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Maher, Bridget, Taylor, Megan, Stuart, Shani, Okolicsanyi, Rachel, Roy, Bishakha, Sutherland, Heidi, Haupt, Larisa,& Griffiths, Lyn (2013) Analysis of 3 common polymorphisms in the KCNK18 in an Aus- tralian Case-control cohort. Gene, 528(2), pp. 343-346.

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Notice: Please note that this document may not be the Version of Record (i.e. published version) of the work. Author manuscript versions (as Sub- mitted for peer review or as Accepted for publication after peer review) can be identified by an absence of publisher branding and/or typeset appear- ance. If there is any doubt, please refer to the published source. https://doi.org/10.1016/j.gene.2013.07.030 Analysis of 3 common polymorphisms in the KCNK18 gene in an Australian Migraine Case-control cohort

+ + Maher BH , Taylor M , Stuart S, Okolicsanyi RK, Roy B, Sutherland HG, Haupt LM, Griffiths LR

+ Joint first authors Genomics Research Centre, Griffith Health Institute, School of Medical Science, Griffith University Gold Coast, Parklands Drive, Southport, Queensland 4215, Australia.

Corresponding author: Professor Lyn Griffiths, Genomics Research Centre, Griffith Health Institute, Griffith University, Queensland 4222, Australia; Phone +61 7 5552 8664, fax +61 7 5552 9081, e-mail: [email protected]

Keywords: Migraine, Migraine with Aura, KCNK18, TRESK

Conflict of Interest: The authors declare no conflict of interest

Abstract Migraine is a common neurological disorder characterised by temporary disabling attacks of severe head pain and associated disturbances. There is significant evidence to suggest a genetic aetiology to the disease however few causal mutations have been conclusively linked to the migraine subtypes Migraine with (MA) or without Aura (MO). The KCNK18 gene, coding the (TRESK), is the first gene in which a rare mutation resulting in a non-functional truncated has been identified and causally linked to MA in a multigenerational family. In this study, three common polymorphisms in the KCNK18 gene were analysed for genetic variation in an Australian case-control migraine population. No association was observed for the polymorphisms examined with the migraine phenotype or with any haplotypes across the gene. Therefore even though the KCNK18 gene is the only gene to be causally linked to MA our studies indicate that common genetic variation in the gene is not a contributor to MA.

Introduction Migraine is a common disorder characterised by substantial head pain frequently associated with a variety of temporary neurological disturbances and associated symptoms such as photophobia, phonophobia and nausea. Substantial evidence exists to support a significant genetic contribution to the aetiology of the migraine subtypes Migraine with and without aura (MA and MO respectively) (Gervil et al 1999, Mulder et al 2003, Stewart et al 2006). Recently, the first mutation to be causally linked to the MA subtype was identified in a large multigenerational pedigree. This mutation resides in the KCNK18 gene on 10q25 that codes the TWIK-related spinal cord potassium channel (TRESK) a member of the two-pore domain potassium (K2P) channel family (Lafreniere et al 2010).

Ion channels and transporters have been of particular interest in migraine genetic studies primarily due to their role in the rare autosomal dominant form of MA known as Familial Hemiplegic Migraine (FHM). Early linkage studies identified mutations in three independent (CACNA1A, ATP1A2 and SCN1A) that are all causal for FHM (De Fusco et al 2003, Dichgans et al 2005, Ophoff et al 1996). It is proposed that mutations in these three FHM genes can independently contribute to increased glutamate and potassium concentrations at the synapse resulting in decreased threshold for cortical spreading depression (van den Maagdenberg et al 2004). These findings along with subsequent functional studies have shown that ion channels are important regulators of neuronal hyperexcitability and cortical spreading depression with the mechanisms of both linked to migraine occurrence.

The potassium channel TRESK was initially identified as the only ion channel gene of 52 genes coded in a migraine study linkage peak at 10q25.2-.3. The function of TRESK in migraine pathogenesis is proposed to include roles in controlling cellular excitability and pain pathways (Huang et al 2008, Pietrobon & Moskowitz 2013). This role for TRESK is supported by expression studies through in situ hybridisation, immunohistochemistry, Q-PCR and Northern analysis in murine models localising the protein in biologically relevant regions of the CNS and brain including the Dorsal root ganglion and the trigeminal ganglion (Dobler et al 2007, Enyedi et al 2012, Lafreniere & Rouleau 2011, Sano et al 2003, Yoo et al 2009).

The causally linked mutation identified in the KCNK18 gene is a 2bp frameshift mutation (F139WfsX24) that causes premature protein truncation. This mutation segregated perfectly with the MA phenotype in a multigenerational family and was not identified in the associated panel of control samples (n=80). The mutation was shown to cause a non-functional protein in addition to causing a dominant-negative downregulation of the wildtype channel (Lafreniere et al 2010). In addition to this mutation, a number of other missense mutations have been identified within the gene, some of which – such as A34V and C110R - similarly cause complete loss of function and down-regulation of the wildtype channel. However, these mutations have been observed in both migraine and non-migraineurs suggesting that the influence of TRESK in migraine pathogenesis is complex and may be modulated by other genetic or environmental effects (Andres-Enguix et al 2012).

The aim of this study was to determine if an association between common polymorphisms in the KCNK18 gene and migraine exists in a case-control population. The gene spans a 12kb genomic region and codes the 384 amino acid TRESK protein across 3 exons. Three common variants were chosen for investigation in the KCNK18 gene; rs363314, rs1617136 and rs963975, which are located within introns 1 and 2 (see Figure 1).

Methods Population: A total of 736 Migraine cases and age (+/-5yrs) and gender matched controls were recruited from the South East Queensland region Australia. All participants were of Caucasian origin, and cases were diagnosed as having MA or MO based on criteria specified by the International Headache Society. Blood samples obtained from patients were collected through the Genomics Research Centre clinic and DNA was extracted using a salting out method (Miller S.A et al 1988). Approval for the study protocol was acquired from the Griffith University’s Ethics Committee for Experimentation on Humans.

Molecular Analysis: Matrix-assisted desorption/ionisation time-of-flight (MALDI-TOF) mass spectrometry was used to genotype the SNPs rs963975 and rs363314 in each sample in a multiplexed reaction. The multiplex was designed using the online Assay Design Suite available at mysequenom.com. The Sequenom MassArray 4 instrument and accompanying Typer 4.0 software was used to carry out all genotyping work. Genotyping was confirmed independently using high resolution melt analysis (rs963975), or restriction fragment length polymorphism (rs363314) analysis and Sanger sequencing on the ABI3130 (Life Technologies).

The SNP rs1617136 could not be designed into the multiplex for genotyping on the Sequenom MassArray 4. Therefore this SNP was genotyped independently using RFLP and independent confirmation by Sanger Sequencing on the ABI3130 (Life Technologies). Due to the low throughput method used the SNP was genotyped in a subset of the population consisting of 284 migraine cases age (+/-5yrs) and gender matched to 284 controls. Primers used for the RFLP and sequencing assays were F:5’-TTCCAGAGCCTGAACCTTTCACCA-3’ and R: 5’-ACTGTGATCTTTGGGCACCAGCTA-3’. The RFLP used the restriction enzyme ClaI to cut at the G allele resulting in two fragments of 284bp and 123bp visualised on a 3% agarose gel against the 407bp uncut fragment which occurs with the A allele.

Statistical Analysis: Prior to statistical analysis samples were filtered for QC. For SNPs rs963975 and rs363314 736 samples were genotyped, however 25 samples failed QC due to poor genotyping call rates (3%) and 26 samples were excluded from analysis as duplicate or triplicate controls of other samples after confirmation that genotyping results matched across samples. After filtering 685 samples remained (167 male and 518 female) divided into 340 unique cases and 345 controls.

For SNP rs1617136 a subset of 568 samples were genotyped including 20 samples that were included for genotyping for QC purposes (as duplicates or triplicates) and were removed prior to analysis. After filtering 548 samples remained (150 male and 398 females) divided into 274 unique cases and 274 controls.

Plink was used to perform a basic association analysis (Purcell et al 2007) and haplotype analysis. Hardy Weinberg equilibrium was calculated for each SNP in case and control cohorts to check for genotyping error and a Chi Square test was used to determine if SNPs were significantly associated with migraine. Migraine cases were also subdivided and compared to controls according to the subtypes MA and MO. Analysis according to gender was also performed. Due to multiple testing the Bonferroni threshold was set at P=0.003. The minor allele frequency was calculated and compared to European HapMap frequencies. Haploview was used to determine linkage disequilibrium blocks across the KCNK18 gene (Barrett et al 2005).

Results Three intronic SNPs in the KCNK18 gene were tested for association with the migraine phenotype in an Australian Caucasian case-control population. The selected polymorphisms capture 64% of the common variation (MAF>0.01) across the gene in the HAPMAP CEU population at r2 ≥0.8 (mean r2 0.92). MAF of both case and controls cohorts for the intronic SNPs rs1617136, rs963975 and rs363314 SNPs were consistent with HapMap CEU frequency data (Table 1) and Hardy Weinberg Equilibrium (HWE) analysis determined that all SNPs were in HWE for both case and control populations (P>0.05).

Overall, the allelic frequencies did not vary significantly between the migraine and control cohorts for the polymorphisms examined. Chi Square analysis confirmed that no genotypic or allelic association of these SNPs with the migraine phenotype exists in this cohort (P>0.05 - see Table 1). Further analysis by migraine subtype (MA or MO) and gender similarly did not show any significant association. Although the SNP rs1617136 was only analysed in a subset of the larger population due to the low throughput method used, identical MAFs were observed for both case and control populations (MAF = 0.38). Thus it is unlikely that association would be observed through additional genotyping in the slightly larger population. Haplotype analysis similarly did not detect any significant differences in haplotype frequencies across the gene between cases and controls (See Table 2) or with the Migraine subtypes.

Discussion Migraine genetic studies have provided significant evidence to implicate ion channels in the pathogenesis of the disorder. Evidence from FHM studies as well as genomewide association studies concerning typical migraine suggest that genes involved in ion homeostasis and neurotransmitter release and regulation are important in migraine pathology. In addition to the FHM genes, mutations

+ - in other ion channels have been reported. These include the SLC4A4 gene, encoding a Na -HCO3 contransporter NBCe1 (Suzuki et al 2010), affecting neuronal excitability through regulation of pH in the brain. The genes PGCP, MTDH (Anttila et al 2010) and LRP1 (Chasman et al 2011) have also all been implicated through GWAS and are involved in glutamate homeostasis, similarly TRPM8 a cation channel (Chasman et al 2011) has been implicated in GWAS studies of both MA and MO. Finally a pedigree-based GWAS using the genetic isolate of Norfolk Island also implicated SNPs within the neurotransmitter-related ADARB2, GRM7 and HTR7 genes (Cox et al 2012).

Despite the plethora of evidence supporting ion channels and transporters for a potential role in migraine, the potassium channel coded by the KCNK18 gene is the first to be causally linked through functional studies to MA. Lafreniere and colleagues demonstrated that the identified frameshift mutation is non-functional in Xenopus oocytes and that the truncated protein could still assemble as homodimers with wildtype subunits causing a dominant-negative suppression of activity (Lafreniere et al 2010). Additional functional studies using mouse knock out models has also demonstrated dorsal root ganglion neurons have a lower activation threshold suggesting that mice without a functional channel showed neuronal hyperexcitability (Dobler et al 2007) providing a plausible link between mutations within this channel and migraine susceptibility.

This study sought to determine any association between common polymorphisms in the KCNK18 gene and migraine phenotype in a case-control population. Overall there was no association observed with the three common SNPs (rs1617136, rs363314 and rs963975) examined. While the results of this study do not encourage further investigation of these particular polymorphisms in a similar case-control association study, it does not detract from the strong evidence supporting KCNK18 as a contributor to migraine pathology. In contrast the results of this study may support the growing hypothesis that rare family specific mutations significantly contribute to migraine in the general population and that testing common polymorphisms alone may not be sufficient to detect these associations.

Overall the results of this study and others combine to suggest that mutations within the KCNK18 gene that contribute significantly to migraine are likely to be private, familial causal mutations that cause dysregulation of potassium homeostasis and neuronal hyperexcitability and therefore predisposition to migraine. To further investigate this gene identification of additional families with causally linked mutations in TRESK or TRESK related will help to explain the exact role TRESK is playing in migraine. In addition, genes within this pathway and those regulating TRESK should be further investigated for possible roles in migraine occurrence.

Table 1 KCNK18 Analysis

MAF Migraine Position SNP Cases Controls HAPMAP X2 (P value) OR (L95-U95) rs1617136 Intron 1 G/A 0.38 0.38 0.39 0.01 (0.92) 1.00 (0.76-1.31) rs963975 Intron 2 C/G 0.28 0.29 0.24 0.54 (0.46) 0.88 (0.63-1.24) rs363314 Intron 2 G/T 0.39 0.41 0.33 0.27 (0.60) 0.92 (0.67-1.26) #CEU population, *SNP not genotyped in HapMap CEU population

Table 2 KCNK18 Haplotype Analysis

Haplotype+ Frequency X2 (P value) Cases Controls GGT 0.28 0.28 0.018 (0.89) ACT 0.01 0.01 0.015 (0.90) GCT 0.10 0.10 0.001 (0.99) ACG 0.36 0.37 0.015 (0.89) GCG 0.22 0.22 0.001 (0.97) + SNPs rs1617136, rs963975, rs363314

Figure 1 KCNK18 LD plot HapMap CEU data ‘X’ identifies SNPs genotyped in this project

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