The Global ALPL gene variant classification project: Dedicated to deciphering variants

BACKGROUND

Hypophosphatasia (HPP) is an inherited multisystem disorder predominantly affecting the mineralization of bones and teeth. HPP is caused by pathogenic variants in ALPL, which encodes tissue non-specific alkaline phosphatase (TNSALP). Variants of uncertain significance (VUS) cause diagnostic delay and uncertainty amongst patients and health care providers.

RESULTS

The ALPL gene variant database (https://alplmutationdatabase.jku.at/) is an open-access archive for interpretation of the clinical significance of variants reported in ALPL. The database contains coding and non-coding variants, including single nucleotide variants, insertions/deletions and structural variants affecting coding or non-coding sequences of ALPL. Each variant in the database is displayed with details explaining the corresponding pathogenicity, and all reported genotypes and phenotypes, including references. In 2021, the ALPL gene variant classification project was established to reclassify VUS and continuously assess and update genetic, phenotypic, and functional variant information in the database. For this purpose, the database provides a unique submission system for clinicians, geneticists, genetic counselors, and researchers to submit VUS within ALPL for classification. An international, multidisciplinary consortium of HPP experts has been established to reclassify the submitted VUS using a multi-step process adhering to the stringent ACMG/AMP variant classification guidelines. These steps include a clinical phenotype assessment, deep literature research including artificial intelligence technology, molecular genetic assessment, and in-vitro functional testing of variants in a co-transfection model to measure ALP residual activity.

CONCLUSION

This classification project and the ALPL gene variant database will serve the global medical community, widen the genotypic and phenotypic HPP spectrum by reporting and characterizing new ALPL variants based on ACMG/AMP criteria and thus facilitate improved genetic counseling and medical decision-making for affected patients and families. The project may also serve as a gold standard framework for multidisciplinary collaboration for variant interpretation in other rare diseases.

A genome sequencing system for universal newborn screening, diagnosis, and precision medicine for severe genetic diseases

Newborn screening (NBS) dramatically improves outcomes in severe childhood disorders by treatment before symptom onset. In many genetic diseases, however, outcomes remain poor because NBS has lagged behind drug development. Rapid whole-genome sequencing (rWGS) is attractive for comprehensive NBS because it concomitantly examines almost all genetic diseases and is gaining acceptance for genetic disease diagnosis in ill newborns. We describe prototypic methods for scalable, parentally consented, feedback-informed NBS and diagnosis of genetic diseases by rWGS and virtual, acute management guidance (NBS-rWGS). Using established criteria and the Delphi method, we reviewed 457 genetic diseases for NBS-rWGS, retaining 388 (85%) with effective treatments. Simulated NBS-rWGS in 454,707 UK Biobank subjects with 29,865 pathogenic or likely pathogenic variants associated with 388 disorders had a true negative rate (specificity) of 99.7% following root cause analysis. In 2,208 critically ill children with suspected genetic disorders and 2,168 of their parents, simulated NBS-rWGS for 388 disorders identified 104 (87%) of 119 diagnoses previously made by rWGS and 15 findings not previously reported (NBS-rWGS negative predictive value 99.6%, true positive rate [sensitivity] 88.8%). Retrospective NBS-rWGS diagnosed 15 children with disorders that had been undetected by conventional NBS. In 43 of the 104 children, had NBS-rWGS-based interventions been started on day of life 5, the Delphi consensus was that symptoms could have been avoided completely in seven critically ill children, mostly in 21, and partially in 13. We invite groups worldwide to refine these NBS-rWGS conditions and join us to prospectively examine clinical utility and cost effectiveness.

Investigation of ALPL variant states and clinical outcomes: An analysis of adults and adolescents with hypophosphatasia treated with asfotase alfa

BACKGROUND

Hypophosphatasia (HPP), a rare metabolic disease, can be inherited in an autosomal recessive (biallelic) or an autosomal dominant (monoallelic) manner. Most of the severe, early-onset, frequently lethal HPP in infants is acquired through recessive inheritance; less severe, later-onset, typically nonlethal HPP phenotypes are acquired through either dominant or recessive inheritance. HPP's variable clinical presentation arises from >400 identified ALPL pathogenic variants with likely variable penetrance, especially with autosomal dominant inheritance. This post hoc analysis investigated the relationship between ALPL variant state (biallelic and monoallelic) and clinical outcomes with asfotase alfa in HPP.

METHODS

Data were pooled from two phase 2, randomized, open-label studies in adolescents and adults with HPP; one study evaluated the efficacy and safety of different doses of asfotase alfa (n = 25), and the other assessed the pharmacodynamics and safety of asfotase alfa (n = 19). Patients were grouped by ALPL variant state (biallelic or monoallelic). Available data from both studies included ALPL pathogenic variant state, Baseline characteristics, HPP-specific medical history, and Baseline TNSALP substrate levels (inorganic pyrophosphate [PPi] and pyridoxal 5'-phosphate [PLP]) concentrations). Clinical outcomes over 5 years of treatment were available from only the efficacy and safety study.

RESULTS

In total, 44 patients with known variant status were included in the pooled analysis (biallelic, n = 30; monoallelic, n = 14). The most common pathogenic variant was c.571G > A (p.Glu191Lys) in biallelic patients (allele frequency: 19/60) and c.1133A > T (p.Asp378Val) in monoallelic patients (allele frequency: 7/28). Median (min, max) Baseline PPi concentrations were significantly higher in patients with a biallelic vs monoallelic variant state (5.3 [2.2, 12.1] vs 4.3 [3.5, 7.4] μM; P = 0.0113), as were Baseline PLP concentrations (221.4 [62.4, 1590.0] vs 75.1 [28.8, 577.0] ng/mL; P= 0.0022). HPP-specific medical history was generally similar between biallelic and monoallelic patients in terms of incidence and type of manifestations; notable exceptions included fractures, which were more common among monoallelic patients, and delayed walking and bone deformities such as abnormally shaped chest and head and bowing of arms or legs, which were more common among biallelic patients. Data from the efficacy and safety study (n = 19) showed that median PPi and PLP concentrations were normalized over 5 years of treatment in patients with both variant states. Median % predicted distance walked on the 6-Minute Walk Test remained within the normal range for monoallelic patients over 4 years of treatment, and improved from below normal (<84%) to normal in biallelic patients.

CONCLUSIONS

Although patients with biallelic variants had significantly higher Baseline PPi and PLP levels than monoallelic variants, both groups generally showed similar pretreatment Baseline clinical characteristics. Treatment with asfotase alfa for up to 5 years normalized TNSALP substrate concentrations and improved functional outcomes, with no clear differences between biallelic and monoallelic variant states. This study suggests that patients with HPP have significant disease burden, regardless of ALPL variant state.

From FastQ data to high confidence variant calls: the Genome Analysis Toolkit best practices pipeline

This unit describes how to use BWA and the Genome Analysis Toolkit (GATK) to map genome sequencing data to a reference and produce high-quality variant calls that can be used in downstream analyses. The complete workflow includes the core NGS data processing steps that are necessary to make the raw data suitable for analysis by the GATK, as well as the key methods involved in variant discovery using the GATK.