Genome sequencing identifies a homozygous inversion disrupting QDPR as a cause for dihydropteridine reductase deficiency

Genome Sequencing for Diagnosing Rare Diseases

BACKGROUND

Genetic variants that cause rare disorders may remain elusive even after expansive testing, such as exome sequencing. The diagnostic yield of genome sequencing, particularly after a negative evaluation, remains poorly defined.

METHODS

We sequenced and analyzed the genomes of families with diverse phenotypes who were suspected to have a rare monogenic disease and for whom genetic testing had not revealed a diagnosis, as well as the genomes of a replication cohort at an independent clinical center.

RESULTS

We sequenced the genomes of 822 families (744 in the initial cohort and 78 in the replication cohort) and made a molecular diagnosis in 218 of 744 families (29.3%). Of the 218 families, 61 (28.0%) - 8.2% of families in the initial cohort - had variants that required genome sequencing for identification, including coding variants, intronic variants, small structural variants, copy-neutral inversions, complex rearrangements, and tandem repeat expansions. Most families in which a molecular diagnosis was made after previous nondiagnostic exome sequencing (63.5%) had variants that could be detected by reanalysis of the exome-sequence data (53.4%) or by additional analytic methods, such as copy-number variant calling, to exome-sequence data (10.8%). We obtained similar results in the replication cohort: in 33% of the families in which a molecular diagnosis was made, or 8% of the cohort, genome sequencing was required, which showed the applicability of these findings to both research and clinical environments.

CONCLUSIONS

The diagnostic yield of genome sequencing in a large, diverse research cohort and in a small clinical cohort of persons who had previously undergone genetic testing was approximately 8% and included several types of pathogenic variation that had not previously been detected by means of exome sequencing or other techniques. (Funded by the National Human Genome Research Institute and others.).

Next-generation sequencing and bioinformatics in rare movement disorders

The ability to sequence entire exomes and genomes has revolutionized molecular testing in rare movement disorders, and genomic sequencing is becoming an integral part of routine diagnostic workflows for these heterogeneous conditions. However, interpretation of the extensive genomic variant information that is being generated presents substantial challenges. In this Perspective, we outline multidimensional strategies for genetic diagnosis in patients with rare movement disorders. We examine bioinformatics tools and computational metrics that have been developed to facilitate accurate prioritization of disease-causing variants. Additionally, we highlight community-driven data-sharing and case-matchmaking platforms, which are designed to foster the discovery of new genotype-phenotype relationships. Finally, we consider how multiomic data integration might optimize diagnostic success by combining genomic, epigenetic, transcriptomic and/or proteomic profiling to enable a more holistic evaluation of variant effects. Together, the approaches that we discuss offer pathways to the improved understanding of the genetic basis of rare movement disorders.

Unique Capabilities of Genome Sequencing for Rare Disease Diagnosis

Background

Causal variants underlying rare disorders may remain elusive even after expansive gene panels or exome sequencing (ES). Clinicians and researchers may then turn to genome sequencing (GS), though the added value of this technique and its optimal use remain poorly defined. We therefore investigated the advantages of GS within a phenotypically diverse cohort.

Methods

GS was performed for 744 individuals with rare disease who were genetically undiagnosed. Analysis included review of single nucleotide, indel, structural, and mitochondrial variants.

Results

We successfully solved 218/744 (29.3%) cases using GS, with most solves involving established disease genes (157/218, 72.0%). Of all solved cases, 148 (67.9%) had previously had non-diagnostic ES. We systematically evaluated the 218 causal variants for features requiring GS to identify and 61/218 (28.0%) met these criteria, representing 8.2% of the entire cohort. These included small structural variants (13), copy neutral inversions and complex rearrangements (8), tandem repeat expansions (6), deep intronic variants (15), and coding variants that may be more easily found using GS related to uniformity of coverage (19).

Conclusion

We describe the diagnostic yield of GS in a large and diverse cohort, illustrating several types of pathogenic variation eluding ES or other techniques. Our results reveal a higher diagnostic yield of GS, supporting the utility of a genome-first approach, with consideration of GS as a secondary or tertiary test when higher-resolution structural variant analysis is needed or there is a strong clinical suspicion for a condition and prior targeted genetic testing has been negative.

Genetic etiology and clinical challenges of phenylketonuria

This review discusses the epidemiology, pathophysiology, genetic etiology, and management of phenylketonuria (PKU). PKU, an autosomal recessive disease, is an inborn error of phenylalanine (Phe) metabolism caused by pathogenic variants in the phenylalanine hydroxylase (PAH) gene. The prevalence of PKU varies widely among ethnicities and geographic regions, affecting approximately 1 in 24,000 individuals worldwide. Deficiency in the PAH enzyme or, in rare cases, the cofactor tetrahydrobiopterin results in high blood Phe concentrations, causing brain dysfunction. Untreated PKU, also known as PAH deficiency, results in severe and irreversible intellectual disability, epilepsy, behavioral disorders, and clinical features such as acquired microcephaly, seizures, psychological signs, and generalized hypopigmentation of skin (including hair and eyes). Severe phenotypes are classic PKU, and less severe forms of PAH deficiency are moderate PKU, mild PKU, mild hyperphenylalaninaemia (HPA), or benign HPA. Early diagnosis and intervention must start shortly after birth to prevent major cognitive and neurological effects. Dietary treatment, including natural protein restriction and Phe-free supplements, must be used to maintain blood Phe concentrations of 120-360 μmol/L throughout the life span. Additional treatments include the casein glycomacropeptide (GMP), which contains very limited aromatic amino acids and may improve immunological function, and large neutral amino acid (LNAA) supplementation to prevent plasma Phe transport into the brain. The synthetic BH4 analog, sapropterin hydrochloride (i.e., Kuvan®, BioMarin), is another potential treatment that activates residual PAH, thus decreasing Phe concentrations in the blood of PKU patients. Moreover, daily subcutaneous injection of pegylated Phe ammonia-lyase (i.e., pegvaliase; PALYNZIQ®, BioMarin) has promised gene therapy in recent clinical trials, and mRNA approaches are also being studied.

Centers for Mendelian Genomics: A decade of facilitating gene discovery

PURPOSE

Mendelian disease genomic research has undergone a massive transformation over the past decade. With increasing availability of exome and genome sequencing, the role of Mendelian research has expanded beyond data collection, sequencing, and analysis to worldwide data sharing and collaboration.

METHODS

Over the past 10 years, the National Institutes of Health-supported Centers for Mendelian Genomics (CMGs) have played a major role in this research and clinical evolution.

RESULTS

We highlight the cumulative gene discoveries facilitated by the program, biomedical research leveraged by the approach, and the larger impact on the research community. Beyond generating a list of gene-phenotype relationships and participating in widespread data sharing, the CMGs have created resources, tools, and training for the larger community to foster understanding of genes and genome variation. The CMGs have participated in a wide range of data sharing activities, including deposition of all eligible CMG data into the Analysis, Visualization, and Informatics Lab-space (AnVIL), sharing candidate genes through the Matchmaker Exchange and the CMG website, and sharing variants in Genotypes to Mendelian Phenotypes (Geno2MP) and VariantMatcher.

CONCLUSION

The work is far from complete; strengthening communication between research and clinical realms, continued development and sharing of knowledge and tools, and improving access to richly characterized data sets are all required to diagnose the remaining molecularly undiagnosed patients.

Microcephaly in Neurometabolic Diseases

Neurometabolic disorders are an important group of diseases that mostly occur in neonates and infants. They are mainly due to the lack or dysfunction of an enzyme or cofactors necessary for a specific biochemical reaction, which leads to a deficiency of essential metabolites in the brain. This, in turn, can cause certain neurometabolic diseases. Disruption of metabolic pathways, and the inhibition at earlier stages, may lead to the storage of reaction intermediates, which are often toxic to the developing brain. Symptoms are caused by the progressive deterioration of mental, motor, and perceptual functions. The authors review the diseases with microcephaly, which may be one of the most visible signs of neurometabolic disorders.

Genome sequencing identifies a homozygous inversion disrupting QDPR as a cause for dihydropteridine reductase deficiency

Background

Dihydropteridine reductase (DHPR) is one of the key enzymes for maintaining in the organism the supply of tetrahydrobiopterin (BH₄), an essential cofactor for aromatic amino acid hydroxylases. Its dysfunction causes the condition of hyperphenylalaninemia together with the lack of neurotransmitters.

Methods

We report a patient with biochemically diagnosed DHPR deficiency, with extensive molecular investigations undertaken to detect variations in quinoid dihydropteridine reductase (QDPR) gene. Sanger sequencing of QDPR coding regions, exome sequencing, QDPR mRNA PCR, and karyotyping were followed by trio genome sequencing.

Results

Short‐read genome sequencing revealed a homozygous 9‐Mb inversion disrupting QDPR. Structural variant breakpoints in chromosome 4 were located to intron 2 of QDPR at Chr4(GRCh38):g.17505522 and in intron 8 of the ACOX3 gene, Chr4(GRCh38):g.8398067). Both nonrelated parents carried the variant in heterozygous state. The inversion was not present in gnomAD structural variant database.

Conclusion

Identification of the exact breakpoints now allows further straightforward molecular genetic testing of potential carriers of the inversion. This study extends the pathogenic variant spectrum of DHPR deficiency and highlights the role of structural variants in recessive metabolic disorders. To our knowledge, this is the first report on a large, canonical (rather than complex) homozygous pathogenic inversion detected by genome sequencing.