROUND

When analyzing DNA sequence data of an individual, knowing which nucleotide was inherited from each parent can be beneficial when trying to identify certain types of DNA variants. Mendelian inheritance logic can be used to accurately phase (haplotype) the majority (67-83%) of an individual's heterozygous nucleotide positions when genotypes are available for both parents (trio). However, when all members of a trio are heterozygous at a position, Mendelian inheritance logic cannot be used to phase. For such positions, a computational phasing algorithm can be used. Existing phasing algorithms use a haplotype reference panel, sequencing reads, and/or parental genotypes to phase an individual; however, they are limited in that they can only phase certain types of variants, require a specific genotype build, require large amounts of storage capacity, and/or require long run times. We created trioPhaser to address these challenges.

RESULTS

trioPhaser uses gVCF files from an individual and their parents as initial input, and then outputs a phased VCF file. Input trio data are first phased using Mendelian inheritance logic. Then, the positions that cannot be phased using inheritance information alone are phased by the SHAPEIT4 phasing algorithm. Using whole-genome sequencing data of 52 trios, we show that trioPhaser, on average, increases the total number of phased positions by 21.0% and 10.5%, respectively, when compared to the number of positions that SHAPEIT4 or Mendelian inheritance logic can phase when either is used alone. In addition, we show that the accuracy of the phased calls output by trioPhaser are similar to linked-read and read-backed phasing.

CONCLUSION

trioPhaser is a containerized software tool that uses both Mendelian inheritance logic and SHAPEIT4 to phase trios when gVCF files are available. By implementing both phasing methods, more variant positions are phased compared to what either method is able to phase alone.