Somatic SLC35A2 mosaicism correlates with clinical findings in epilepsy brain tissue

Disease presentation and clinical findings

The patient is a 3-year-old male who presented at age 9 months with West syndrome, a severe form of epilepsy characterized by infantile spasms, an abnormal EEG pattern termed hypsarrhythmia, and developmental delay. The etiologies for West syndrome are multifactorial and may include genetic or structural abnormalities.²⁰ A commercially available epilepsy-specific gene panel using patient blood did not identify any pathogenic variants, and the patient's initial structural brain MRI was normal. His EEG revealed hypsarrhythmia with a left posterior quadrant predominance of epileptiform activity and generalized epileptic spasms. He was treated with adrenocorticotropin hormone with initial remission, followed 5 months later by recurrence and remission with prednisolone therapy. At age 2.5 years, epileptic spasms recurred along with focal tonic seizures, which were refractory to several different antiseizure medications. At that time, he underwent long-term EEG monitoring, FDG-PET, MRI, and neurodevelopmental testing as part of an evaluation for refractory seizures. New findings included seizures with left posterior quadrant onset seizures, a brain MRI finding suggestive of a temporal lobe dysplasia, and FDG-PET hypometabolism in the left temporoparietal region. This was followed by placement of subdural grids and strips covering the left posterior frontal, temporal, parietal, and occipital lobes. Ictal findings, defined as spike and wave and gamma frequency activity, were diffuse in the electrodes over the left temporal and parieto-occiptal regions, including the mesial temporal contacts (figure 1). A gradient was present in the interictal epileptiform activity, where spikes were nearly continuous or abundant in the contacts over the hippocampus and temporal lobe contacts and frequent or occasional in contacts over the parietal and portions of the occipital lobe. Because of the diffuse nature of the ictal pattern involving the left posterior quadrant, the patient underwent a grid-based resection of presumed epileptic zones, including removal of the left temporal lobe, left amygdala, left hippocampus, left inferior parietal lobe, and left occipital lobe (table e-1, links.lww.com/NXG/A273). Histologic examination of the resected tissue specimens showed cortical dyslamination with areas featuring neurons arranged in microcolumns (occipital lobe) and areas with ill-defined hexalaminar architecture (temporal and occipital lobes), consistent with FCD type 1c according to the International League Against Epilepsy classification system.¹¹ The amygdala and hippocampus showed fragments of gray and white matter with gliosis. In summary, figure 2 shows neuroimaging, EEG, and histopathology of 2 vastly differentially affected brain regions, the hippocampus and occipital lobe.

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Figure 1 Epileptic spasm and intracranial grid location

(A) Ictal recording of typical epileptic spasms. The spikes and high-frequency activity at ictal onset were broadly distributed in the mesial temporal, frontotemporal, inferior parietal, and occipital contacts (sensitivity: 75 uV, low-frequency filter: 5.3 Hz; high-frequency filter: 500 Hz). (B) Placement of the grid and strips (blue) over the left frontal, temporal, parietal, and occipital lobes. (C) Predominant ictal onset (red) and rapid propagation (orange) over a broad region. (D) Location of the tissue samples and spike quantification. FT = frontotemporal; MT = mesial temporal; Occ = occipital.

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Figure 2 Neuroimaging, EEG, and histopathology of differentially affected hippocampus and parietal/occipital lobe

(A) Hippocampus: T2-weighted coronal MRI of the brain demonstrates increased signal within the left temporal white matter with circling of the asymmetric gray-white matter blurring on the left temporal lobe (top left). FDG-PET fused with MRI demonstrates focal area of asymmetrically decreased uptake within the left temporal lobe and hippocampus area; arrows point to the left temporal lobe and left hippocampal region (top right). Intracranial EEG demonstrates high-amplitude spikes (asterisks) abundantly in the hippocampus contacts (bottom left). Histology image at 100×; H&E-stained section from hippocampus shows expected cytoarchitecture (bottom right). (B) Parietal/occipital lobe: T1-weighted coronal MRI of the brain demonstrates no focal abnormality in the left parietal lobe (top left). FDG-PET fused with MRI demonstrates focal area of asymmetrically decreased uptake within the left parietal lobe; arrows point to the left parietal lobe (top right). Intracranial EEG demonstrates high-amplitude spikes (asterisks) only occasionally in the occipital contacts (bottom left). Histology image at 40×; H&E-stained section shows cortical dyslamination with neurons of the occipital neocortex arranged in microcolumns (arrowheads). FDG = fluorodeoxyglucose; H&E = hematoxylin and eosin.

Exome sequencing of brain tissues reveals somatic mosaicism in SLC35A2

DNA was extracted from 6 brain tissues from different regions within the same patient brain and from peripheral blood mononuclear cells as a matched comparator. All brain tissues were from suspected affected areas and resected during the same surgery. We performed exome sequencing initially on the 6 brain tissues plus matched blood to search for inherited (germline) variation and acquired (somatic) variation in coding regions, including single nucleotide, insertion/deletion, and copy number variants. For the temporal lobe and occipital lobe, we sequenced 2 different samples removed from the same brain region. Mean, on-target exome sequencing read coverage depth was 222x for matched blood and 331x (range: 282x–384x) for brain tissues (table e-2, links.lww.com/NXG/A273). Our analysis of inherited variants yielded 3 variants that merited further review (table e-3, links.lww.com/NXG/A273). Two variants were within genes unrelated to the patient's phenotype. The third variant was in DYNC1H1 and was previously identified in our patient, as well as the patient's unaffected mother, through clinical genetic testing and reported as a variant of unknown significance (VUS). De novo variants in DYNC1H1 have been identified in individuals with malformations of cortical development and in individuals with epileptic encephalopathies, including West syndrome.^21,22 Because of the inherited status of this variant, we do not believe that it is associated with the patient's phenotype and assessed it as a VUS.

Our analysis of acquired, somatic variants revealed 46 variants that met the initial filtering criteria, but after manually reviewing these in the IGV to discount strand bias or other sequencing artifacts, we determined that 41/46 suspect variants were sequencing artifacts. The 5 remaining candidate somatic mosaic variants are listed in table e-4, links.lww.com/NXG/A273. We identified a likely causal variant in the solute carrier family 35 member A2 (SLC35A2) gene, which was absent in the matched blood comparator and present in a range of VAFs from 0.6% to 27.7% in the resected brain tissues (table 1). The X-linked NM_005660.3:c.634_635delTC (p.Ser212LeufsTer9) variant is predicted to cause a frameshift in the transmembrane domain and a premature stop codon 9 amino acid downstream. This variant has not been reported in the Genome Aggregation Database of 150,647 alleles from the general population.²³ We found 1 report of this somatic variant in a patient with intractable epilepsy.²⁴ We assessed the p.Ser212LeufsTer9 variant as pathogenic according to the ACMG/AMP guidelines by assigning the following criteria as evidence of pathogenicity: PVS1 (null variant in a gene where loss of function is a known mechanism of disease), PS2 (de novo variant in a patient with the disease and no family history; applied due to proven somatic mosaicism), and PM2 (absence from large-scale control population databases).¹⁵

Deep, targeted sequencing of SLC35A2 confirms a wide range of VAFs in patient brain tissue

We used 2 different targeted sequencing approaches to confirm the SLC35A2 variant in DNA from 6 resected brain regions and to produce high-depth sequencing data at the variant site as a means of correlating the prevalence of the variant in the cells obtained from each region. First, we used a PCR-based approach (libricon) to selectively amplify a ∼100 bp region that included the variant of interest and constructed a library from the resulting amplicons. Our second variant confirmation approach included a custom direct sequencing panel NND, designed to capture and sequence all coding regions of the SLC35A2 gene. Both targeted approaches confirmed the presence of the SLC35A2 variant at varying proportions in different brain tissues (figure 3A).

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Figure 3 SLC35A2 c.634_635delTC VAFs among different sequencing methods

(A) Comparison of SLC35A2 c.634_635delTC VAFs in 6 brain tissues and blood comparator from the affected patient, using 3 different sequencing techniques. Average sequencing depth at the SLC35A2 variant position for each method is shown in parentheses in legend. The apparent presence of the variant at <1% VAF in the blood sample for the libricon approach is likely due to the high error rate of this PCR-based approach and the high read depth achieved during sequencing. (B) VAFs in 12 brain and 1 matched blood tissue using the NND SLC35A2 targeted sequencing kit. (C) Comparison of VAFs in DNA and RNA from 6 different brain tissues using the NND SLC35A2 targeted sequencing kit. Only nucleic acids from high-quality, frozen tissue samples were used for targeted RNA sequencing. Average sequencing depth for each method is shown in parentheses in legends. NND = NEBNext Direct; VAF = variant allele fraction.

The NND approach revealed variant read percentages ranging from 4.2% to 19.5%, which were highly similar to our initial exome sequencing allele percentages (figure 3A). NND uses UMIs added before PCR amplification, permitting the identification and removal of PCR duplicates after sequencing. Therefore, on the basis of these assay attributes, we chose NND as the methodology to confirm the SLC35A2 variant in 6 additional brain tissues, which had been archived in FFPE blocks from the patient's initial surgery. The variant was present in all 6 additional brain tissues at a range of percentages (figure 3B). Overall, the hippocampus tissue (section C) had the highest proportion of the SLC35A2 variant allele, whereas portions of the occipital lobe (sections D2 and F) were among the lowest proportions.

Our initial transcriptome sequencing of total RNA yielded low read depth at the SLC35A2 c.634_635delTC variant site. In addition, the expression level of SLC35A2 in all brain tissues was very low. FPKM values for SLC35A2 expression ranged from 3.2 to 3.9 across all tissues. As such, we were unable to correlate variant expression from transcriptome sequencing to the observed variability in allele proportions from the DNA data. Therefore, we performed deep sequencing using the NND targeted panel on brain-extracted RNA from 6 of the brain regions to determine whether the c.634_635delTC variant is expressed. Average read depth in RNA at the variant site was 5,206x for all tissues, and the VAF varied from 1.5% to 7.7%, demonstrating much lower proportions than were detected from DNA sequencing (figure 3C). There was no clear correlation between DNA and RNA VAFs among all tissues.

Somatic SLC35A2 VAF correlates with severity of electrophysiologic and radiographic findings

The SLC35A2 VAF, based on high-depth NND targeted sequencing of 12 brain regions obtained at surgery, ranged from 4.2% (occipital lobe, section D2) to 19.5% (hippocampus, section C). As shown previously in figure 2, intracranial EEG was consistent with seizure onset from the hippocampus, which had the highest VAF, but showed only occasional seizure onset from the occipital lobe, one of the lowest VAFs. This observation prompted us to quantify interictal epileptiform discharges (spikes) for all involved tissues (table 2). Average spikes per minute, a standard measure of the severity of abnormal neurophysiologic activity, correlated with the proportions of SLC35A2 variant allele in these different brain tissues (Pearson r = 0.881, p = 0.0087), with the highest rate of interictal epileptiform discharges (32.8 spikes/min) observed in the tissue with the highest VAF (hippocampus, 19.5%). In addition, as shown in table 2, the trend in correlation between VAFs and IED activity is reflected in a binary descriptor of seizure onset relative to brain region and to imaging-based analyses from MRI and FDG-PET neuroimaging modalities. Electrophysiologic and neuroimaging findings generally correlated with higher VAF compared with tissues with a lower VAF, suggesting that the presence of the somatic mosaic SLC35A2 variant is contributing to the seizure phenotype. We compare these clinical findings with findings from a previously published patient with the same SLC35A2 somatic variant in table 3.