Biology subjects

Gunning, A. C.

Publications and source records attributed to Gunning, A. C..

3 recordsLinked to original sources

bioRxiv2020

Functional interpretation of ATAD3A variants in neuro-mitochondrial phenotypes

BackgroundThe ATPase family AAA-domain containing protein 3A (ATAD3A) is a nuclear-encoded mitochondrial membrane anchored protein involved in diverse processes including mitochondrial dynamics, mitochondrial DNA organization, and cholesterol metabolism. Biallelic deletions (null), recessive missense variants (hypomorph), and heterozygous missense variants or duplications (antimorph) in ATAD3A lead to neurological syndromes in humans. ObjectiveTo expand the mutational spectrum of ATAD3A variants and to provide functional interpretation of missense alleles in trans to deletion alleles. MethodsExome sequencing was used to identify single nucleotide variants (SNVs) and copy number variants (CNVs) in ATAD3A in individuals with neurological and mitochondrial phenotypes. A Drosophila Atad3A Gal4 trap null allele was generated using CRISPR-Cas9 genome editing technology to aid interpretation of variants. ResultsWe report 13 individuals from 8 unrelated families with biallelic ATAD3A variants. Four of the identified missense variants, p.(Leu77Val), p.(Phe50Leu), p.(Arg170Trp), p.(Gly236Val), were inherited in trans to loss-of-function alleles. A fifth missense variant, p.(Arg327Pro), was homozygous. Affected individuals exhibited findings previously associated with ATAD3A pathogenic variation, including developmental delay, hypotonia, congenital cataracts, hypertrophic cardiomyopathy, and cerebellar atrophy. Drosophila studies indicated that Phe50Leu, Gly236Val, and Arg327Pro are severe loss-of-function alleles leading to early developmental lethality and neurogenesis defects, whereas Leu77Val and Arg170Trp are partial loss of function alleles that cause progressive locomotion defects. Moreover, Leu77Val and Arg170Trp expression leads to an increase in autophagy and mitophagy in adult muscles. ConclusionOur findings expand the allelic spectrum of ATAD3A variants, and exemplify the use of a functional assay in Drosophila to aid variant interpretation.

genetics↗

bioRxiv2020

Assessing performance of pathogenicity predictors using clinically-relevant variant datasets

PurposePathogenicity predictors are an integral part of genomic variant interpretation but, despite their widespread usage, an independent validation of performance using a clinically-relevant dataset has not been undertaken. MethodsWe derive two validation datasets: an "open" dataset containing variants extracted from publicly-available databases, similar to those commonly applied in previous benchmarking exercises, and a "clinically-representative" dataset containing variants identified through research/diagnostic exome and diagnostic panel sequencing. Using these datasets, we evaluate the performance of three recently developed meta-predictors, REVEL, GAVIN and ClinPred, and compare their performance against two commonly used in silico tools, SIFT and PolyPhen-2. ResultsAlthough the newer meta-predictors outperform the older tools, the performance of all pathogenicity predictors is substantially lower in the clinically-representative dataset. Using our clinically-relevant dataset, REVEL performed best with an area under the ROC of 0.81. Using a concordance-based approach based on a consensus of multiple tools reduces the performance due to both discordance between tools and false concordance where tools make common misclassification. Analysis of tool feature usage may give an insight into the tool performance and misclassification. ConclusionOur results support the adoption of meta-predictors over traditional in silico tools, but do not support a consensus-based approach as recommended by current variant classification guidelines.

genomics↗

bioRxiv2019

Using structural analysis to assess the impact of missense variants in MEN1

Despite the rapid expansion in recent years of databases reporting either benign or pathogenic genetic variation, the interpretation of novel missense variants can remain challenging, particularly for clinical or genetic testing laboratories where functional analysis is often unfeasible. Previous studies have shown that thermodynamic analysis of protein structure in silico can discriminate between groups of benign and pathogenic missense variants. However, although structures exist for many human disease-associated proteins, such analysis remains largely unexploited in clinical laboratories. Here, we analysed the predicted effect of 338 known missense variants on the structure of Menin, the MEN1 gene product. Results provided strong discrimination between pathogenic and benign variants, with a threshold of >4 kcal/mol for the predicted change in stability providing a strong indicator of pathogenicity. Subsequent analysis of 7 novel missense variants identified during clinical testing of MEN1 patients showed that all 7 were predicted to destabilise Menin by >4 kcal/mol. We conclude that structural analysis provides a useful tool in understanding the impact of missense variants in MEN1, and that integration of proteomic with genomic data could potentially contribute to the classification of novel variants in this disease.

genetics↗