c Copyright 2011 Springer Notice Changes introduced as a … · severe monogenic migraine subtype Familial Hemiplegic Migraine (FHM) in affected families has provided the best avenue

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Maher, Bridget H. & Griffiths, Lyn R. (2011) Identification of molecular ge-netic factors that influence migraine. Molecular Genetics and Genomics,285(6), pp. 433-446.

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http://dx.doi.org/10.1007/s00438-011-0622-3

1

Identification of Molecular Genetic Factors that Influence Migraine

Bridget H Maher1 and Lyn R Griffiths

1

1Genomics Research Centre, School of Medical Science, Griffith Health Institute, Griffith University,

Gold Coast, Queensland, Australia

Corresponding Author: Prof Lyn Griffiths

Genomics Research Centre

Griffith Health Institute

G05, Rm 2.11, Gold Coast campus

GRIFFITH UNIVERSITY QLD 4222

Phone: +61 (0)7 5552 8664

Fax No: +61 (0)7 5552 9081

Email address: [email protected]

2

Abstract: Migraine is a common neurological disorder with a strong genetic basis. However, the complex nature

of the disorder has meant that few genes or susceptibility loci have been identified and replicated

consistently to confirm their involvement in migraine. Approaches to genetic studies of the disorder

have included analysis of the rare migraine subtype, Familial Hemiplegic Migraine with several causal

genes identified for this severe subtype. However the exact genetic contributors to the more common

migraine subtypes are still to be deciphered. Genome-wide studies such as genome-wide association

studies and linkage analysis as well as candidate genes studies have been employed to investigate genes

involved in common migraine. Neurological, hormonal and vascular genes are all considered key

factors in the pathophysiology of migraine and are a focus of many of these studies. It is clear that the

influence of individual genes on the expression of this disorder will vary. Furthermore the disorder may

be dependent on gene-gene and gene-environment interactions that have not yet been considered. In

addition, identifying susceptibility genes may require phenotyping methods outside of the International

Classification of Headache Disorders II criteria, such as trait component analysis and latent class

analysis to better define the ambit of migraine expression.

Keywords:

Migraine, Migraine with Aura, Migraine without Aura, Familial Hemiplegic Migraine, molecular

genetics.

3

Introduction:

Migraine is an episodic, neurological disorder that presents with variable clinical phenotypes. The

common forms of migraine - Migraine with/or without Aura (MA and MO, respectively), are

diagnosed by the presence of recurrent headache that lasts 4-72 hours and is generally accompanied by

nausea, photophobia, phonophobia, aggravation by physical activity and possible neurological

symptoms, as outlined by the International Classification of Headache Disorders 2nd Edition (IHS

2004). Migraine affects approximately 12% of the population and has significant personal, social and

economic burdens (Lipton et al. 2007). However the exact causes and mechanisms that underlie

migraine have not been easily forthcoming.

Family and twin studies have clearly demonstrated that both the rare and common forms of migraine

have a significant genetic basis (Gervil et al. 1999; Mulder et al. 2003; Stewart et al. 2006), however

approaches to understanding this genetic basis have had varying degrees of success. Analysis of the

severe monogenic migraine subtype Familial Hemiplegic Migraine (FHM) in affected families has

provided the best avenue for identification of migraine genes. In contrast, the most prevalent forms MA

and MO are largely accepted to be polygenic and consensus on the key genetic contributors is elusive.

This is further complicated by a multifactorial mode of inheritance and environmental interactions

which create a phenotypic spectrum associated with expression of the disorder.

Approaches to genetic studies of the common migraine subtypes, MA and MO include genome-wide

methods such as linkage analysis and more recently Genome-wide Association Studies (GWAS).

Numerous key susceptibility loci have been identified through these methods with subsequent

candidate gene analysis. An alternative approach has been to identify and analyse candidate genes

directly. These genes are selected on the basis of information provided by clinical and other genetic

studies of the pathophysiology of migraine. Consequently neurotransmitters, hormones and vascular

genes are of particular interest.

Molecular genetics of severe migraine subtypes

Hemiplegic migraine is a very severe, rare monogenic subtype of MA that when found in families

(FHM) displays autosomal dominant transmission. This form of migraine can also occur as Sporadic

Hemiplegic Migraine (SHM) where sufferers have no first or second degree relative that share the aura

with motor weakness that is characteristic of FHM and SHM. Linkage studies of FHM families have

identified numerous genetic variants in independent genes that cause the disorder.

FHM1 is caused by mutations in the CACNA1A gene at 19p13 (Ophoff et al. 1996) and approximately

21 different causal missense mutations have been identified in this gene (de Vries et al. 2009).

CACNA1A codes for the α1A subunit of the Cav2.1 channels. This subunit is involved in voltage

sensitivity and resultantly mutations lead to uptake of Ca2+

ions into the neuron in response to smaller

depolarisations than wildtype channels. This in turn causes excess release of the neurotransmitter

glutamate (Wessman et al. 2007).

4

The FHM2 gene is ATP1A2 (De Fusco et al. 2003), located at 1q21-31 with over 30 different causal

mutations identified to date (de Vries et al. 2009). The gene encodes the Na+/K

+-ATPase α2 subunit.

The final known FHM gene (FHM3) is SCN1A encoding the voltage gated sodium channel gene on

chromosome 2q24 (Dichgans et al. 2005) with 5 known FHM mutations (Vanmolkot et al. 2007;

Castro et al. 2009; Vahedi et al. 2009).

The identification of FHM genes has provided insight into the pathophysiology of this severe form of

MA. It has been suggested that mutations in all three genes may lead to increased efflux of glutamate

and potassium in the synapse consequently resulting in increased susceptibility to cortical spreading

depression (CSD). CSD is a self-propagating depolarisations of neurons associated with disturbance of

ionic gradients and neurotransmitter release (Moskowitz 2007) that may ultimately trigger the migraine

aura. Further evidence implicating glutamate dysfunction in CSD and the aura includes the

identification of a de novo mutation in the SLC1A3 gene that codes the glutamate transporter;

Excitatory Amino Acid Transporter (EAAT1) 1. The mutation was identified in a single patient with

episodes of ataxia, migraine, hemiplegia and seizures. The authors concluded from the study that the

mutation led to reduced transporter function and consequently decreased glutamate uptake potentially

contributing to neuronal hyperexcitability and resulting in the neurological disturbances described in

the patient (Jen et al. 2005).

Functional studies of FHM mutations in cellular and animal models also support the view that

increased levels of glutamate in the synaptic cleft can lead to CSD causing the aura. FHM1 mutant

mice have been used to study the functional consequences of a number of FHM causing mutations in

CACNA1A. In particular the R192Q FHM-1 mouse has been observed to have a gain of function effect

leading to a lowered threshold for CSD (van den Maagdenberg et al. 2004). In vitro assays have also

been employed to study numerous other FHM mutations, demonstrating altered channel activity for

both FHM2 and FHM3 (Kahlig et al. 2008; Tavraz et al. 2008).

However, the role of the FHM genes in the headache phase of MA is still debatable. There is evidence

to suggest that CSD may trigger the trigeminovascular system (TGVS) and downstream pain pathways

leading to the migraine headache (Ayata 2010; Eikermann-Haerter and Ayata 2010), however the exact

mechanisms that lead to the TGVS activation are still to be established (Messlinger 2009).

Genetic studies that support the theory that hemiplegic and common migraine share at least some

genetic basis include the potential identification of a 4th

FHM locus by Cuenca-Leon and colleagues.

The locus at 14q32 was identified in a Spanish family with FHM, MA and MO (Cuenca-Leon et al.

2009) suggesting a possible shared locus for hemipleigic migraine and common subtypes. Another

study also identified a number of different mutations in the SLC4A4 gene in migraine families. This

study determined that homozygotes for any of 5 different mutations in this gene suffered either

hemiplegic migraine, MA or MO depending on the particular mutation (Suzuki et al. 2010). This gene

5

encodes an Na+-HCO3

- contransporter NBCe1, that can affect neuronal excitability through regulation

of pH in the brain.

However, investigation of the known FHM mutations has provided little evidence to suggest that these

are causative in common migraine subtypes (Terwindt et al. 2001; Jen et al. 2004; Todt et al. 2005;

Nyholt et al. 2008) or in many cases of SHM indicating that other genes are involved in this complex

disorder. Therefore it is possible that the known FHM genes may only influence the aura or hemiplegia

symptoms in the FHM sufferers, particularly as the CACNA1A gene (FHM1) is known to cause other

neurological disorders such as episodic ataxia that are not associated with migraine. Nonetheless the

pathways in which the FHM genes act remain top candidates for common migraine studies.

Common Migraine Subtypes

Studies of complex diseases such as common migraine pose many difficulties. Heritability studies of

migraine have firstly shown that migraine is influenced by environmental factors which can alter the

phenotypic expression of the disorder consequently affecting diagnosis which can be critical to genetic

studies. Furthermore significant evidence points to the fact that common migraine is a polygenic

disorder and gene-gene interactions may thus also play a critical role.

There is significant debate also as to whether MA and MO are distinct disorders or a spectrum of

migraine. The headache phase of these subtypes share the same clinical features, however MA is

associated with reversible neurological symptoms that occur just prior to the onset of the headache

phase (IHS 2004). Recent evidence through the use of alternative phenotyping methods such as Latent

Class Analysis (LCA) suggests that MA and MO are not distinct entities. LCA recognises 3 major

headache classes; Mild, Moderate or Severe and one asymptomatic class where groups are based on the

combination and severity of symptoms (Nyholt et al. 2004). Therefore it is expected that a few key

susceptibility genes will underlie both disorders and these may be alternatively influenced by other

genetic and/or environmental factors. Genetic studies have supported this theory with many studies

providing conflicting results as to whether specific loci or variants are associated with MA, MO or both

(see Tables I and II).

A number of different approaches to identifying candidate genes have therefore been employed to

overcome these problems. These may be divided into two categories, genome-wide approaches to

identify susceptibility loci and direct candidate gene analysis.

Genome-wide approaches

Genome-wide approaches attempt to identify specific contributing loci in which candidate gene studies

may then be carried out. Two main methods have been employed; linkage studies that analyse affected

pedigrees and GWAS that use large case-control populations.

Linkage analysis

6

Analysis of migraine inheritance in affected pedigrees is a frequently used approach that has identified

numerous migraine susceptibility loci. Table I outlines the known loci, however many are yet to be

replicated. There may be a number of reasons for this, including rare family specific markers that have

significant impact within subsets of families and consequently over represent a linkage signal (Anttila

et al. 2008). These may not then be replicated in other pedigrees or case-control populations. Or more

likely, as migraine is highly prevalent in the population (12%) (Lipton et al. 2007), interference may

occur from migraine sufferers married into the family where their genes influence the outcome of the

linkage study. A final factor that may inhibit the linkage studies is difficulty in accurate diagnosis and

the heterogeneity of migraine manifestation.

Studies by Nyholt, Antilla and colleagues have attempted to overcome this through the use of LCA and

Trait Component Analysis (TCA) to breakdown the MA/MO classification into more homogeneous

groups for genetic analysis. As can be seen from Table I only a handful of migraine studies have made

use of either TCA or LCA however results are promising. Both methods have been shown to identify

linkage regions previously not seen through the ICHD-II classification. Using the LCA method Nyholt

and colleagues identified the 5q21 region that is predominantly associated with pulsating headache

(Nyholt et al. 2005). Similarly the LCA method identified linkage on 18p11 (Lea et al. 2005).

A study by Antilla and colleagues used all three methods and showed consistent linkage to 10q22-23

for 5 TCA phenotypes, the MA ICHD-II classification and the LCA class migrainous headache in a

Finnish population (Anttila et al. 2008). This was also replicated in Australian populations.

Furthermore, the 10q22-23 region is one that has been identified previously (Nyholt et al. 2005). This

strongly suggests that these methods can assist in providing replication to confirm independent studies

and be used to identify new regions of interest in their own right (Anttila et al. 2008).

Linkage studies have yielded a number of other susceptibility loci, and despite a number of these

lacking replication many have analysed candidate genes identified within these loci. Some significant

examples include the 19p13, Xq24-28, 15q11-13 and the 10q25 loci.

Candidate genes and 19p13 (MGR5, MIM ID: %607508)

This locus was identified in two independent linkage studies as segregating with the MA phenotype

(Nyholt et al. 1998b; Jones et al. 2001). Although the peak linkage regions identified do not overlap,

the locus contains a number of interesting candidates. In particular the FHM1 gene CACNA1A is coded

in the locus however this gene has not been consistently found to contribute to common migraine (Lea

et al. 2001; Terwindt et al. 2001; Jen et al. 2004). Other genes within the region that have been of

particular interest include the insulin receptor (INSR), notch homolog 3 (NOTCH3) and the low density

lipoprotein receptor (LDLR) genes.

Analysis of the INSR gene showed 5 SNPs with positive association to migraine in 2 independent

populations (McCarthy et al. 2001). This was also confirmed in a large study by Netzer and colleagues

7

in a German population (Netzer et al. 2008a) where one of the five SNPs, rs2860174, showed

significant allelic association P=0.005. While the exact role of the insulin receptor in migraine is still to

be elucidated there is epidemiological evidence of migraine and diabetes co-morbidity. Furthermore

fasting may also be considered a trigger for migraine occurrence (Netzer et al. 2008a).

The NOTCH3 gene also resides at 19p13.2-13.1 and encodes a large single pass transmembrane protein

expressed in arterial vascular smooth muscle cells. Mutations in this gene are known to cause the rare

autosomal dominant disorder Cerebral autosomal dominant arteriopathy with subcortical infarcts and

leucoencephalopathy (CADASIL) which presents with recurrent subcortical ischemic strokes and MA.

Therefore analysis of SNPs within exon 3 and 4 (where the majority of CADASIL mutations are

found) of this gene have been undertaken in migraine populations. Schwaag and colleagues sequenced

these exons in 97 patients; no new mutations were identified but associations were found with 2 SNPs

(G864A genotypes P=0.008 and C381T allelic P=0.032) and the MO subtype (Schwaag et al. 2006).

We recently undertook analysis of the same 2 polymorphisms in 2 independent Australian populations.

The results confirmed the association in the first population, however upon replication the C381T SNP

failed to show association suggesting further investigation of the variant is required to confirm its

involvement in migraine. The 2nd

SNP G864T however, showed strong association particularly with the

MA subtype (population 1 genotype P=0.004, population 2 genotype P=0.005), however as this SNP is

synonymous it is still unclear how it may affect the function of Notch3 (Menon et al. 2010).

Finally the LDLR gene has also shown conflicting evidence for involvement in migraine. Mochi et al.

identified a microsatellite in exon 18 that showed positive association with MO (Mochi et al. 2003),

however this association was not replicated in an Australian population (Curtain et al. 2004).

Furthermore no relationship was found between cholesterol levels and migraine diagnosis in the

Norfolk Island genetic isolate casting additional doubt on the role of this gene in migraine (Curtain et

al. 2004).

Candidate genes and Xq24-28 (MGR2, MIM ID: %300125)

Epidemiological evidence and the female preponderance of this disorder strongly suggest a hormonal

influence on migraine. However, families with an excess of affected females and lack of male to male

transmission may also suggest an X chromosomal component. Studies of large multigenerational

pedigrees in our laboratory identified that this was the case in 2 large Australian pedigrees and

indicated that the Xq24-28 region contributed to migraine susceptibility (Nyholt et al. 1998a; Nyholt et

al. 2000). This region harbours a number of candidate genes that have been investigated including 5-

hydroxytryptamine (serotonin) receptor 2C (5HT2C), Glutamate Receptor ionatropic AMPA3 (GRIA3),

gamma-aminobutyric acid A receptor epsilon (GABRE), gamma-aminobutyric acid receptor theta

(GABRQ) and gamma-aminobutyric acid A receptor 3 (GABRA3).

The serotonin receptor 5HT2C has been analysed in a number of populations, however these studies

have shown no indication that variants in this gene are involved in migraine (Burnet et al. 1997;

8

Johnson et al. 2003; Racchi et al. 2004). Similarly, the GABRE and GABRQ genes that code for 2 of the

19 subunits of the GABA-A receptors have shown no association in an Australian population. However

GABRA3, which is yet to be analysed, remains a potential candidate that should be investigated due to

the role of GABA as the main inhibitory neurotransmitter in the brain.

In contrast, glutamate is the main excitory neurotransmitter and functions through the Alpha-amino-3-

hydroxy-5-methyl-4-isoxazole-propionin acid (AMPA) ionatropic receptor. Glutamate is believed to be

required for cortical spreading depression and to activate the TNS and central sensitization, thus

inhibition of glutamate release culminates in an anti-nociceptive effect (Vikelis and Mitsikostas 2007;

Neeb et al. 2010). GRIA3 at Xq28 codes for 1 of 4 subunits for the AMPA receptor.

Formicola and collegues analysed a number of SNPs in each GRIA gene in an Italian population of 250

migaineurs and 260 controls. Their results indicate positive association with 2 SNPs in GRIA1 (5q33.2,

rs548294 MO allelic P=0.008, rs2195450 MA allelic P=0.0005) and 1 SNP in GRIA3 (rs3761555 MA

Females allelic P=0.003) (Formicola et al. 2010). These results suggest that GRIA3 may contribute to

the linkage signal at Xq24, however further research into the glutamate system is warranted to confirm

its role in migraine susceptibility and pathophysiology.

Candidate genes and 15q11-q13 (MGR5, MIM ID: %609179)

Linkage studies have also implicated the 15q11-q13 region which contain the GABA-A subunits

GABRB3, GABRA5 and GABRG3 (Russo et al. 2005). Sequencing of the coding regions of these genes

identified only one polymorphism in GABRB3 in the affected individuals in only one (of five) families

in the linkage studies. Further studies by Netzer (Netzer et al. 2008b) and Oswell (Oswell et al. 2008)

in independent case-control cohorts also showed no evidence for involvement of this cluster in

migraine. This suggests that if these genes are the causative ones in the region then another

polymorphism perhaps in a regulatory region may be playing a role.

While genetic association studies of GABA receptor subunits both at Xq24-28 and 15q11-13 have not

conclusively confirmed their role in migraine, there is significant clinical evidence suggesting their

involvement particularly as GABA-A receptor agonists such as topiramate and gabapentin are

commonly used migraine prophylactics (Fernandez et al. 2008). Further research is required on both

the subunits already considered and those not yet investigated.

Tresk and 10q25

Lafreniere and colleagues recently identified the first functional variant in a gene to show linkage to

familial MA. The KCNK18 gene encodes the TRESK K2P channel involved in neuronal excitability.

This study sequenced the coding region in 110 unrelated migraineurs and 80 controls and identified 2

variants that were found only in migraine sufferers. 1 variant was synonymous while the second was a

2bp deletion resulting in a prematurely truncated protein. Subsequent gene sequencing analysis in

Australian samples also identified 9 other variants.

9

Linkage analysis of a large multigenerational family with MA identified a region from 10q25.2-25.3

(9.7Mb) in which KCNK18 was the only ion channel gene of 52 known genes encoded at the locus.

Further analysis of this family identified the same 2bp deletion variant that segregated with all affected

individuals within the family (Lafreniere et al. 2010).

To further investigate TRESK in migraine pathophysiology Lafreniere and colleagues also showed that

the protein was strongly expressed in the trigeminal ganglion neurons, supporting a role for TRESK in

neuronal excitability. Further analysis of the functional consequence of the 2bp deletion showed that

the truncated protein is non-functional and was demonstrated to cause a dominant-negative

downregulation of wildtype channels. This study concluded that migraine risk may therefore increase

as TRESK activity decreases due to genetic mutation.

This research clearly demonstrated how a linkage study can be used to confirm involvement of a

specific chromosomal region as well as a specific candidate gene. The family analysed shared similar

migraine episodes suggesting that a homogenous group for analysis potentially aided the identification

of this gene. The results indicate also that further analysis of KCNK18 is required in migraine groups of

similar phenotype. Furthermore functional studies have indicated that TRESK may be a target for new

therapeutics.

GWAS

Genome-wide association studies are a relatively new approach that have been successful in aiding the

current understanding of many complex disorders, including various cancers, Alzheimers,

inflammatory bowel disease and diabetes. This approach requires large case-control cohorts and

genotyping of 100, 000’s of SNPs generally using commercially available array techniques. Common

variants with large effect size should be relatively easy to identify using this approach, however as is

the case for most complex disorders, it is expected that risk alleles with smaller effect sizes are likely to

contribute and these would then require large cohorts or meta analysis of a number of studies to

identify. Alternatively rare variants with larger effect sizes may also be implicated however these are

not commonly well covered in the arrays used (Seng and Seng 2008). Despite these limitations GWAS

have proved useful in both confirming existing susceptibility loci and identifying new regions for

further investigation.

Unfortunately to date only one GWAS has been published focusing on migraine. The GWAS analysed

over 3000 Finnish, German and Dutch migraineurs recruited from headache clinics and compared these

to age and sex matched population based controls. The study classified the migraineurs according to

the ICHD-II criteria. The study identified only one marker at the appropriate level of significance on

chromosome 8q22.1. The marker is situated between the genes MTDH and PGCP both of which are in

pathways thought to regulate glutamate accumulation in the synaptic cleft. The association of this

marker with MA was also replicated in Danish and Icelandic populations strongly suggesting this loci’s

involvement in MA (Anttila et al. 2010). This finding potentially strengthens the evidence for a

10

mechanism involving excess glutamate in the synaptic cleft contributing to the occurrence of a

migraine aura and/or the headache phase as has been suggested in studies of hemiplegic migraine.

Candidate Genes

In addition to genome-wide approaches such as the GWAS and linkage studies, many studies have

taken a candidate gene approach using case-control association studies. These studies have generally

either attempted to cover the specific gene using tagging SNPs or have selected known functional

variants that may have been associated with disorders related to migraine. The genes that have been

focused on primarily include genes with neurological, hormonal or vascular functions. Table II, III and

IV list a number of association studies that have shown positive association between migraine and

genes in these categories respectively.

Replication studies have been undertaken on a significant number of these, however for the vast

majority, results are conflicting or inconclusive. This may be due to any number of reasons including

under powered studies, ethnic differences, or the genetic and phenotypic heterogeneity of the disorder

which could vary significantly between independent case-control cohorts contributing to the difficulty

in replicating associations with variants of small effect size.

Neurological Candidate Genes

The trigeminovascular system is believed to be integral to the onset of migraine (Moskowitz 2008).

The neurotransmitters, peptides, receptors and channels located in various components of this system

may trigger vascular dysfunction and downstream pain signals and are therefore key candidates. The

serotonergic system is of particular interest as 5-HT is a neurotransmitter involved in a plethora of

biological functions including information processing and nociception. Furthermore 5-HT receptor

agonists (Triptans) originally developed as vasoconstrictive agents, have been observed to mitigate

migraine attacks. While the exact mechanisms of the serotonergic system in migraine are still unknown

one theory considers a deficiency of central 5-HT associated with sensitivity to an increase in 5-HT

release to be a basis for migraine aetiology (Hamel 2007; Panconesi 2008). Extensive research has

been carried out to identify genetic variants that may alter the functions of a number of genes involved

in 5-HT function and regulation. These genes include the 5-HT1B, 1D and 2C receptors, the 5-HT

transporter (SLC6A4), Tryptophan Hydroxylase (TPH2), Monoamine Oxidase A enzyme (MAOA), and

Calcitonin Gene Related Peptide (CGRP) genes.

The serotonin transporter gene SLC6A4 in particular has been extensively studied. This gene on

chromosome 17q11.2 encodes the integral membrane protein that transports serotonin into and out of

the synaptic cleft in a sodium dependant manner. In this gene 2 polymorphisms have been of particular

interest. The first is an insertion deletion polymorphism in intron 2 known as STin2, with 2 common

variants designated STin2.10 and STin2.12. Analysis of this polymorphism has provided conflicting

results. Schurks recently conducted a meta-analysis of 5 studies considering this polymorphism and

found that the non-STin2.12 alleles appear to provide a protective effect against migraine in the

populations studied (Schurks et al. 2010d). The second polymorphism is a 44-bp insertion/deletion in

11

the promoter region known as 5-HTTLPR. The shorter allele is associated with slower clearing of

serotonin from the synaptic cleft (Schurks et al. 2010d). Early studies provided evidence of an

association with migraine or MA (Juhasz et al. 2003; Marziniak et al. 2005). In contrast Todt et al.

conducted a study including this variation and a number of SNPs across the gene and found no

association to MA (Todt et al. 2006) and a recent study by Corominas et al. also confirmed this finding

(Corominas et al. 2010). A meta analysis of 10 studies considering this polymorphism also determined

no overall association, although the authors noted that migraine type and gender may modify the

influence this gene has on migraine (Schurks et al. 2010a).

Similarly the dopaminergic system has been implicated in the pathogenesis of migraine due to the

presence of dopamine driven processes that occur prior to or during a migrainous episode (Sicuteri

1977), the incidence of which are increased by dopamine and dopamine agonists. It is therefore

hypothesised that migraineurs may be hypersensitive to dopamine and it may act as trigger for the

migraine attack (Akerman and Goadsby 2007). However, the exact mechanism through which the

dopaminergic system influences migraine remains unclear. Dopamine receptors are present in the

trigeminocervical complex and administration of dopamine agonists in rat inhibits neuronal firing and

consequent nociceptive transmission (Bergerot et al. 2007). Yet, dopamine antagonists are also known

to be effective in relieving the migraine therefore it is uncertain whether these function through the

dopamine receptor or another path (Charbit et al. 2010). Despite the apparently conflicting roles for

dopamine and dopamine antagonists in migraine there is significant evidence to suggest there is an

influence on the pathogenesis of this disease and therefore investigation into dopamine receptors,

transporters and the dopamine beta hydroxylase (DBH) gene have been undertaken.

DBH converts dopamine into noradrenaline which is also a key neurotransmitter. In an Australian

population a promoter insertion/deletion polymorphism that is associated with reduced plasma enzyme

activity has been studied. The homozygous del/del genotype was shown to increase migraine risk in

males up to three times (Fernandez et al. 2006). Further analysis of the promoter region in the

Australian population considered a SNP that is responsible for 31-52% of enzyme activity. This SNP,

rs161115, showed significant association in the migraine cohorts tested (population 1 P=0.012,

population 2 P=0.031) and particularly associates with MA (Fernandez et al. 2009). Corominas and

colleagues similarly analysed this SNP in a Spanish population. They found association in migraine

only in their first cohort but this was not replicated in their second, therefore it was dropped from

further analysis (Corominas et al. 2009a). A final SNP was also recently considered by Todt and

showed significant association in a German MA population using ~650 cases and an enlarged control

group (rs2097629 allelic P=0.0116). This SNP is not in LD with the highly functional SNP analysed in

the Australian population (Todt et al. 2009) suggesting that there may be two different functional

variants that influence this enzyme and its role in MA.

Hormone Candidate genes

The observations that migraine generally increases in women at puberty (Lipton et al. 2001), and may

be altered with reproductive milestones such as menstruation, pregnancy, menopause and hormone

12

therapy (Maggioni et al. 1997; MacGregor 2009) strongly indicates that fluctuating hormones,

particularly estrogen levels may play a role in triggering a migraine attack. It has previously been

hypothesised that prolonged exposure to high levels of estrogen prior to a drop in concentrations ie.

‘estrogen withdrawal’ may precipitate the migraine event (MacGregor 2004). Genetic studies have

focused on hormone receptors such as estrogen receptor 1 (ESR1) and the progesterone receptor.

ESR1 is located on chromosome 6q25.1 and is expressed in a number of areas of the brain and other

tissues. ESR1 is believed to be involved in gene expression and may also be involved in modulation of

neurotransmitters such as CGRP, glutamate and serotonin. In addition steroid hormones are thought to

have vascular effects such as influencing Nitric Oxide production thereby affecting vascular tone

(Gupta et al. 2007).

An early study considered a SNP in ESR1 known to be associated with breast cancer. The G594A SNP

in exon 8 was found to be positively associated with migraine in two independent Australian case-

control populations (population 1 genotypic P=0.008, population 2 genotypic P=4x10-5

) (Colson et al.

2004). A separate study of the progesterone receptor in the same populations also showed association

(Population 1 genotypic P=0.04, Population 2 genotypic P=0.019). Furthermore, analysis of both

hormonal genes together determined that the interaction of the PROGINS Alu insertion allele in intron

7 combined with the 594A ESR1 allele increased migraine risk by 3.2 (Colson et al. 2005). However

follow-up studies of 2 further SNPs within the ESR1 gene in intron 1 and exon 4 (G325C) found no

association in the same population (Colson et al. 2006a). This is in contrast to a Spanish study which

identified positive association with the G325C but not the original G594A polymorphism (Oterino et

al. 2006). Negative results were similarly found in a larger Finnish cohort that looked at 26 SNPs

across the gene (Kaunisto et al. 2006), and another Spanish study that found no association across 3

SNPs (Corominas et al. 2009b).

Recently Schurks and collegues conducted a meta-analysis of sex hormone receptor genes and

migraine in order to summarise the existing data on these variants and their respective associations with

migraine. This study analysed the previously discussed ESR1 G594A and C325G SNPs as well as the

PROGINS Alu insertion. An additional ESR1 Pvu II C>T SNP was also considered. The authors

identified an association between migraine and both the ESR1 G594A and C325G SNPs that followed

dominant and recessive models respectively. In contrast no associations were identified for the

remaining variants tested (Schurks et al. 2010c).

In order to overcome some of the conflicting reports on ESR1 and to further investigate the gene-gene

interactions a study was conducted by Oternio and colleagues considering a multilocus analysis of 5

estrogen related genes. Nominal association was observed in the ESR1, ESR2 and FSHR genes and

further analysis of gene-gene interactions suggested these loci were significantly associated with

MA/MO and MA alone (Oterino et al. 2008). These studies support the role of hormones and/or

13

hormone related genes in migraine. However it is still unclear whether the genes analysed so far are the

key contributors. If so, the relationship between hormones levels and their specific influences on

migraine pathophysiology in the central nervous system and/or the vascular system still needs to be

defined.

Vascular Candidate genes

Migraine was once thought to be a vascular disorder due to observations of increased blood flow prior

to and during a migraine episode. This theory hypothesised that the initiating event in a migraine

episode occurred in the perivascular nerves of the cerebral vasculature (Parsons and Strijbos 2003).

However development of new effective migraine drugs have shown that vasoconstriction is not

required for migraine treatment and therefore vasodilation of cranial vessels may only be a secondary

phenomenon caused through activation of the Trigeminovascular system (Goadsby et al. 2002).

Despite this finding, the involvement of the vasculature in migraine pathophysiology is clear and the

effects of vasoactive drugs in migraine treatment cannot be ignored. Consequently numerous genetic

studies of vascular genes that can alter vascular endothelial function have been undertaken. These

include Nitric Oxide Synthase (NOS), Calcitonin Gene Related Peptide (CGRP), Angiotensin I

Converting Enzyme (ACE), Methylenetetrahydrofolate reductase (MTHFR) and the NOTCH3 gene.

Homocysteine is an important regulator in vascular disease and is thought to also play a role in

migraine. Homocysteine is an intermediate metabolite of methionine, and MTHFR catalyses the

reduction of 5,10-methyltetrahydrofolate to 5-methyltetrahydrofolate, the predominant circulatory form

of folate, which is the carbon donor required for methylation of homocysteine to methionine (Lea et al.

2009). A SNP in the MTHFR gene C677T causes an alanine to be replaced with a valine within the

catalytic domain of the enzyme reportedly reducing the enzymatic capacity by up to 50% (Frosst et al.

1995). This in turn may lead to mild hyperhomocysteinemia which has been associated with

endothelial cell injury (Hering-Hanit et al. 2001), reduced production of NO (Colson et al. 2006b),

oxidative stress and may contribute to the activation of the trigeminal fibres.

The C677T SNP has been studied in a number of migraine populations with conflicting results. Kowa

and colleagues considered a Japanese cohort of 74 cases and 261 controls and found the TT genotype

was significantly associated with migraineurs, particularly MA (Kowa et al. 2000) and this has been

confirmed in a number of independent studies of various ethnicities. (Kara et al. 2003; Lea et al. 2004;

Scher et al. 2006; Liu et al. 2010). In contrast though, Schurks recently conducted a large study using

data from the Women’s health study in the US where it was found that the TT genotype conferred a

modest protective effect on MA (Schurks et al. 2010e). Alternatively, Oterino, did not identify an

association in a Spanish population, however it was noted that the T allele was higher in the MA cohort

than in the MO cohort. A lack of association has also been found in a number of other studies

(Kaunisto et al. 2006; Ferro et al. 2008; Joshi et al. 2009).

14

Due to the number of studies conducted on this particular variant it is also interesting to consider the

results of a large meta-analysis. Rubino and collegues were the first to consider the MTHFR SNP using

the meta-analysis approach and analysed 8 studies involving 2961 migraineurs predominantly of

caucasian populations. This analysis showed a significant association between MA and the TT

genotype (Rubino et al. 2009). Interestingly, the second and more recent analysis by Schurks et al. also

found a similar result, however their analysis determined that the result appeared to be driven by the

non-caucasian populations included in the study. The authors noted the inclusion of a number of recent

studies and variations in methodology that may contribute to the variations in results (Schurks et al.

2010b). However, overall, the Rubino et al. meta-analysis and the Schurks recent analysis showed a

significant involvement of this gene in MA.

The role of the MTHFR gene is further supported by observations that supplementation with folic acid

(Vitamin B9) combined with vitamins B12 and B6 can not only lower homocysteine levels but can also

affect migraine symptoms. This was demonstrated in a recent pilot study that showed reduction in

homocysteine levels also reduced migraine frequency, severity and disability in MA sufferers.

Furthermore, this response was associated with the C677T SNP where individuals with at least one C

allele showed improved response over the TT genotype (Lea et al. 2009).

Implications of Phenotypic Diversity in Migraine

Genetic studies of complex disease can often be hindered by poor diagnosis and phenotyping leading to

heterogeneity in case cohorts and consequently impeding the replication of findings. Migraine can

present with a variety of symptoms that may differ significantly between sufferers; as well as between

episodes in a single individual. Coupled with a lack of lab based diagnostic tests this presents

difficulties in obtaining a clear diagnosis.

The implications of poor diagnosis can be significant particularly when stratifying the case group by

migraine subtype or in order to replicate results in independent populations. Therefore the diagnostic

strategies used for genetic studies in migraine should be well documented. In particular the method of

collection of phenotypic data (ie. survey, interview, questionnaire etc.) on which diagnosis is based

should be carefully considered.

The quality of phenotypic data collected is also critical to the analysis of migraine subtypes or traits

independently. In a single individual migraine characteristics can vary over a lifetime. Thus when

searching for a gene that may contribute to a particular phenotype eg. Photophobia, the clinical history

and phenotypic data available must be of a high quality to ensure consistency of the presence or

absence of the particular subtype or trait across the individual’s migraine history.

Conclusion:

Common migraine is a polygenic multifactorial disorder that is most likely influenced by multiple

genes and environmental triggers. Variants are likely to involve gene-environment and gene-gene

15

interactions increasing the genetic variability of the disorder and perhaps explaining why many single

gene studies are conflicting in their outcomes.

The search for migraine genes remains complicated by the fact that many susceptibility variants are

likely to have modest contributions to the phenotypic expression of the disorder. Linkage studies are a

sound approach for identifying contributing loci. However, confirmation in independent studies and

possibly through future GWAS is required in case rare family-specific mutations of larger effect size

distort linkage signals which may therefore not translate to analysis in case-control populations. An

additional influence on the outcome of many of the genetic studies is the spectrum of phenotypes

among sufferers. Approaches such as LCA and TCA in addition to the use of specific ICHD-II criteria

may assist to improve concordance amongst the studies being undertaken as has been seen in a handful

of linkage studies.

The approaches used in migraine genetics, be it genome-wide or candidate gene, each have a role to

play in identifying new regions and confirming existing studies. Overall, current linkage, GWAS and

candidate gene studies provide tantalising insights into the pathophysiology of migraine. There have

been some successes such as the recent studies implicating a functional mutation in the TRESK gene,

and others that warrant further investigation at genetic and/or clinical levels such as ESR1 and MTHFR.

These genes and others considered in this review are promising migraine candidates that require further

investigation particularly of gene-gene interactions to assist in building a gene profile of this complex

disorder.

16

Locus Migraine subtype Families Population Genotyping Method Reference

1q31 MA & MO 85 Australian Loci specific microsatellite markers (Lea et al. 2002)

2p12 TCA-pulsation, MA & LCA-migraine 58 Finnish Genome-wide scan (Anttila et al. 2008)

3qter LCA severe 21 Australian Genome-wide scan (Lea et al. 2005)

4q21 MO 103 Icelandic Genome-wide scan (Bjornsson et al. 2003)

4q24 MA

TCA – age at onset, photophobia,

phonophobia, pain intensity,

unilaterality, pulsation

50

50

Finnish

Finnish

Genome-wide scan

Genome-wide scan

(Wessman et al. 2002)

(Anttila et al. 2006)

5q21 LCA Twins Australian Genome-wide scan (Nyholt et al. 2005)

6p12.2-p21.1 MO & MA

Activity prohibiting headache and

photophobia

1

Twins

Swedish

Australian

Genome-wide scan

Genome-wide scan

(Carlsson et al. 2002)

(Nyholt et al. 2005)

9q21-22 Visual migraine aura 36 Finnish Genome-wide scan (Tikka-Kleemola et al. 2010)

10q22-23 LCA

MA, TCA – Unilaterality, pulsation,

pain/intensity, nausea/vomiting,

photophobia & phonophobia. LCA –

migrainous headache

TCA-Phonophobia

LCA migraine, phonophobia,

photophobia

756

210

50

Twins

Australian Twins

Finnish and

Australian

Finnish

Australian

Genome-wide scan

Genome-wide scan

Genome-wide scan

Genome-wide scan

(Nyholt et al. 2005)

(Anttila et al. 2008)

(Anttila et al. 2006)

(Nyholt et al. 2005)

11q24 MA 43 Canadian Genome-wide scan (Cader et al. 2003)

14q21.2-q22.3 MO

TCA –pain intensity

1

125

Italian

Australian

Genome-wide scan (Soragna et al. 2003)

(Anttila et al. 2008)

15q11-q13 MA 10 - Loci specific microsatellite markers (Russo et al. 2005)

17p13.1 TCA-pulsation 50 Finnish Genome-wide scan (Anttila et al. 2006)

18p11 LCA severe 92 Australian Genome-wide scan (Lea et al. 2005)

17

Table I: Summary of Linkage studies

(MA: Migraine with Aura, MO: Migraine without Aura, TCA: Trait Component Analysis, LCA: Latent Class Analysis)

18q12 TCA – attack length

TCA – aggravation by physical

exercise, attack length

MO

58

50

103

Finnish

Finnish

Icelandic

Genome-wide scan

Genome-wide scan

Genome-wide scan

(Anttila et al. 2008)

(Anttila et al. 2006)

(Bjornsson et al. 2003)

19p13 MA

MA

1

16

Australian

North American

Loci specific microsatellite markers

Loci specific microsatellite markers

(Nyholt et al. 1998b)

(Jones et al. 2001)

Xp22 TCA pulsation, MA & LCA severe

Migraine - mixed

58

61

Finnish

European descent

Genome-wide scan

Loci specific microsatellite markers

(Anttila et al. 2008)

(Wieser et al. 2010)

Xq24-28 MA and MO 2 Australian Loci specific microsatellite markers (Nyholt et al. 2000)

(Nyholt et al. 1998a)

18

Gene Locus Reference Ethnicity Cases Controls # SNPs Associated SNPs P value

Serotonin related Genes (Corominas et al. 2010)

HTR1E 6q14-q15 Spanish 528 528 8 rs828358

rs1581774

P=00018*

P=0.016* (MA)

HTR2A 13q14-q21 Spanish 528 528 24 rs7984966

rs7322347

rs9534511

rs6561332

P=0.037* (MO)

P=0.07* (MO)

P=0.012* (MA)

P=0.016* (MA)

HTR2C+ Xq24 Spanish 528 528 9 rs4911871

rs2428721

P=0.029*

P=0.036* (MA)

HTR3A 11q23.1 Spanish 528 528 4 rs1176717 P=0.042* (MA)

HTR3B 11q23.1 Spanish 528 528 9 rs11214775 P=0.025* (MO)

HTR4 5q31-q33 Spanish 528 528 17 rs7721747 P=0.034* (MO)

HTR7 10q21-q24 Spanish 528 528 11 rs1298056 P=0.0058* (MA)

DDC+ 7p12.2 Spanish 528 528 15 rs1982406

rs6944090

P=0.0035* (MA)

P=0.021* (MA)

MAOA+ Xp11.3 Spanish 528 528 2 rs3027400

rs2072743

P=0.0093* (MO)

P=0.043* (MO)

Dopamine related Genes

DBH 9q34 (Fernandez et al. 2006) Australian 275 275 2 19bp in/del P=0.003 (MA)

(Fernandez et al. 2009) Australian 200 200 rs16111115 P=0.012

300 300 rs1611115 P=0.031

(Todt et al. 2009) German 650 2937 1 rs2097629 P=5.57x10-8

(Corominas et al. 2009a) Spanish 263 274 11 rs1611131 P=0.04

SLC6A3+ 5p15.3 (Todt et al. 2009) German 650 2937 1 rs40184 P=6.36x10

-7

DRD2+ 11q23 (Todt et al. 2009) German 650 2937 1 rs7131056 P=0.034

DRD3+ 3q13.3 (Corominas et al. 2009a) Spanish 263 274 10 rs12363125

rs22832265

P=0.03

P=0.008

Glutamate Receptors

GRIA1 5q31.1 (Formicola et al. 2010) Italian 250 260 6 rs2195450

rs548294

P=0.00002 (MA)

P=0.0003 (MO)

GRIA3 Xq25 (Formicola et al. 2010) Italian 250 260 8 rs3761555 P=0.0001 (MA)

Table II: Positive Migraine Association Studies: Neurological genes (*Uncorrected +

Other studies have failed to show association between migraine and these genes)

19

(HTR: 5-hyydroyytryptamine (serotonin) receptor, DDC: Dopa Decarboxylase (aromatic L-amino acid decarboxylase) MAOA: Monoamine Oxidase A, DBH: Dopamine

Beta-Hydroxylase, SLC6A3: Solute Carrier Family 6 (neurotransmitter transporter, dopamine), DRD2: Dopamine Receptor D2, DRD3: Dopamine Receptor D3, GRIA1:

glutamate receptor, ionotropic, AMPA 1, GRIA3: glutamate receptor, ionotropic, AMPA 3)

Gene Locus Reference Ethnicity Cases Controls # SNPs Associated SNPs P value

Progesterone

Receptor

11q22 (Colson et al. 2005) Australian 275 275 1 P=0.02

300 300 1 P=0.003

ESR1+ 6q25.1 (Colson et al. 2004)

Australian 224 224 1 rs2228480 P=0.003

260 260 1 rs2228480 P=8x10-6

(Oterino et al. 2006) Spanish 240 160 rs1801132 P=0.008 (females)

Table III: Positive Migraine Association Studies: Hormone Related Genes (+

Other studies have failed to show association between migraine and these genes)

(ESR1: Estrogen Receptor 1)

Gene Locus Reference Ethnicity Cases Controls # SNPs Associated SNPs P value

ACE 17q23.3 (Joshi et al. 2009) Indian 150 150 rs4646994 P=0.04 (MA)

(Paterna et al. 1997) 191 201 rs4646994 P<0.05

(Kowa et al. 2005) 176 248 rs4646994 P<0.01 (MA)

MTHFR+ 1p36.3 (Kowa et al. 2000) Japanese 74 261 1 rs1801133 P<0.01

(Kara et al. 2003) Turkish 102 136 2 rs1801133 P=0.015

(Lea et al. 2004) Australian 270 270 1 rs1801133 P=0.017 (MA)

NOTCH3 19p13.2-13.1 (Schwaag et al. 2006) Caucasion 97 97 2 rs1043994 P=0.005

(Menon et al. 2010) Australian 275 275 2 rs3815188

rs1043994

P=0.002 (MO)

P=0.001 (MA)

300 300 2 rs3815188

rs1043994

P=0.06 (MO)

P=0.003 (MA)

EDNRA 4q31.22 (Tikka-Kleemola et al. 2009) Finnish 850 900 13 rs2048894 P=0.015 (MA)

Table IV: Positive Migraine Association Studies: Vascular Related Genes (+

Other studies have failed to show association between migraine and these genes)

(ACE: Angiotensin I Converting Enzyme (peptidyl-dipeptidase A) , MTHFR: Methylenetetrahydrofolate Reductase (NAD(P)H), EDNRA: Endothelin Receptor Type A)

20

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