Parkinson’s disease (PD) will become more prevalent in the next decades as the world’s population ages.Although PD is diagnosed based on its motor symptoms, PD includes a wide range of non-motor symptoms. Two symptoms, in particular, significantly decrease quality-of-life: hallucinations and dyskinesia. Hallucinations are an important co-morbidity and dyskinesia is a common treatment-related complication. This dissertation analyzes the genetic risk factors for both dyskinesia and hallucinations, and identifies specific genetic variants and combinations of genetic variants that are associated with a higher risk of developing these symptoms.

In the first study, a large population-based study (PEG) was used to establish the association between four candidate genes (DRD1, DRD2, DRD3 and BDNF) and dyskinesia. This study consisted of 418 patients whose diagnosis was confirmed by a movement disorder specialist, who were using levodopa, and who had a minimum of three years disease duration at the time of assessment. Applying Haploview and Phase, haploblocks for DRD1-3 and BDNF were created. Risk scores for DRD2 and DRD3 were generated. Risk ratios were calculated using Poisson regression with robust error variance. One haplotype in each DRD2 haploblock was associated with a 29% to 50% increase in dyskinesia risk. For each unit increase in risk score we observed a 16% increase in dyskinesia risk for DRD2 (95%CI: 1.05-1.29) and a 17% (95%CI: 0.99-1.40) increase for DRD3. The BDNF haploblock was not associated, but the minor allele of the rs6265 SNP was associated with dyskinesia (adjusted RR 1.31 (95%CI: 1.01-1.70)). Among the candidate genes for dyskinesia the following were genetic risk factors for dyskinesia: several haplotypes in DRD2, possibly some haplotypes in DRD3, and the minor allele of rs6265 in BDNF. Among PD patients, there is a constant tradeoff between increasing medication to address PD symptoms and increasing the risk of dyskinesia. Genetic information could help prevent or postpone this debilitating consequence of treatment and may improve patient-centered, personalized therapy. Future studies are needed to confirm our findings and quantify the benefits of implementing a personalized treatment based on a genetic risk score. PD patients with these genetic variants may be prime candidates for treatments aiming to prevent or delay the onset of dyskinesia.

The second and third study are based on three longitudinal PD cohorts: two population-based studies (ParkWest and PEG) and one international clinic-based study (PPMI). The population was restricted to Caucasians only (N=745). The second and third study in this dissertation analyze the association between polygenic risk scores (PRS) and hallucinations. In the second study, we describe the strengths and limitations of a PRS. In addition, a PRS for hallucinations based on PD candidate genes was generated and validation was attempted. The PEG and PW studies were used for the creation of the PRS, and the PPMI was used for validation. Unfortunately, the PRS generated with the two population-based studies could not be replicated, most likely due to the sample size. A second PRS was created based on a large GWAS for PD. Based on the findings from a pooled analysis of all three studies, the hallucinations PRS, based on the GWAS, indicated that the following genes might contribute to increased risk of developing hallucinations in PD: LRRK2, APOE, SLC6A4, BDNF and MAPT.

In the third study, the overlap of the genetic architecture for Alzheimer’s disease (AD) and schizophrenia (SZ) with Parkinson’s hallucinations was assessed. For this purpose, two PRS were created. Both PRS were based on previously performed, large GWAS; one for SZ and one for AD. Various PRS were created using different p-value thresholds. The full PRS model, using all SNPs consisted of over 70,000 SNPs (AD and SZ). The genetic risk for hallucinations appears to differ by age at onset of PD. Stratifying by younger (<60 years) and older (60+ years) age at diagnosis, the SZ-PRS was associated with an increased risk for hallucinations among young PD patients (adjusted OR=1.18 (95%CI: 1.03-1.35, p-value 0.02). The AD-PRS was positively associated with hallucinations in older onset PD patients (adjusted OR=1.27 (95%CI: 1.08-1.50, p-value 0.005). The results suggest that the biological mechanisms for hallucinations may depend on age at diagnosis. Among young onset PD patients, SZ susceptibility factors may play a role in the development of hallucinations. In contrast, among older onset PD patients, hallucinations appear to be influenced by the genetic architecture seen in AD that contributes to cognitive decline.