Bagnall, R. D. | bioRxiv Science

bioRxiv2024

An ALPK3 truncation variant causing autosomal dominant hypertrophic cardiomyopathy is partially rescued by mavacamten

The ALPK3 gene encodes alpha-protein kinase 3, a cardiac pseudo-kinase of unknown function. Heterozygous truncating variants (ALPK3tv) can cause dominant adult-onset Hypertrophic Cardiomyopathy (HCM). Here we confirm an excess of ALPK3tv in sarcomere-gene negative HCM patients. Moreover, we generated a novel knock-in mouse model carrying an ALPK3tv (K201X). Homozygous animals displayed hypertrophy and systolic dysfunction. Heterozygous animals demonstrated no obvious baseline; however, they had an aggravated hypertrophic response upon chronic adrenergic challenge. Isolated cardiomyocytes from heterozygous and homozygous mice showed reduced basal sarcomere length with prolonged relaxation, whilst calcium transients showed increased diastolic calcium levels and prolonged re-uptake. We also observed reduced fractional shortening. Protein kinase A-mediated phosphorylation, including that of cardiac troponin I, was significantly decreased. In agreement with the cellular HCM phenotype, reduced ratios of myosin heads in the super-relaxed state were measured. Contractile and calcium handling defects were partly corrected by treatment with mavacamten, a novel myosin inhibitor. For the first time with a non-sarcomere HCM variant, we have demonstrated hallmark changes in cardiac contractility and calcium handling, some resembling sarcomere-positive HCM, while others are distinct and DCM-like. Mavacamten is able to partially rescue the cellular phenotype, hence could be beneficial to HCM patients with ALPK3tv.

genetics↗

bioRxiv2023

Predicting the impact of rare variants on RNA splicing in CAGI6

BackgroundVariants which disrupt splicing are a frequent cause of rare disease that have been under-ascertained clinically. Accurate and efficient methods to predict a variants impact on splicing are needed to interpret the growing number of variants of unknown significance (VUS) identified by exome and genome sequencing. Here we present the results of the CAGI6 Splicing VUS challenge, which invited predictions of the splicing impact of 56 variants ascertained clinically and functionally validated to determine splicing impact. ResultsThe performance of 12 prediction methods, along with SpliceAI and CADD, was compared on the 56 functionally validated variants. The maximum overall accuracy achieved was 82% from two different approaches, one weighting SpliceAI scores by minor allele frequency, and one applying the recently published Splicing Prediction Pipeline (SPiP). SPiP performed optimally in terms of sensitivity, while an ensemble method combining multiple prediction tools and information from databases exceeded all others for specificity. ConclusionsSeveral challenge methods equalled or exceeded the performance of SpliceAI, with ultimate choice of prediction method likely to depend on experimental or clinical aims. One quarter of the variants were incorrectly predicted by at least 50% of the methods, highlighting the need for further improvements to splicing prediction methods for successful clinical application.

bioinformatics↗