The identification of genetic variants that modify the risk for stroke is still in its infancy. Inherited stroke syndromes with identified disease-causing mutations exist, but are rare [
7]. The majority of strokes are thought to be associated with a complex variety of interacting risk factors, related to co-morbidities, life style, baseline characteristics and genetic variants [
8]. The impact of environmental and modifiable risk factors on stroke is well recognized, albeit difficult to capture in its whole complexity. On the contrary, modern genetic technologies like high density single nucleotide polymorphism (SNP) microarrays or second generation sequencing approaches permit the precise, rapid and standardized documentation of a growing number of individual genetic variants - at falling prices.
A GWAS is an observational study in which genetic variation is compared between people with a particular condition (cases) and unaffected control individuals. Because genetic variants are assigned at random from parents to offspring (Mendel's law of segregation) before birth (prospectively), a genetic case control study can be thought of as a "natural", randomized controlled trial.
The GWAS technology is based on the popular hypothesis that common diseases are associated with common genetic variants [
9]. However, GWAS results probably explain only a few percent of the apparent genetic variance contributing to common diseases [
10]. Some limitations of the GWAS approach (lack of power due to insufficient sample size, phenotypic heterogeneity) may be solved, but others (only selected single nucleotide variants with frequent alleles are genotyped) are intrinsic to the microarray technology. It is to be expected that other genetic techniques (whole exome sequencing studies or analysis of rare copy number variation [
11]) will identify other types of genetic variation (
de novo mutations, rare mutations, structural aberrations) that contribute to the risk for stroke [
12,
13].
The currently published GWAS is a milestone in stroke genetics for several reasons: it demonstrates the power of very large multicenter study samples, advocates the study of distinct stroke subtypes, replicates findings of previous stroke GWAS and identifies a new associated genetic variant. Moreover, the authors introduce a statistical model to demonstrate the subtype-specificity of the identified associations. Accordingly, the association near the
PITX2 and
ZNFX3 genes was confirmed to be specific for cardioembolic stroke, as to be expected [
14], since these variants were associated with atrial fibrillation, a major risk factor for cardiac embolism. The association of the
ANRIL locus (chromosome 9p21 locus) with LVD seemed less specific. Indeed, alleles of this locus were associated with a broad variety of vascular conditions, including myocardial infarction, type 2 diabetes mellitus, aortic aneurysm and intracranial aneurysm [
15,
16].
SNP microarray studies start from the "common diseases/common genetic variants" hypothesis. However, the current GWAS study suggests that stroke genetics develops towards the study of multiple distinct stroke subtypes instead of a "common stroke" phenotype. Future analysis of well defined stroke subtypes and of a combination of multiple risk alleles [
17] may lead to the identification of high-risk multilocus genotype patterns, but the population frequency of such allelic combinations will be low. Hence, fragmentation of the stroke phenotype into genetically homogeneous subtypes and their association with specific genetic risk profiles may lead away from the GWAS methodology and from the "common disease/common genetic variants" hypothesis towards the identification of personalized genetic blueprints as predictors of individual disease risks.
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