Biology subjects

Lindy, A.

Publications and source records attributed to Lindy, A..

3 recordsLinked to original sources

bioRxiv2025

Characterization of the functional and clinical impacts of CACNA1A missense variants found in neurodevelopmental disorders

CACNA1A encodes the P/Q-type CaV2.1 calcium channels whose function underlies neuronal excitability, presynaptic neurotransmitter release, and Ca2+ signaling in neurons. Pathogenic variants in CACNA1A have been found in individuals with various neurological conditions, including hemiplegic migraine, epilepsy, developmental delay, and ataxia. Clinical presentations can vary significantly between patients, with limited information known about the underlying neurobiology of these different clinical patterns. Adding further complication, prior work on pathogenic missense variants has demonstrated variable impacts on CaV2.1 channel function, sometimes in opposite directions. As such, the relationships between specific coding variants, electrophysiological properties, and clinical phenotypes remain elusive. In this study, we determined the biophysical properties of an allelic series of 42 de novo missense CACNA1A variants discovered in a neurodevelopmental disorder cohort of more than 31,000 individuals, together with the most common eight coding variants found in the general population. We found that all but one de novo variant altered at least one aspect of the channel properties examined, and the majority (70%) of the variants reduced the channel current density. In addition, for variants that encode human CaV2.1 channels (hCaV2.1) with detectable currents, nearly 50% altered how channels respond to membrane potential, while common variations did not significantly change any channel biophysical properties. Coupled with our functional analyses and AlphaMissense prediction, we showed that CaV2.1 missense variants significantly underlie the risk of developmental epileptic encephalopathy. Subsequently, we examined the physiological impact of variant hCaV2.1 using NEURON simulations as an omnibus output of neuronal function and found that abnormal biophysical channel properties have a profound impact on Purkinje cell excitability. Most interestingly, we correlated the clinical phenotype with molecular consequences of missense variants provided by our comprehensive functional analyses and found that distinct CaV2.1 channel molecular function is significantly associated with different clinical outcomes. By analyzing an entire allelic series of CACNA1A de novo changes in a large cohort of individuals with neurodevelopmental disorders, we provide a powerful approach to dissecting the role of missense variants in CACNA1A channelopathy, which in turn may help pave the way for future precision medicine initiatives.

neuroscience↗

bioRxiv2021

High-throughput Evaluation of Epilepsy-associated KCNQ2 Variants Reveals Functional and Pharmacological Heterogeneity

Hundreds of KCNQ2 variants have been identified by genetic testing of children with early onset epilepsy and/or developmental disability. Voltage-clamp recording from heterologous cells has proved useful for establishing deleterious functional effects of KCNQ2 variants, but procedures adapting these assays for standardized, higher throughput data collection and reporting are lacking. In this study, we employed automated patch clamp recording to assess in parallel the functional and pharmacological properties of 79 missense and 2 in-frame deletion variants of KCNQ2. Among the variants we studied were a training set of 18 pathogenic variants previously studied by voltage-clamp recording, 24 mostly rare population variants, and 39 disease-associated variants with unclear functional effects. Variant KCNQ2 subunits were transiently expressed in a cell line stably expressing KCNQ3 to reconstitute the physiologically relevant channel complex. Variants with severe loss-of-function were also co-expressed 1:1 with WT KCNQ2 in the KCNQ3 cell line to mimic the heterozygous genotype and assess dominant-negative behavior. In total, we analyzed electrophysiological data recorded from 9,480 cells. The functional properties of WT KCNQ2/KCNQ3 channels and pharmacological responses to known blockers and activators determined by automated patch clamp recording were highly concordant with previous findings. Similarly, functional properties of 18 known pathogenic variants largely matched previously published results and the validated automated patch clamp assay. Many of the 39 previously unstudied disease-associated KCNQ2 variants exhibited prominent loss-of-function and dominant-negative effects, providing strong evidence in support of pathogenicity. All variants, exhibit response to retigabine (10 {micro}M), although there were differences in maximal responses. Variants within the ion selectivity filter exhibited the weakest responses whereas retigabine had the strongest effect on gain-of-function variants in the voltage-sensor domain. Our study established a high throughput method to detect deleterious functional consequences of KCNQ2 variants. We demonstrated that dominant-negative loss-of-function is a common mechanism associated with missense KCNQ2 variants but this does not occur with rare population variation in this gene. Importantly, we observed genotype-dependent differences in the response of KCNQ2 variants to retigabine.

neuroscience↗

bioRxiv2018

Genetic variant pathogenicity prediction trained using large-scale disease specific clinical sequencing datasets

Recent advances in DNA sequencing technologies have expanded our understanding of the molecular underpinnings for several genetic disorders, and increased the utilization of genomic tests by clinicians. Given the paucity of evidence to assess each variant, and the difficulty of experimentally evaluating a variants clinical significance, many of the thousand variants that can be generated by clinical tests are reported as variants of unknown clinical significance. However, the creation of population-scale variant databases can significantly improve clinical variant interpretation. Specifically, pathogenicity prediction for novel missense variants can now utilize features describing regional variant constraint. Constrained genomic regions are those that have an unusually low variant count in the general population. Several computational methods have been introduced to capture these regions and incorporate them into pathogenicity classifiers, but these methods have yet to be compared on an independent clinical variant dataset. Here we introduce one variant dataset derived from clinical sequencing panels, and use it to compare the ability of different genomic constraint metrics to determine missense variant pathogenicity. This dataset is compiled from 17,071 patients surveyed with clinical genomic sequencing for cardiomyopathy, epilepsy, or RASopathies. We further utilize this dataset to demonstrate the necessity of disease-specific classifiers, and to train PathoPredictor, a disease-specific ensemble classifier of pathogenicity based on regional constraint and variant level features. PathoPredictor achieves an average precision greater than 90% for variants from all 99 tested disease genes while approaching 100% accuracy for some genes. Accumulation of larger clinical variant datasets and their utilization to train existing pathogenicity metrics can significantly enhance their performance in a disease and gene-specific manner.

genomics↗