Compound Heterozygous Variants in Pediatric Cancers: A Systematic Review

A kinetic model for compound heterozygous pathogenic variants in Tyrosyl-tRNA synthetase gene YARS2-Associated neonatal phenotype

Human genetic disorders are often caused by mutations of compound heterozygosity, where each allele of the mutant gene harbors a different genetic lesion. However, studies of such mutations are hampered due to the lack of an appropriate model. Here we describe a kinetic model of compound heterozygous variants in an obligate enzyme dimer that contains one mutation in one monomer and the other mutation in the second monomer. This enzyme is encoded by human YARS2 for mitochondrial tyrosyl-tRNA synthetase (mt-TyrRS), which aminoacylates tyrosine to mt-tRNATyr. YARS2 is a member of the genes for mt-aminoacyl-tRNA synthetases, where pathogenic mutations present limited correlation between disease severity and enzyme activity. We identify a pair of compound heterozygous variants in YARS2 that is associated with neonatal fatality. We show that, while each mutation causes a minor-to-modest defect in aminoacylation in the homodimer of mt-TyrRS, the two mutations in trans synergistically reduce the enzyme activity to a greater effect. This kinetic model thus accurately recapitulates the disease severity, emphasizing its utility to study YARS2 mutations and its potential for generalization to other diseases with compound heterozygous mutations.

Understanding genetic variants in context

Over the last three decades, human genetics has gone from dissecting high-penetrance Mendelian diseases to discovering the vast and complex genetic etiology of common human diseases. In tackling this complexity, scientists have discovered the importance of numerous genetic processes - most notably functional regulatory elements - in the development and progression of these diseases. Simultaneously, scientists have increasingly used multiplex assays of variant effect to systematically phenotype the cellular consequences of millions of genetic variants. In this article, we argue that the context of genetic variants - at all scales, from other genetic variants and gene regulation to cell biology to organismal environment - are critical components of how we can employ genomics to interpret these variants, and ultimately treat these diseases. We describe approaches to extend existing experimental assays and computational approaches to examine and quantify the importance of this context, including through causal analytic approaches. Having a unified understanding of the molecular, physiological, and environmental processes governing the interpretation of genetic variants is sorely needed for the field, and this perspective argues for feasible approaches by which the combined interpretation of cellular, animal, and epidemiological data can yield that knowledge.

Pathogenic nsSNPs of protein kinase C-eta with hepatocellular carcinoma susceptibility

BACKGROUND

Hepatocellular carcinoma (HCC) is a global health concern. Due to late diagnosis and limited therapeutic strategies, HCC based mortality rate is exponentially increasing globally. Genetic predisposition is a non-avoidable intrinsic factor that could alter the genome sequence, ultimately leading to HCC. Protein kinase C eta (PKCη) is involved in key physiological roles, hence alteration in PKCη could aid in cancer progression. Research indicates association between non-synonymous (ns) SNPs and HCC onset. However, effect of nsSNP variants of PKCη on HCC development has not been explored yet. Hence, this study aimed to investigate the association between pathogenic nsSNPs of PKCη with HCC.

METHODS

Non-synonymous (missense) variants of PKCη were obtained from Ensembl genome browser. These variants were filtered out to obtain pathogenic nsSNPs of PKCη. Genotyping of nsSNPs was done through Tetra ARMS PCR. For that, blood samples of 348 HCC patients and 337 controls were collected. The clinical factors that influence HCC were studied. Relative risk (RR) and Odds Ratio (OR) with 95% confidence interval was calculated by Chi-square test and P-value < 0.05 was deemed significant.

RESULTS

Five nsSNP variants of PKCη including rs1162102190 (T/C), rs868127012 (G/T), rs750830348 (G/T), rs768619375 (T/C), and rs752329416 (T/C) were identified. The retrieved nsSNPs were frequently identified in HCC patients. However, rs752329416 T/C was significantly prevalent in patients having HCC family history. Moreover, all the variants were found in HCC patients manifesting the stage II than the advance stages of HCC.

CONCLUSION

This study can be utilized to identify potential genetic markers for early screening of HCC. Moreover, consideration of further clinical factors, and mechanistic approach would enhance the understanding that how alteration in nsSNPs could impact the HCC onset.

Phased nanopore assembly with Shasta and modular graph phasing with GFAse

Reference-free genome phasing is vital for understanding allele inheritance and the impact of single-molecule DNA variation on phenotypes. To achieve thorough phasing across homozygous or repetitive regions of the genome, long-read sequencing technologies are often used to perform phased de novo assembly. As a step toward reducing the cost and complexity of this type of analysis, we describe new methods for accurately phasing Oxford Nanopore Technologies (ONT) sequence data with the Shasta genome assembler and a modular tool for extending phasing to the chromosome scale called GFAse. We test using new variants of ONT PromethION sequencing, including those using proximity ligation, and show that newer, higher accuracy ONT reads substantially improve assembly quality.

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.

Phased nanopore assembly with Shasta and modular graph phasing with GFAse

As a step towards simplifying and reducing the cost of haplotype resolved de novo assembly, we describe new methods for accurately phasing nanopore data with the Shasta genome assembler and a modular tool for extending phasing to the chromosome scale called GFAse. We test using new variants of Oxford Nanopore Technologies' (ONT) PromethION sequencing, including those using proximity ligation and show that newer, higher accuracy ONT reads substantially improve assembly quality.

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.

Recent Advances in Pediatric Cancer Research

Over the past few years, the field of pediatric cancer has experienced a shift in momentum, and this has led to new and exciting findings that have relevance beyond pediatric malignancies. Here we present the current status of key aspects of pediatric cancer research. We have focused on genetic and epigenetic drivers of disease, cellular origins of different pediatric cancers, disease models, the tumor microenvironment, and cellular immunotherapies.

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.

Toward a methodology for evaluating DNA variants in nuclear families

The genetic underpinnings of most pediatric-cancer cases are unknown. Population-based studies use large sample sizes but have accounted for only a small proportion of the estimated heritability of pediatric cancers. Pedigree-based studies are infeasible for most human populations. One alternative is to collect genetic data from a single nuclear family and use inheritance patterns within the family to filter candidate variants. This approach can be applied to common and rare variants, including those that are private to a given family or to an affected individual. We evaluated this approach using genetic data from three nuclear families with 5, 4, and 7 children, respectively. Only one child in each nuclear family had been diagnosed with cancer, and neither parent had been affected. Diagnoses for the affected children were benign low-grade astrocytoma, Wilms tumor (stage 2), and Burkitt's lymphoma, respectively. We used whole-genome sequencing to profile normal cells from each family member and a linked-read technology for genomic phasing. For initial variant filtering, we used global minor allele frequencies, deleteriousness scores, and functional-impact annotations. Next, we used genetic variation in the unaffected siblings as a guide to filter the remaining variants. As a way to evaluate our ability to detect variant(s) that may be relevant to disease status, the corresponding author blinded the primary author to affected status; the primary author then assigned a risk score to each child. Based on this evidence, the primary author predicted which child had been affected in each family. The primary author's prediction was correct for the child who had been diagnosed with a Wilms tumor; the child with Burkitt's lymphoma had the second-highest risk score among the seven children in that family. This study demonstrates a methodology for filtering and evaluating candidate genomic variants and genes within nuclear families that may merit further exploration.

Genetic association studies of alterations in protein function expose recessive effects on cancer predisposition

The characterization of germline genetic variation affecting cancer risk, known as cancer predisposition, is fundamental to preventive and personalized medicine. Studies of genetic cancer predisposition typically identify significant genomic regions based on family-based cohorts or genome-wide association studies (GWAS). However, the results of such studies rarely provide biological insight or functional interpretation. In this study, we conducted a comprehensive analysis of cancer predisposition in the UK Biobank cohort using a new gene-based method for detecting protein-coding genes that are functionally interpretable. Specifically, we conducted proteome-wide association studies (PWAS) to identify genetic associations mediated by alterations to protein function. With PWAS, we identified 110 significant gene-cancer associations in 70 unique genomic regions across nine cancer types and pan-cancer. In 48 of the 110 PWAS associations (44%), estimated gene damage is associated with reduced rather than elevated cancer risk, suggesting a protective effect. Together with standard GWAS, we implicated 145 unique genomic loci with cancer risk. While most of these genomic regions are supported by external evidence, our results also highlight many novel loci. Based on the capacity of PWAS to detect non-additive genetic effects, we found that 46% of the PWAS-significant cancer regions exhibited exclusive recessive inheritance. These results highlight the importance of recessive genetic effects, without relying on familial studies. Finally, we show that many of the detected genes exert substantial cancer risk in the studied cohort determined by a quantitative functional description, suggesting their relevance for diagnosis and genetic consulting.

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

Compound heterozygous (CH) variants occur when two recessive alleles are inherited and the variants are located at different loci within the same gene in a given individual. CH variants are important contributors to many different types of recessively inherited diseases. However, many studies overlook CH variants because identification of this type of variant requires knowing the parent of origin for each nucleotide. Using computational methods, haplotypes can be inferred using a process called "phasing," which estimates the chromosomal origin of most nucleotides. In this paper, we used germline, phased, whole-genome sequencing (WGS) data to identify CH variants across seven pediatric diseases (adolescent idiopathic scoliosis: n = 16, congenital heart defects: n = 709, disorders of sex development: n = 79, ewing sarcoma: n = 287, neuroblastoma: n = 259, orofacial cleft: n = 107, and syndromic cranial dysinnervation: n = 172), available as parent-child trios in the Gabriella Miller Kids First Data Resource Center. Relatively little is understood about the genetic underpinnings of these diseases. We classified CH variants as "potentially damaging" based on minor allele frequencies (MAF), Combined Annotation Dependent Depletion scores, variant impact on transcription or translation, and gene-level frequencies in the disease group compared to a healthy population. For comparison, we also identified homozygous alternate (HA) variants, which affect both gene copies at a single locus; HA variants represent an alternative mechanism of recessive disease development and do not require phasing. Across all diseases, 2.6% of the samples had a potentially damaging CH variant and 16.2% had a potentially damaging HA variant. Of these samples with potentially damaging variants, the average number of genes per sample was 1 with a CH variant and 1.25 with a HA variant. Across all samples, 5.1 genes per disease had a CH variant, while 35.6 genes per disease had a HA variant; on average, only 4.3% of these variants affected common genes. Therefore, when seeking to identify potentially damaging variants of a putatively recessive disease, CH variants should be considered as potential contributors to disease development. If CH variants are excluded from analysis, important candidate genes may be overlooked.

CompoundHetVIP: Compound Heterozygous Variant Identification Pipeline

Compound Heterozygous ( CH) variant identification requires distinguishing maternally from paternally derived nucleotides, a process that requires numerous computational tools. Using such tools often introduces unforeseen challenges such as installation procedures that are operating-system specific, software dependencies that must be installed, and formatting requirements for input files. To overcome these challenges, we developed Compound Heterozygous Variant Identification Pipeline (CompoundHetVIP), which uses a single Docker image to encapsulate commonly used software tools for file aggregation ( BCFtools or GATK4), VCF liftover ( Picard Tools), joint-genotyping ( GATK4), file conversion ( Plink2), phasing ( SHAPEIT2, Beagle, and/or Eagle2), variant normalization ( vt tools), annotation ( SnpEff), relational database generation ( GEMINI), and identification of CH, homozygous alternate, and de novo variants in a series of 13 steps. To begin using our tool, researchers need only install the Docker engine and download the CompoundHetVIP Docker image. The tools provided in CompoundHetVIP, subject to the limitations of the underlying software, can be applied to whole-genome, whole-exome, or targeted exome sequencing data of individual samples or trios (a child and both parents), using VCF or gVCF files as initial input. Each step of the pipeline produces an analysis-ready output file that can be further evaluated. To illustrate its use, we applied CompoundHetVIP to data from a publicly available Ashkenazim trio and identified two genes with a candidate CH variant and two genes with a candidate homozygous alternate variant after filtering based on user-set thresholds for global minor allele frequency, Combined Annotation Dependent Depletion, and Gene Damage Index. While this example uses genomic data from a healthy child, we anticipate that most researchers will use CompoundHetVIP to uncover missing heritability in human diseases and other phenotypes. CompoundHetVIP is open-source software and can be found at https://github.com/dmiller903/CompoundHetVIP; this repository also provides detailed, step-by-step examples.