High-Throughput Sequencing Reveals the Loss-of-Function Mutations in GALT Cause Recessive Classical Galactosemia

A case report of classic galactosemia with a GALT gene variant and a literature review

BACKGROUND

Galactosemia is an autosomal recessive disorder resulting from an enzyme defect in the galactose metabolic pathway. The most severe manifestation of classic galactosemia is caused by galactose-1-phosphate uridylyltransferase (GALT) deficiency, and this condition can be fatal during infancy if left untreated. It also may result in long-term complications in affected individuals.

CASE PRESENTATION

This report describes a patient whose initial clinical symptoms were jaundice and liver dysfunction. The patient's liver and coagulation functions did not improve after multiple admissions and treatment with antibiotics, hepatoprotective and choleretic agents and blood transfusion. Genetic analysis revealed the presence of two variants in the GALT gene in the compound heterozygous state: c.377 + 2dup and c.368G > C (p.Arg123Pro). Currently, the variant locus (c.377 + 2dup) in the GALT gene has not been reported in the Human Gene Mutation Database (HGMD), while c.368G > C (p.Arg123Pro) has not been reported in the Genome Aggregation Database (GnomAD) nor the HGMD in East Asian population. We postulated that the two variants may contribute to the development of classical galactosemia.

CONCLUSIONS

Applications of whole-exome sequencing to detect the two variants can improve the detection and early diagnosis of classical galactosemia and, more specifically, may identify individuals who are compound heterozygous with variants in the GALT gene. Variants in the GALT gene have a potential therapeutic significance for classical galactosemia.

Identification and molecular analysis of 11 cases of the PTS gene variants associated with tetrahydrobiopterin deficiency

Background: Tetrahydrobiopterin deficiency (BH4D) is a rare autosomal recessive amino acid metabolic disease that belongs to a kind of hyperphenylalaninemia (HPA), and 6-pyruvyltetrahydrotrexate synthase (PTPS) deficiency is the most common type of BH4D. This study investigates the clinical and genetic characteristics of 11 PTPS deficiency cases in the Beijing area, identifies the genetic pathogenic factors, and evaluates the value of high-throughput sequencing in the precise diagnosis of PTPS deficiency.

Methods: The Beijing Neonatal Disease Screening Center diagnosed patients with HPA. The study used phenylalanine (Phe) in blood, the ratio of Phe to Thr, urotrexate spectrum analysis, erythrocyte dihydrotrexate reductase (DHPR) activity determination, and high-throughput sequencing as methods. Bioinformatics software analyzed the variants’ pathogenicity and used RT-PCR to identify deep intron variants’ pathogenicity.

Result: Among 635 cases with HPA, 38 cases were diagnosed with BH4D, of which the incidence in HPA was 5.98%. Nine kinds of PTS gene variants were detected, including seven missense variants, one splicing variant, and one deletion variant. The splicing variant c.84–291A>G had three splicing results in vivo: normal length, 79bp pseudoexon insertion, and exon 3 skipping. Bioinformatics and Sanger sequencing were performed to verify the identified variants.

Conclusion: High-throughput sequencing is a helpful tool for clinical diagnosis and differential diagnosis of BH4D. This study confirms that c.84–291A>G is the hot spot variant of PTPS deficiency, and it is the first reported variant with a new splicing pattern in vivo. A novel deletion variant c.84_163del (p.Lys29Cysfs∗9) was found to enrich the genetic variant spectrum of the disease.

Current Understanding on the Genetic Basis of Key Metabolic Disorders: A Review

Simple Summary

Metabolic disorders (MD) are a challenge to healthcare systems; the emergence of the modern socio-economic system has led to a profound change in lifestyles in terms of dietary habits, exercise regimens, and behavior, all of which complement the genetic factors associated with MD. Diabetes Mellitus and Familial hypercholesterolemia are two of the 14 most widely researched MD, as they pose the greatest challenge to the public healthcare system and have an impact on productivity and the economy. Research findings have led to the development of new therapeutic molecules for the mitigation of MD as well as the invention of experimental strategies, which target the genes themselves via gene editing and RNA interference. Although these approaches may herald the emergence of a new toolbox to treat MD, the current therapeutic approaches still heavily depend on substrate reduction, dietary restrictions based on genetic factors, exercise, and the maintenance of good mental health. The development of orphan drugs for the less common MD such as Krabbe, Farber, Fabry, and Gaucher diseases, remains in its infancy, owing to the lack of investment in research and development, and this has driven the development of personalized therapeutics based on gene silencing and related technologies.

Abstract

Advances in data acquisition via high resolution genomic, transcriptomic, proteomic and metabolomic platforms have driven the discovery of the underlying factors associated with metabolic disorders (MD) and led to interventions that target the underlying genetic causes as well as lifestyle changes and dietary regulation. The review focuses on fourteen of the most widely studied inherited MD, which are familial hypercholesterolemia, Gaucher disease, Hunter syndrome, Krabbe disease, Maple syrup urine disease, Metachromatic leukodystrophy, Mitochondrial encephalopathy lactic acidosis stroke-like episodes (MELAS), Niemann-Pick disease, Phenylketonuria (PKU), Porphyria, Tay-Sachs disease, Wilson’s disease, Familial hypertriglyceridemia (F-HTG) and Galactosemia based on genome wide association studies, epigenetic factors, transcript regulation, post-translational genetic modifications and biomarker discovery through metabolomic studies. We will delve into the current approaches being undertaken to analyze metadata using bioinformatic approaches and the emerging interventions using genome editing platforms as applied to animal models.