Exome sequencing of ion channel genes reveals complex profiles confounding personal risk assessment in epilepsy

Abstract

Ion channel mutations are an important cause of rare Mendelian disorders affecting brain, heart, and other tissues. We performed parallel exome sequencing of 237 channel genes in a well-characterized human sample, comparing variant profiles of unaffected individuals to those with the most common neuronal excitability disorder, sporadic idiopathic epilepsy. Rare missense variation in known Mendelian disease genes is prevalent in both groups at similar complexity, revealing that even deleterious ion channel mutations confer uncertain risk to an individual depending on the other variants with which they are combined. Our findings indicate that variant discovery via large scale sequencing efforts is only a first step in illuminating the complex allelic architecture underlying personal disease risk. We propose that in silico modeling of channel variation in realistic cell and network models will be crucial to future strategies assessing mutation profile pathogenicity and drug response in individuals with a broad spectrum of excitability disorders.

Figure 1. Multiple variants render each individual channotype unique

A. Low resolution (gray background) 3D representations illustrating the most extreme channotypes present in the study cohort (two cases and two controls, each with >450 SNPs). The columns list the channel subunit genes in alphabetical order (ANK – SCN) and the rows list validated individual SNP identifiers organized alphabetically by type (3’UTR – promoter). An enlargement at left in teal is presented for clarity and scale. The gene dosage of the minor (variant) allele for a SNP is denoted by a bar (tall red=Homozygous Minor Allele; short blue = Heterozygous Minor Allele). Sparsely populated regions present in all four channotypes reflect low frequency novel SNPs. B. Histogram of all individuals by cohort with the total number of SNPs in the individual plotted against the total number of SNPs in the channotype that are heterozygous or homozygous. The affected and control cohorts show similar allelic dosages with increasing SNP count. C. Histogram of all individuals within each cohort showing the total number of SNPs per individual plotted against number of nsSNPs contained in the channotype. The number of nsSNPs in a channotype increases with increasing total SNP count in both populations. The individual channotypes profiled in A. (A1,A2,C1,C2) are indicated in the histograms.

Figure 2. Known monogenic human epilepsy (hEP) genes populated with missense and nonsense variants found in our study cohort

The protein products of twelve ion channel genes known to cause monogenic epilepsy are shown schematically. Validated missense and nonsense SNPs discovered by profiling are represented by circles marking the nearest amino acid location as determined by comparative multiple alignment. Presence of a SNP denoted by the fill pattern (filled circle = in affected only; open circle = in controls only; half filled circle = SNP is present in both groups). The nsSNPs in dbSNP are colored black, novel nsSNPs from our study are red, and the nonsense SNPs are colored blue.

Figure 3. Channotype complexity comparisons for individuals with 3 nsSNPs in known hEP genes reveal unique patterns

A. Individual channotype profiles of four cases and four controls each having 3 missense mutations among 4 known hEP genes (CACNA1A, SCN1A, CLCN2 and KCNQ2), but in distinct patterns that cannot be described by a simple numerical count of “load”. Affected 1, Affected 2, Control 1 and Control 2 all have 3 missense mutations in three hEP genes. Control 1 and Affected 1 share the same channotype profile with identical mutations in SCN1A, CLCN2 and KCNQ2. Affected 3 and Control 3 both have 3 mutations in 2 hEP genes, and Affected 4 and Control 4 have the same 3 nsSNPs in the single CLCN2 gene. B. The total number of affected or control individuals with nsSNPs in known hEP genes showing the proportion of individuals with 1, 2 or 3 nsSNPs in the same hEP gene. C. Population distribution of nsSNP load found in the hEP genes. Both affected and control individuals have multiple variants within known epilepsy causing disease genes. D. Histogram of all individuals by cohort with the total number of nsSNPs per individual plotted against number of nsSNPs in the known hEP genes. Affected and control channotypes cannot be reliably distinguished by nsSNP count in hEP genes. .

Figure 4. Intragenic and epistatic variants of known hEP genes underlie individual complexity

A. A 3D representation illustrating unique missense channotype profiles from 14 individuals of the voltage-gated calcium (CACN) and sodium (SCN) genes for cases (n=7) and controls (n=7) selected from less extreme (85th percentile) profiles for nsSNP load (60-80 nsSNPs in Fig1C). The columns list the channel subunit with the pore forming alpha subunits listed before accessory subunits and the rows represent the same individual channotype across both gene families. The number of missense (nsSNP) mutations present in the gene is denoted by bar height (grey = no nsSNP; short yellow = 1 nsSNP; medium red = 2 nsSNP; tall blue = 3 nsSNP). B. The total number of affected or control individuals with nsSNPs in the 26 voltage gated calcium channel genes showing the proportion of individuals with multiple SNPs in the same gene. C. Population distribution of nsSNP load in the calcium channel genes by subunit type. Individuals in both populations have multiple variants in one or more subunit genes, with the highest nsSNP load being observed in a control individual.

Figure 5. Computational model of a single hippocampal neuron simulates the effect of varying the allelic pattern (gain/loss of function) in a “two-hit” (two distinct channel genes) and a “three hit” functional mutation profile

A simplified Traub (1991) CA3 pyramidal neuron was used to test the effects of mutational pattern in a “two-hit” load paradigm. A and B, the gain (up arrow) or loss (down arrow) of function (defined as a 50% change in peak conductance) of essential ionic currents were modeled in combination. A change in Nav conductance is complimented by a change in corresponding Cav (A) or Kv (B) conductance. The ‘normal’ (default conductance) firing behavior is shown in red traces, the input stimulus of 0.1nA and scale bar is the same for all panels. Each simulation produces a strikingly different firing pattern. C. Excitability change incorporating an additional mutant channel shows further dependence on the allelic pattern. When the two-hit model (50% increase in Cav and Kv conductance) is supplemented by a third hit in Nav, where a simulated variant showing a gain (250% increase) or a loss (75% reduction) of Nav conductance is added, the neuron generates spontaneous (untriggered) burst discharges, however the second burst is shifted toward the normal interburst interval when Nav is increased (above), and greatly prolonged with reduced action potential firing when Nav is decreased (below). The input stimulus of 0.2nA and scale bar is the same for all panels.