Genetic risk loci for Parkinson's disease: Moving from state to trait?

Although the identification of monogenic forms of Parkinson disease (PD) is “coming of age” this year— 18 y after the identification of the alpha-Synuclein (aSyn) gene as the first example of a causative gene—the past 6 y have seen major efforts toward identifying genetic risk factors for the idiopathic form of PD. In idiopathic PD, genetic factors exert a variable and moderate effect at best, and no large pedigrees are available to search for a genetic contribution to the disease. Therefore, a hypothesis-free, systematic approach is necessary in this setting, which became available through the advent of genome-wide association studies (GWAS) in the past decade. The GWAS assess the association between millions of polymorphisms, that is, single-nucleotide polymorphisms (SNP), across the entire genome and a phenotype of interest, such as PD case-control status, based on data from one single experiment using specific genomewide microarrays. All published PD GWAS have consistently identified a number of risk loci, with a-Syn and tau being the most established top hits (www. pdgene.org). This was recently confirmed and amended by six new risk loci in the largest metaanalysis carried out in an impressive number of 13,708 cases and 95,282 controls, which resulted in the identification and replication of a total of 28 independent risk SNPs for PD across 24 gene loci. Importantly, SNPs assessed in GWAS can be informative markers tagging chromosomal regions associated with disease, but often do not represent the actual variants exerting a direct functional effect. Currently, GWAS have typically focused on disease risk as a marker of state and are designed as casecontrol studies comparing unrelated patients and controls. From a clinical point of view, however, individual disease characteristics are just as important as disease risk. In this issue of Movement Disorders, Nalls et al. and Lill et al. present the first genetic association studies on a trait of PD, in this case age at onset. They both based the selection of genetic markers on the above-mentioned GWAS meta-analysis and examined two independent cohorts. Nalls and colleagues investigated 28 loci in 6,249 PD patients and built a “weighted genetic risk score” by summing up individual PD risk alleles present in each patient and weighing them by their effect size described in the GWAS meta-analysis. Patients with a score 1 standard deviation above the mean had a 37-d earlier age at onset than the patients within the standard deviation, however, explaining only 0.7% of the variance in age at onset. The only single variant significantly associated with age at onset was SNP in the TMEM175 gene. In an independent study also published in the present issue, Lill et al. analyzed risk SNPs selected from the same original publication in a different sample of 1,526 Danish PD patients for their impact on age at onset. Intriguingly, they also observed a significant effect of the same SNP in TMEM175 associated with an even 1.2-y decreased age at onset per risk allele. However, the main effect they observed is connected to an SNP in the Glucocerebrosidase gene (GBA) and corresponds to a 3.6-y earlier age at onset per risk allele. This SNP was also assessed in the Nalls et al. study, where it showed a direction of effect in the same direction and a similar effect size, albeit not reaching significance. This finding of comparable results in two entirely independent studies is remarkable, given that previous candidate–gene association studies on PD have frequently not stood the test of replication. Possible explanations include that the candidate gene selection for the age at onset assessments was based on a largescale GWAS meta-analysis of PD risk variants, which may have a higher prior probability of also affecting age at onset in comparison with other “candidate genes,” and that both studies assess a comparatively large number of cases. Biologically, GBA is a very plausible candidate, because it represents one of the strongest -----------------------------------------------------------*Correspondence to: Prof. Christine Klein, MD, Institute of Neurogenetics, University of L€ ubeck, Ratzeburger Allee 160, L€ ubeck, 23538, Germany, e-mail: christine.klein@neuro.uni-luebeck.de