Current prediction algorithms fail to predict the effects of nsSNPs due in part to the inability of models to account for the many factors that prevent complete penetrance—noise from complicating genetic and environmental risk factors buries the protein-specific functional signal. To help illustrate this point I curated a set of nearly 1,400 nsSNPs from the available literature on SCN5A, including 304 variants that were at least partially functionally characterized. The results can be summarized as follows: There is a range of tolerated NaV1.5 perturbation. There is also a range of perturbation that is not well tolerated. In both these extremes, clinical presentation is largely homogeneous. However, modest perturbations result in varied clinical presentations that are heterogeneous. This trend holds when comparing among different variants, but also holds within the population of carriers of a single variant (Table 1). This highlights that SCN5A variant function is informative to an accurate risk of clinical presentation, probabilistically, and in silico models that can accurately predict changes in function may be of greater utility in clinical diagnosis than models that only predict binary "pathogenic" or "benign".
Table 1. Example of intravariant (hetero/homo)geneity of clinical presentation
|Variant||Peak Current||# Unaffected||# BrS1|
My laboratory addresses the challenge of VUSs by blending experimental and computational strategies: 1) structure and flexibility-induced changes from selected ion channel variants using a combination of Rosetta modeling, molecular dynamics in AMBER, and nuclear magnetic resonance (NMR) 2) experimental deep mutational scanning data sensitive to trafficking/functionally defective ion channel variants. 3) functional effects of variants in human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs). These technologies enable us to construct predictive models of ion channel phenotypes and validate the resulting predictions.
Computational and experimental structural biology. The ultimate goal of generating phenotypes of any ion channel nsSNP is only currently possible in silico. My laboratory experimentally structurally characterizes domains of ion channels using NMR. Further, we develop fully solvated, full-atom trajectories of ion channels for comparison with NMR experimental data and for high-throughput variant flexibility determination in silico. The advantage of this approach is the capability of more high-throughput parallel running of variants in silico than could be concievably determined experimentally.
Deep mutational scanning. Computational approaches will never eclipse the need for experimental data of some resolution. To complement large-scale variant characterization done computationally, my laboratory assays functionality of all codon substitutions within targeted segments in LQTS-implicated ion channels. This technology enables very high-throughput analysis of variants at relatively low resolution.
hiPSC-CM. The relationship between function of ion channel variants characterized by heterologous expression and resulting action potential perturbations in people is not always straight forward. Though the there is a clear correlation between SCN5A variant perturbation measured by heterologous expression and clinical presentation, there are variants where relatively high minor allele frequency (MAF, as measured by gnomAD) conflicts with the severity of functional perturbation. This begs the question of whether the degree of perturbation is tolerable or whether the heterologous expression data are not representative of the true phenotypes in human cardiomyocytes. My laboratory tests ion channel variant phenotypes in the hiPSC-CM model system. This model system allows for a direct assessment of the variant-specific perturbation against isogenic controls.
This work is funded by National Institutes of Health grant R00 HL135442 and Vanderbilt University Medical Center.