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October 2020; 6 (5) ArticleOpen Access

Genetic risk scores and hallucinations in patients with Parkinson disease

Cynthia D.J. Kusters, Kimberly C. Paul, Aline Duarte Folle, Adrienne M. Keener, Jeff M. Bronstein, Valerija Dobricic, Ole-Bjørn Tysnes, Lars Bertram, Guido Alves, Janet S. Sinsheimer, Christina M. Lill, Jodi Maple-Grødem, Beate R. Ritz
First published July 20, 2020, DOI: https://doi.org/10.1212/NXG.0000000000000492
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Abstract

Objective We examine the hypothesized overlap of genetic architecture for Alzheimer disease (AD), schizophrenia (SZ), and Parkinson disease (PD) through the use of polygenic risk scores (PRSs) with the occurrence of hallucinations in PD.

Methods We used 2 population-based studies (ParkWest, Norway, and Parkinson's Environment and Gene, USA) providing us with 399 patients with PD with European ancestry and a PD diagnosis after age 55 years to assess the associations between 4 PRSs and hallucinations after 5 years of mean disease duration. Based on the existing genome-wide association study of other large consortia, 4 PRSs were created: one each using AD, SZ, and PD cohorts and another PRS for height, which served as a negative control.

Results A higher prevalence of hallucinations was observed with each SD increase of the AD-PRS (odds ratio [OR]: 1.37, 95% confidence interval [CI]: 1.03–1.83). This effect was mainly driven by APOE (OR: 1.92, 95% CI: 1.14–3.22). In addition, a suggestive decrease and increase, respectively, in hallucination prevalence were observed with the SZ-PRS and the PD-PRS (OR: 0.77, 95% CI: 0.59–1.01; and OR: 1.29, 95% CI: 0.95–1.76, respectively). No association was observed with the height PRS.

Conclusions These results suggest that mechanisms for hallucinations in PD may in part be driven by the same genetic architecture that leads to cognitive decline in AD, especially by APOE.

Glossary

AD=
Alzheimer disease;
aOR=
adjusted odds ratio;
CI=
confidence interval;
GWAS=
genome-wide association study;
MDS-UPDRS=
Movement Disorder Society–Unified Parkinson Disease Rating Scale;
MMSE=
Mini-Mental State Examination;
PD=
Parkinson disease;
PEG=
Parkinson's Environment and Gene;
PK=
ParkWest;
PRS=
polygenic risk score;
SZ=
schizophrenia

Parkinson disease (PD) is the second most common neurodegenerative disease worldwide after Alzheimer disease (AD). Associated with a decreased health-related quality of life and increased mortality, hallucinations are an important nonmotor symptom among patients with PD.1,2

Prolonged disease duration is a major risk factor for hallucinations, and one hypothesis is that neurodegenerative changes are responsible for the onset of hallucinations. A well-known disease with hallucinations is schizophrenia (SZ), although hallucinations in SZ differ in characteristics from those in PD. Furthermore, hallucinations often co-occur with cognitive decline, and the genetic underpinnings of the pathomechanisms related to AD or SZ may be relevant.3,4

Studies aimed to identify genetic risk factors for hallucinations reported conflicting results, as discussed in various review articles.5,–,7 However, these studies tested candidate genes, and no study has taken a comprehensive look at the genetic architecture of SZ, AD, or PD using polygenic risk scores (PRSs) and their association with hallucinations among patients with PD.

Here, we used existing genome-wide association study (GWAS) results from large consortia for AD, SZ, or PD to first create PRS. Then, we examined the hypothesized overlap between genetic burdens for AD, SZ, and PD susceptibility and hallucinations among patients with PD using 2 longitudinal studies of PD progression.

Methods

This study combines 2 separate population-based patient cohorts: The Parkinson's Environment and Gene (PEG) study and the Norwegian ParkWest (PW) study.

The PEG study began as a population-based case-control study among residents of the Central Valley of California, United States. The specifics of this study have been described previously.8 In this article, we used information from the cohort of patients with PD that was followed between 2001 and 2019. These patients with PD were clinically classified by movement disorder neurologists as probable idiopathic PD according to published criteria.9 See extensive information regarding the patient recruitment in appendix e-1, links.lww.com/NXG/A297. In total, for the PEG study, we followed 434 patients with PD who provided information about the presence or absence of hallucinations.

The PW study is a longitudinal, population-based cohort of patients with PD and noncases in South and West Norway.10 All patients with incident PD diagnosed between November 2004 and August 2006 were approached for this study. Patients with PD are currently under continued follow-up, and only those with a confirmed diagnosis of PD at their latest or final clinical visit were eligible for this study. Here, we included data from 191 patients at baseline and 159 patients seen at a 5-year follow-up visit.

The presence of hallucinations was assessed using the Movement Disorder Society–Unified Parkinson Disease Rating Scale (MDS-UPDRS) in PEG, whereas PW used the UPDRS.11,12 The presence of hallucinations was considered positive when a patient or caregiver indicated the presence of illusions, hallucinations, and/or psychosis over the past week. To achieve consistency between studies in terms of disease duration for the assessment of hallucination, we used information provided at the first follow-up visit by PEG patients (on average 5.7 years after diagnosis) and from the 5-year disease duration mark for PW patients.

Genetic data

Blood samples from both studies were genotyped using a genome-wide single nucleotide polymorphism (SNP) array. The PEG study used the Global Screening Array (GSA; Illumina, Inc) chip and the PW study the Illumina Infinium OmniExpress. For pre- and post-imputation quality control, see appendix e-1, links.lww.com/NXG/A297. Phasing was performed using ShapeIT v2.r790,13 and the reference panel was HRC.r1.2016.14 We imputed SNPs using the Michigan Imputation Server, which uses Minimac3 for imputation.15 We restricted to 5,400,408 SNPs that were available in both data sets. All quality control was performed using Plink 1.9.16

For family members with estimated kinship of 12% or more (reflecting second-degree relatives or more closely related) based on estimated IBD,16 one individual was randomly selected to remain in the study. Fractional ancestry among all individuals was estimated using hidden Markov modeling and clustering (Structure 2.3.4).17 We restricted the analysis to individuals classified as the European super-population, and in the analysis, we adjusted using the fractional ancestry.

After quality control, 524 patients with PD, followed longitudinally, had provided both genotyping and hallucination information (390 in PEG and 133 in PW); of these, 447 were of European descent. We then excluded 48 patients with PD who were diagnosed at or before age 55 years to exclude potential hereditary, nonidiopathic PD leaving 399 patients with PD.

Standard protocol approvals, registrations, and patient consents

All study protocols regarding human subjects have been approved by their local institutional review board, and written consent was given by all participants.

Creation of PRSs

Four weighted sum PRSs were created using PRSice 2.1.818 based on 4 distinct sets of the GWAS, i.e., using SNPs and effect sizes found with the GWAS of AD, SZ, PD, and for height as a negative control. Each PRS is described in detail in appendix e-1, links.lww.com/NXG/A297. We clumped the data to take linkage disequilibrium into account, based on an R-squared threshold of 0.5, without a p value threshold. The final PRS included variants that had a p value less than of 5 × 10−8 in the previously performed GWAS. The allelic weights were based on the effect estimates from previous large-scale GWAS data,19,–,27 and for AD a large meta-analysis that specifically estimated the effect size for the APOE allele.28 The final score for each individual in the PD progression sample was the sum of the number of risk alleles for that individual weighted by each β-coefficient (log of the odds ratio). Each set of PRS values was then standardized using z-transformations. For specific details of each PRS, please see the additional information in appendix e-1, links.lww.com/NXG/A297.

Analysis

We performed logistic regression analysis using each PRS as a covariate and the presence of hallucinations among patients with PD during follow-up as the outcome. All analyses additionally included sex, fractional ancestry, age at diagnosis, disease duration at the time of assessment for hallucinations, and study as potential confounders through the use of a propensity score. We restricted the analysis to those individuals diagnosed after age 55 years. All analyses were performed using SAS 9.4 (SAS Institute, Cary NC).

Sensitivity analysis

As sensitivity analyses, we also performed logistic regression analyses with the total population, and a subpopulation diagnosed at or after age 60 years. In addition, we performed logistic regression analysis adjusting for various confounders and/or risk factors for hallucinations to further explore the influence of potential confounding.

For the PRS, we used a genome-wide p value threshold of 5 × 10−8. However, the p values in the GWA studies depend on the sample size, the effect size of the allele, and the type of outcome (continuous vs dichotomous). As this differed between the 4 GWASs, it is difficult to compare the PRSs with each other. Therefore, as part of our sensitivity analyses, we created 4 PRSs with the top 75 SNPs. Furthermore, we created PRSs with different p value thresholds (1 × 10−8, 1 × 10−7, 1 × 10−6, 1 × 10−5, and 1 × 10−4).

Moreover, we removed patients who reported illusions (or slight to mild hallucinations among PW patients as this study did not differentiate between illusions and hallucinations) to examine findings among those with formed hallucinations only. In addition, we performed an ordinal logistic regression to evaluate associations with severity of hallucinations symptoms. Finally, to determine whether these PRSs were associated with PD susceptibility as well as hallucinations, we performed logistic regression analysis to assess the association between the PRS with PD status among PEG patients and controls (restricted to European ancestry only and those diagnosed at or after age 56 years).

Data availability

Access to deidentified data related to this study will be made available on agreement and material transfer agreements. Requests can be made to B.R. for clinical data of PEG, to C.L. and B.R. for genetic data of PEG, and to J. M-G. for clinical and genetic data of the PW study.

Results

There were 281 patients with PD of European descent in PEG and 118 in the PW study, totaling 399 patients with PD of European ancestry. After on average 5.5 years of disease duration, hallucinations were prevalent in 53 patients (13%) during the past week at the time of their follow-up visit (table 1). Among those with hallucinations, 38 patients (72%) reported illusions or hallucinations with insight, whereas 15 patients (28%) had severe hallucinations with loss of insight, psychosis, or delusions.

View this table:
Table 1

Characteristics of patients with PD of European ancestry, diagnosed after age 55 years, stratified by study

The results of the PRS associations with hallucinations are provided in table 2. An increase in 1 SD in the AD-PRS was associated with a 37% increase in the odds of hallucinations (95% confidence interval [CI]: 1.03–1.83, table 2). The APOE-PRS of hallucinations based on APOE status alone (summing the risks for e4 or e2 alleles) showed strong effect estimates, i.e., we estimated a 92% increase in odds of hallucinations for an increase in 1 point of the APOE-PRS (which is equivalent to 1 APOE-e4 allele, 95% CI: 1.14–3.22). However, the AD-PRS on exclusion of the APOE signal also showed an association with hallucinations (adjusted odds ratio [aOR]: 1.34, 95% CI: 1.00–1.79).

View this table:
Table 2

Logistic regression for the association between schizophrenia–PRS, Alzheimer disease–PRS, PD-PRS, and the height PRS and hallucinations among 399 patients with Parkinson disease from the 2 cohorts combined (Parkinson's Environment and Gene and ParkWest)

The SZ-PRS was associated with a 23% decrease in odds (95% CI: 0.59–1.01), and every SD increase in the PD-PRS was associated with a 29% increase in the odds for the presence of hallucinations, but the 95% CI is wide (95% CI: 0.95–1.76). The height PRS was not associated with hallucinations in any of our analyses.

There was no collinearity between the 4 PRSs. When we combined all 3 PRSs (AD, SZ, and PD-PRS) in the same model, the effect estimates and CIs were very similar (table 2). However, the 95% CIs for the SZ- and PD-PRS (but not the AD-PRS) included the null.

Results sensitivity analyses

Using different subpopulation samples, the results remained similar (table 3). The estimated effect sizes for the AD-PRS, SZ-PRS, and APOE-PRS appeared slightly weaker in the total sample and stronger in the subsample diagnosed at or after age 60 years. The effect estimates for the PD-PRS and hallucinations were slightly stronger in the total population.

View this table:
Table 3

Logistic regression for the association between schizophrenia–PRS, Alzheimer disease–PRS, PD-PRS, and the height PRS and hallucinations among the total population (including those diagnosed at or before age 55 years) and the subpopulation that was diagnosed at or after age 60 years

Adjusting for cognitive status, measured with the Mini-Mental State Examination (MMSE) and assessed at the time collecting hallucination information, strengthened the effect estimate for the AD-PRS and the PD-PRS with hallucinations (AD-PRS: aOR 1.50, 95% CI: 1.10–2.05; PD-PRS: aOR 1.42, 95% CI: 1.01–2.00). Restricting to a population without cognitive decline (MMSE score ≥25) limits the sample size to only 37 patients with PD with hallucinations, but the effect estimates were similar to those after adjustment for MMSE (AD-PRS: aOR 1.45, 95% CI: 1.03–2.05; PD-PRS: aOR 1.56, 95% CI: 1.04–2.33). Adjusting for other risk factors did not change the effect estimates, although adjusting for UPDRS motor score widened the CI slightly (see table e-1, links.lww.com/NXG/A293). In addition, when adjusting for additional variables, especially rapid eye movement sleep behavior disorder and the neuropsychiatric characteristics, such as cognitive decline, depression, apathy, or anxiety scores (see table e-1), the associations between the PD-PRS and hallucinations remained similar, but the CIs narrowed.

As another sensitivity test, we also created multiple PRSs with various p value thresholds (table 4). Point estimates and SDs varied only slightly for the AD-PRS, PD-PRS, SZ-PRS, and height PRS, respectively, suggesting that a relatively small number of SNPs selected according to genome-wide statistically significant p value thresholds suffices. Specifically, adding SNPs by increasing the p value threshold appears to add precision for some (e.g., AD-PRS), but not all, PRSs. In addition, when we created PRSs with the top 75 SNPs from GWAS data, the AD-, SZ-, and PD-PRS effect estimates remained essentially the same—albeit CIs widened—and the height PRS remained unassociated with hallucinations (table 4).

View this table:
Table 4

Logistic regression for the association between the 4 PRS sets and hallucinations, using various p value thresholds and using 75 SNPs for the PRS sets among the patients with Parkinson disease from the Parkinson's Environment and Gene study and ParkWest study that were diagnosed after age 55 years (N = 399)

After removing patients with PD who reported illusions, only 29 patients with PD reported formed hallucinations. Although this decreased statistical power, the effect estimates and CIs remained very similar (see table e-2, links.lww.com/NXG/A294). The effect estimates also remained very similar when modeling the severity of hallucinations with the PRS in an ordinal logistic regression analysis (see table e-3, links.lww.com/NXG/A295).

Finally, we also assessed the association between each PRS and a PD diagnosis in the PEG study, using 1,000 individuals (484 patients with PD and 516 controls) with a diagnosis (or interview age for controls) at or after age 56 years. The only PRS we found to be associated with an increased risk for a PD diagnosis was—as expected—the PD-PRS (see table e-4, links.lww.com/NXG/A296).

Discussion

We studied whether genetic risk architecture of AD, SZ, and PD is associated with hallucinations in patients with PD. We identified an increase of hallucinations within the first 6 years after a PD diagnosis that is associated with higher AD-PRS.

The AD-PRS included a strong APOE status component. APOE regulates amyloid-beta aggregation and clearance in the brain, as well as brain lipid transport, glucose metabolism, neuronal signaling, neuroinflammation, and mitochondrial function.29 An association between APOE and cognitive decline among patients with PD has been established previously.30 Previous studies of genetic risk factors related to cognitive decline, such as APOE, and hallucinations among patients with PD have not been consistent.5,–,7 In our study, the AD-PRS without APOE still shows an association with hallucinations, suggesting that other AD-related genetic risk variants also play a role in the occurrence of hallucinations. Finally, when adjusting for cognitive decline, the association between the AD-PRS and hallucinations remained and became stronger, suggesting that the AD-PRS plays an independent role in the development of hallucinations.

The SZ-PRS showed a suggestive decrease in prevalence of hallucinations. Possible explanations for this finding include, first, that this is a chance finding; second, that we efficiently selected out of our study all SZ-related patients with parkinsonism; and third, that an underlying genetically determined SZ pathobiology leads to these opposing results. In support of this third hypothesis, SZ and PD both involve dopaminergic dysfunction. In SZ, one of the main hypotheses for the occurrence of hallucinations is an increased dopaminergic activity in the mesolimbic system. Conversely, in patients with PD, there is a depletion of striatal dopamine due to a loss of dopaminergic neurons in the substantia nigra. PD treatment aims at replacing dopaminergic activity at synapses. As neurodegeneration progresses, dopaminergic dysfunction may create imbalances in the circuitry that may lead to hallucinations, similar to the increased dopaminergic tone in the mesolimbic pathway that leads to hallucinations in SZ.31 We did not see any association between the SZ-PRS and a PD diagnosis. Together, our data suggest that the biology related to the SZ-PRS is not related to vulnerability of dopaminergic neurons in the SN; however, the effect of dopaminergic treatment in the mesolimbic pathway among patients with PD with an increased genetic risk for SZ may differ from those without a genetic risk for SZ.

Although not formally statistically significant in the primary analysis, when analyzing the association adjusting for rapid eye movement sleep behavior disorder, or neuropsychiatric characteristics (such as depression or anxiety), there appears to be an increased prevalence of hallucinations with increasing PD-PRS. Overall, this initial finding suggests that genetic risk factors for PD and the neurodegenerative processes underlying PD might also increase the risk for developing hallucinations among patients with PD.

When studying hallucinations among patients with PD, it is important to take PD disease duration into account because longer duration is known to be associated with an increase in hallucinations. Therefore, we decided to analyze the prevalence of hallucinations within on average about 5 years of disease duration, when the prevalence both in the PEG and PW study was 13%. Mortality and loss-to-follow-up in longitudinal PD studies have been shown to increase substantially after 5 years, further justifying this cutoff to minimize survival bias.

It is difficult to assess the prevalence and onset of hallucinations in PD accurately, and we had to rely on the UPDRS or MDS-UPDRS. More extensive instruments for measuring hallucinations have been developed,32 but were unavailable to us at the time we collected our data. Thus, the number of patients with hallucinations in our studies may have been underestimated. Also, patients might have developed hallucinations after the end of our follow-up, and some patients may have been reluctant to acknowledge the presence of hallucinations. Because there is no indication that the genetic score would influence this mismeasurement of the outcome differentially, outcome misclassification is probably nondifferential, and we would expect our estimates to be biased toward the null.

Using existing GWAS data for the creation of a PRS has several benefits. One benefit is the large size of these studies allowing for estimates to be precise and ensuring that the measurement errors for the weights in the PRS are minimized. Another benefit is that there is no need for validation of the PRS in a separate, independent data set, as the scores are created based on independent populations. Previous studies have provided validation for both the AD-PRS and SZ-PRS, whereas we validated the association between PD-PRS and PD diagnosis in our study.33,–,36

In genetic studies, genetic ancestry (population stratification) is a potentially large and commonly observed confounder. We restricted to individuals genetically identified as from European descent, and additionally adjusted for fractional ancestry, limiting any potential confounding in our findings. The SZ-PRS was generated in a mixed population, whereas the AD-PRS and PD-PRS were created with individuals from European ancestry only. Although the SZ-PRS was based on a mixed population, it consisted mainly of European ancestry individuals. Unfortunately, until large GWASs in diverse ethnic populations become available, it is impossible to develop ethnicity-stratified PRS, and it remains open whether the associations we report are generalizable to other ethnicities.

Hallucinations in PD appear to be associated with the genetic architecture of AD, especially as represented by APOE. There is some indication for potential associations between hallucinations and the genetic architecture of SZ and also with genetic susceptibility for PD in late-onset patients.

Study funding

No targeted funding reported.

Disclosure

C.D.J. Kusters was supported in part by the NIH Training Grant in Genomic Analysis and Interpretation T32HG002536 and the NIH grant F32AG063442. C.D.J. Kusters and K.C. Paul were supported in part by the Burroughs Wellcome Fund fellowships. A. Duarte Folle and A.M. Keener report no disclosures relevant to the manuscript. J.M. Bronstein received funding that made the PEG study available with funding from NIH grants R01-ES010544, U54-ES012078, P01-ES016732, and P50-NS038367; initial pilot funding from NIH P30-ES07048; a Community Fast Track grant by the MJFox Foundation; a pilot grant by the American Parkinson Disease Association; and from the Parkinson's Alliance. V. Dobricic and O-B. Tysnes report no disclosures relevant to the manuscript. L. Bertram received funding from the German Research Foundation for the genome-wide SNP data generation and processing of the PEG samples (DFG; FOR2488/1: GZ zLI 2654/2-1 and BE 2287/5-1). G. Alves reports no disclosures relevant to the manuscript. J.S. Sinsheimer received funding that made the PEG study available with funding from NIH grants R01-ES010544, U54-ES012078, P01-ES016732, and P50-NS038367; initial pilot funding from NIH P30-ES07048; a Community Fast Track grant by the MJFox Foundation; a pilot grant by the American Parkinson Disease Association; and from the Parkinson's Alliance. J.S. Sinsheimer is also supported in part by NIH grants HG009120 and GM053275. C. Lill received funding from the German Research Foundation for the genome-wide SNP data generation and processing of the PEG samples (DFG; FOR2488/1: GZ zLI 2654/2-1 and BE 2287/5-1) and received support by a habilitation grant (H01-2019) from the University of Lübeck. J. Maple-Grødem is supported by the grants for the ParkWest study. The Norwegian ParkWest study was supported by the Western Norway Regional Health Authority (Grant Nos. 911218, 911792, and 912049), the Research Council of Norway (Grant No. 177966), and the Norwegian Parkinson's Disease Association. B. R. Ritz received funding that made the PEG study available with funding from NIH grants R01-ES010544, U54-ES012078, P01-ES016732, and P50-NS038367; initial pilot funding from NIH P30-ES07048; a Community Fast Track grant by the MJFox Foundation; a pilot grant by the American Parkinson Disease Association; and from the Parkinson's Alliance. Go to Neurology.org/NG for full disclosures.

Acknowledgment

The authors thank all the participants in this study. Genotyping of the ParkWest cohort was supported by the Michael J. Fox Foundation and Biogen, for which the authors are thankful to Aaron Day‐Williams. They thank Dr. Fabian Kilpert at Lübeck Interdisciplinary Platform for Genome Analytics (LIGA) for GWAS data preprocessing and quality control and Mrs. Tanja Wesse, Mrs. Sanaz Sedghpour Sabet, Dr. Michael Wittig, and Dr. Andre Franke at the Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany, for assistance with GSA genotyping. The LIGA team acknowledges computational support from the OMICS compute cluster at the University of Lübeck.

Appendix Authors

Table
Table

Footnotes

  • Go to Neurology.org/NG for full disclosures. Funding information is provided at the end of the article.

  • The Article Processing Charge was funded by F32AG063442.

  • Received April 6, 2020.
  • Accepted in final form May 26, 2020.

This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND), which permits downloading and sharing the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.

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