SLC6A1 variant pathogenicity, molecular function, and phenotype: a genetic and clinical analysis

in Brain: a Journal of Neurology (2023)

Genetic variants in the SLC6A1 gene can cause a broad phenotypic disease spectrum by altering the protein function. Thus, systematically curated clinically relevant genotype-phenotype associations are ... [more ▼]

Genetic variants in the SLC6A1 gene can cause a broad phenotypic disease spectrum by altering the protein function. Thus, systematically curated clinically relevant genotype-phenotype associations are needed to understand the disease mechanism and improve therapeutic decision-making. We aggregated genetic and clinical data from 172 individuals with likely pathogenic/pathogenic (lp/p) SLC6A1 variants and functional data for 184 variants (14.1% lp/p). Clinical and functional data were available for a subset of 126 individuals. We explored the potential associations of variant positions on the GAT1 3D structure with variant pathogenicity, altered molecular function, and phenotype severity using bioinformatic approaches. The GAT1 transmembrane domains 1, 6, and extracellular loop 4 (EL4) were enriched for patient over population variants. Across functionally tested missense variants (n = 156), the spatial proximity from the ligand was associated with loss-of-function in the GAT1 transporter activity. For variants with complete loss of in vitro GABA uptake, we found a 4.6-fold enrichment in patients having severe disease vs. non-severe disease (P = 2.9e-3, 95% CI: 1.5 - 15.3). In summary, we delineated associations between the 3D structure and variant pathogenicity, variant function, and phenotype in SLC6A1-related disorders. This knowledge supports biology-informed variant interpretation and research on GAT1 function. All our data can be interactively explored in the SLC6A1 Portal (https://slc6a1-portal.broadinstitute.org/). [less ▲]

Genotype-phenotype correlations in SCN8A-related disorders reveal prognostic and therapeutic implications

E-print/Working paper (2021)

We report detailed functional analyses and genotype-phenotype correlations in 433 individuals carrying disease-causing variants in SCN8A, encoding the voltage-gated Na+ channel NaV1.6. Five different ... [more ▼]

We report detailed functional analyses and genotype-phenotype correlations in 433 individuals carrying disease-causing variants in SCN8A, encoding the voltage-gated Na+ channel NaV1.6. Five different clinical subgroups could be identified: 1) Benign familial infantile epilepsy (BFIE) (n=17, normal cognition, treatable seizures), 2) intermediate epilepsy (n=36, mild ID, partially pharmacoresponsive), 3) developmental and epileptic encephalopathy (DEE, n=191, severe ID, majority pharmacoresistant), 4) generalized epilepsy (n=21, mild to moderate ID, frequently with absence seizures), and 5) affected individuals without epilepsy (n=25, mild to moderate ID). Groups 1-3 presented with early-onset (median: four months) focal or multifocal seizures and epileptic discharges, whereas the onset of seizures in group 4 was later (median: 39 months) with generalized epileptic discharges. The epilepsy was not classifiable in 143 individuals. We performed functional studies expressing missense variants in ND7/23 neuroblastoma cells and primary neuronal cultures using recombinant tetrodotoxin insensitive human NaV1.6 channels and whole-cell patch clamping. Two variants causing DEE showed a strong gain-of-function (GOF, hyperpolarising shift of steady-state activation, strongly increased neuronal firing rate), and one variant causing BFIE or intermediate epilepsy showed a mild GOF (defective fast inactivation, less increased firing). In contrast, all three variants causing generalized epilepsy induced a loss-of-function (LOF, reduced current amplitudes, depolarising shift of steady-state activation, reduced neuronal firing). Including previous studies, functional effects were known for 165 individuals. All 133 individuals carrying GOF variants had either focal (76, groups 1-3), or unclassifiable epilepsy (37), whereas 32 with LOF variants had either generalized (14), no (11) or unclassifiable (5) epilepsy; only two had DEE. Computational modeling in the GOF group revealed a significant correlation between the severity of the electrophysiological and clinical phenotypes. GOF variant carriers responded significantly better to sodium channel blockers (SCBs) than to other anti-seizure medications, and the same applied for all individuals of groups 1-3.In conclusion, our data reveal clear genotype-phenotype correlations between age at seizure onset, type of epilepsy and gain- or loss-of-function effects of SCN8A variants. Generalized epilepsy with absence seizures is the main epilepsy phenotype of LOF variant carriers and the extent of the electrophysiological dysfunction of the GOF variants is a main determinant of the severity of the clinical phenotype in focal epilepsies. Our pharmacological data indicate that SCBs present a therapeutic treatment option in early onset SCN8A-related focal epilepsy. [less ▲]

Predicting Functional Effects of Missense Variants in Voltage-Gated Sodium and Calcium Channels

E-print/Working paper (2019)

Malfunctions of voltage-gated sodium and calcium channels (SCN and CACNA1 genes) have been associated with severe neurologic, psychiatric, cardiac and other diseases. Altered channel activity is ... [more ▼]

Malfunctions of voltage-gated sodium and calcium channels (SCN and CACNA1 genes) have been associated with severe neurologic, psychiatric, cardiac and other diseases. Altered channel activity is frequently grouped into gain or loss of ion channel function (GOF or LOF, respectively) which is not only corresponding to clinical disease manifestations, but also to differences in drug response. Experimental studies of channel function are therefore important, but laborious and usually focus only on a few variants at a time. Based on known gene-disease-mechanisms, we here infer LOF (518 variants) and GOF (309 variants) of likely pathogenic variants from disease phenotypes of variant carriers. We show regional clustering of inferred GOF and LOF variants, respectively, across the alignment of the entire gene family, suggesting shared pathomechanisms in the SCN/CACNA1 genes. By training a machine learning model on sequence- and structure-based features we predict LOF- or GOF- associated disease phenotypes (ROC = 0.85) of likely pathogenic missense variants. We then successfully validate the GOF versus LOF prediction on 87 functionally tested variants in SCN1/2/8A and CACNA1I (ROC = 0.73) and in exome-wide data from > 100.000 cases and controls. Ultimately, functional prediction of missense variants in clinically relevant genes will facilitate precision medicine in clinical practice. [less ▲]