LRRK2 gene in Parkinson disease: mutation analysis and case control association study

BACKGROUND

In addition to the four well-confirmed genes linked to early-onset Parkinson disease (PD) (SNCA, PARKIN, DJ-1, and PINK1), mutations in the leucine-rich repeat kinase 2 gene (LRRK2) have recently been identified in families with autosomal dominant late-onset PD.

OBJECTIVE

To perform mutation analysis of LRRK2 in probands of families showing dominant inheritance of PD and to conduct a case control association study to test the hypothesis that common coding variations might be associated with increased susceptibility to PD.

METHODS

All 51 LRRK2 coding exons were sequenced in 23 probands and the mutation frequencies were evaluated in 180 neurologically normal control subjects. For the association study the authors genotyped four coding LRRK2 polymorphisms in 250 normal control subjects and 121 patients with PD (predominantly white patients of Canadian origin), 84% of whom had age at onset before 50 years and 42% had a positive family history.

RESULTS

The authors identified three probands with heterozygous LRRK2 mutations: two of them have the known G2019S substitution and one proband has a novel I1371V substitution. Mutation analysis of a large family demonstrated complete segregation of the G2019S with PD. However, there was no association between PD and any of the four polymorphisms at the allelic or genotypic levels (p > 0.17). Furthermore, the authors did not detect a modifying effect for any genotype or of APOE genotypes upon the age at onset in the PD group (p > 0.20).

CONCLUSIONS

The results support the prior suggestion that LRRK2 mutations cause PD. The disease in the families reported here presents a phenotype indistinguishable from typical PD. All three families demonstrate a very variable age at onset that is not explained by APOE genotypes. The common coding variations in the LRRK2 gene neither constitute strong PD risk factors nor modify the age at onset; however, the possibility of a modest risk effect remains to be assessed in large datasets.