This population-based study investigates the cumulative association of established genetic risk factors for Parkinson disease with cognitive impairment and reexamines the association of the polygenetic risk score with motor progression and survival among patients with Parkinson disease.
Key Points
Question
Do genome-wide association study–identified susceptibility risk loci for Parkinson disease modify cognitive and motor symptom progression?
Findings
In this population-based study of 285 patients with Parkinson disease, a higher polygenic risk score based on 23 Parkinson disease genome-wide association study–identified single-nucleotide polymorphisms was associated with faster cognitive decline and progression of motor symptoms. Results did not change after removing GBA loci from the risk score.
Meaning
Susceptibility risk alleles had a cumulative association with cognitive and motor decline in Parkinson disease; these alleles may influence not only Parkinson disease susceptibility but also disease progression in multiple domains.
Abstract
Importance
Genetic factors have a well-known influence on Parkinson disease (PD) susceptibility. The largest genome-wide association study (GWAS) identified 26 independent single-nucleotide polymorphisms (SNPs) associated with PD risk. Among patients, the course and severity of symptom progression is variable, and little is known about the potential association of genetic factors with phenotypic variance.
Objective
To assess whether GWAS-identified PD risk SNPs also have a cumulative association with the progression of cognitive and motor symptoms in patients with PD.
Design, Setting, and Participants
This longitudinal population-based cohort study of 285 patients of European ancestry with incident PD genotyped 23 GWAS SNPs. One hundred ninety-nine patients were followed up for a mean (SD) of 5.3 (2.1) years for progression (baseline: June 1, 2001, through November 31, 2007; follow-up: June 1, 2007, through August 31, 2013, with mortality surveillance through December 31, 2016); 57 patients had died or were too ill for follow-up, and 29 withdrew or could not be contacted. Movement disorder specialists repeatedly assessed PD symptom progression.
Main Outcomes Measures
The combined association of PD risk loci, after creating a weighted polygenic risk score (PRS), with cognitive decline, motor progression, and survival, relying on Cox proportional hazards regression models and inverse probability weights to account for censoring.
Results
Of the 285 patients undergoing genotyping, 160 were men (56.1%) and 125 were women (43.9%); the mean (SD) age at diagnosis was 69.1 (10.4) years. The weighted PRS was associated with significantly faster cognitive decline, measured by change in the Mini-Mental State Examination (hazard ratio [HR] per 1 SD, 1.44; 95% CI, 1.00-2.07). The PRS was also associated with faster motor decline, measured by time to Hoehn & Yahr Scale stage 3 (HR, 1.34; 95% CI, 1.00-1.79) and change in Unified Parkinson’s Disease Rating Scale part III score (HR, 1.42; 95% CI, 1.00-2.01).
Conclusions and Relevance
Susceptibility SNPs for PD combined with a cumulative PRS were associated with faster motor and cognitive decline in patients. Thus, these genetic markers may be associated with not only PD susceptibility but also disease progression in multiple domains.
Introduction
Parkinson disease (PD) is the second most common neurodegenerative disorder worldwide. Although PD is typically described in terms of motor dysfunction, nonmotor features are common. Cognitive impairment in particular is frequent in PD and especially detrimental to patients’ quality of life and increases in caregiver burden. Furthermore, the rates of symptom development and symptom severity in PD are highly heterogeneous. Identifying factors that influence progression could provide insight into etiologic pathways and ultimately prevention and therapies.
Idiopathic PD likely has a considerable genetic component. Genome-wide association studies (GWASs) have successfully identified 26 independent single-nucleotide polymorphisms (SNPs) associated with PD at a genome-wide significance level (α = 5 × 10−8). The risk alleles of several of these PD loci may also lower the age of PD onset. However, the cumulative influence of these risk loci on onset age, as assessed with a constructed polygenic risk score (PRS), is rather small.
On the other hand, the collective association of these PD genetic risk loci with other PD phenotypes, including disease progression and survival, is largely unexplored. A Nordic study generated a PRS based on 19 GWAS SNPs in 336 patients and found that the PRS estimated a faster time from diagnosis to Hoehn & Yahr Scale (H&Y) stage 3 but was not associated with patient survival. To our knowledge, no study has yet assessed the association of a PD GWAS PRS with cognitive decline during disease progression.
Thus, the aim of the present study was to investigate for the first time, to our knowledge, the cumulative association of established PD genetic risk factors with cognitive impairment. Furthermore, we reexamined the association of the PRS with PD motor progression and survival.
Methods
Participants
The Parkinson Environment and Gene (PEG) study is a population-based study in central California. More details on recruitment methods, case definition criteria, and the longitudinal patient cohort have been published previously. Patients with idiopathic PD diagnosed less than 3 years previously were recruited from June 1, 2001, through November 31, 2007. Patients were confirmed as having clinically probable or possible PD by a team of movement disorder specialists, led by one of us (J.M.B.), and were generally cognitively unimpaired at baseline. All procedures described were approved by the UCLA human subjects committee, and written informed consent was obtained from all participants.
Initially, 360 patients with PD were enrolled. We limited our study sample to patients of European ancestry (n = 285), all of whom are included in the survival analyses. We assessed symptom progression during 1 to 3 follow-up examinations by our movement disorder team (June 1, 2007, to August 31, 2013; mean [SD] follow-up, 5.3 [2.1] years; mean [SD] time from disease onset, 7.3 [2.8] years). We reexamined 199 patients (69.8%) during follow-up (57 had died or were too ill to participate in follow-up, and 29 withdrew or could not be contacted). A total of 192 participants provided the biosamples and data necessary for analyses of cognitive and motor symptom progression.
PD Symptom Assessment
Trained interviewers collected detailed information on demographic and risk factors. UCLA movement disorder specialists conducted in-person physical examinations to record progression for each participant. Motor symptoms were assessed with the Unified Parkinson’s Disease Rating Scale part III (UPDRS-III; range, 0-108, with higher scores indicating worse motor symtoms). If possible, patients were examined functionally while not receiving PD medications (off-score; 229 [80.4%] at the baseline examination and 146 [79.8%] at follow-up). For patients only examined while receiving medication (on-score), we estimated an off-score by adding the difference of the whole study population’s mean off- and on-scores at the time of examination to the patient’s on-score. During the examination, the neurologists also assigned patients to one of the modified H&Y stages (1-5, with higher stages indicating worse motor symptoms) based on the clinical descriptions of each stage. Cognitive function was assessed with the Mini-Mental State Examination (MMSE; range, 0-30, with lower scores indicating worse cognitive function) at the same neurologic examination, although after the off-score UPDRS-III examination, patients were asked to take their PD medications as needed.
Outcomes
Survival
Continued mortality surveillance has been performed throughout the PEG follow-up, primarily through vital statistics data, review of public obituaries, and continued active follow-up with patients and their families. Although our patients were examined last by study neurologists in 2013, mortality surveillance extended to December 31, 2016, which was 16 years after our study began (2001), with as many as 19 years of passive follow-up for mortality for patients first diagnosed in 1998.
Cognitive Decline
Cognitive decline was determined with the MMSE. Multiple studies investigating reliable change indices, which provide estimates of the probability that an individual’s change in test scores is not due to chance, have suggested that a reliable change in MMSE score during long intervals is 3 to 4 points. Because our mean (SD) follow-up was 5.3 (2.1) years (Table 1), we defined cognitive decline as a 4-point decrease from baseline MMSE score and time to event as the time from the baseline to follow-up examinations in which a 4-point decrease was first measured.
Table 1. Demographic and Outcome Characteristics of the Follow-up Cohort.
Characteristic | Data |
---|---|
Age at diagnosis, mean (SD), y | 69.1 (10.4) |
Age at baseline examination, mean (SD), y | 71.1 (10.3) |
Male, No./total No. (%) | 160/285 (56.1) |
PD duration at baseline examination, mean (SD), y | 2.0 (1.4) |
PD duration at last follow-up, mean (SD), y | 7.3 (2.8) |
Follow-up, mean (SD), ya | 5.3 (2.1) |
Survival | |
Registered deaths, No./total No. (%) | 166/285 (58.2) |
Observation time from baseline examination, mean (SD), yb | 8.1 (3.7) |
Age at death, mean (SD), y | 81.4 (7.3) |
MMSE cognition score (n = 191)c | |
Mean change per 5 y, mean (SD) | −0.9 (2.5) |
Fast cognitive decline (decrease in score ≥4 points), No./total No. (%) | 32/191 (16.8) |
Observation time from baseline examination, mean (SD), yb | 5.2 (2.1) |
Mean change per 5 y among 32 patients with fast cognitive decline | −5.1 (3.7) |
H&Y stage (n = 192)a,d | |
Baseline ≥3, No./total No. (%) | 23/192 (12.0) |
Observed conversion from <3 to ≥3, No./total No. (%) | 57/192 (29.7) |
Observation time from baseline examination, mean (SD), yb | 4. 9 (2.0) |
UPDRS-III motor score (n = 183)e,f | |
Change per 5 y, mean (SD) | 8.2 (12.5) |
Fast motor progression (increase in score ≥20 points), No./total No. (%) | 41/183 (22.4) |
Observation time from baseline examination, mean (SD), yb | 5.6 (1.8) |
Change per 5 y among 183 patients with fast motor progression, mean (SD) | 24.4 (18.7) |
Abbreviations: H&Y, Hoehn & Yahr Scale; MMSE, Mini-Mental State Examination; PD, Parkinson disease; PRS, polygenic risk score; UPDRS-III, Unified Parkinson’s Disease Rating Scale part III.
Includes 192 patients with available data.
Indicates time to event or censoring.
Scores range from 0 to 30, with lower scores indicating worse cognitive function.
Stages range from 1 to 5, with higher stages indicating worse motor symptoms.
Includes 183 patients.
Scores range from 0 to 108, with higher scores indicating worse motor symptoms.
Motor Decline
Changes of 2.5 to 5.2 points on the UPDRS-III motor score represent clinically meaningful differences. We thus defined fast motor progression, based on the mean 5.3 years of follow-up, as a 20-point increase in UPDRS-III score (mean of 4 points per year) and time to event as the time from the baseline to follow-up examinations in which a 20-point increase was first measured.
H&Y Stage
Previous research using a PRS investigated conversion to H&Y stage 3. Time to conversion to H&Y stage 3 was defined as the time from the baseline to first follow-up examinations in which the patient scored at least stage 3. The 23 patients with this score at baseline (Table 1) were excluded from these analyses.
Genotyping and Calculation of the Weighted PRS
Participants provided biospecimens (blood or saliva) from which we extracted DNA. The SNPs were selected based on published GWASs (eTable 1 in the Supplement). Genotyping was performed using a high-throughput system (BioMark HD; Fluidigm Corporation). Of all 26 SNPs showing genome-wide significant evidence for association with PD risk in the latest GWAS meta-analysis, 23 SNPs were successfully genotyped. The genotyping assays of SNPs rs8118008 and rs7681154 did not work properly, and rs13201101 failed our genotyping efficiency criterion (ie, <97%). The genotyping efficiency for the remaining 23 SNPs was greater than 99.6%. Furthermore, all SNPs were in Hardy-Weinberg equilibrium in PEG controls (significance cutoff of α = .002 based on Bonferroni correction for 23 SNPs) as determined based on Pearson χ2 test implemented in the PLINK tool set (version 1.07; http://zzz.bwh.harvard.edu/plink/).
The PRS was calculated using R software (version 3.3.1; https://www.r-project.org). This score is defined as the sum of the number of risk alleles per individual weighted by their β coefficient (ie, their effect size estimate corresponding to the logarithm of the odds ratio, as described by Nalls et al and Purcell et al). We extracted the β coefficients from the combined discovery and replication stage analysis of Nalls et al so that the weights were ascertained independently from the data set used for the present study. We standardized the PRS by z transformation.
Statistical Analysis
To assess associations between the PRS and the survival and progression outcomes, we used Cox proportional hazards regression models to estimate hazard ratios (HRs) with 95% CI and a Wald χ2 test for significance (α = .05). Each outcome was modeled individually. In each model, we controlled for sex and age at diagnosis. For the MMSE and UPDRS-III, we chose not to analyze the rate of change as a continuous variable. Symptom progression is likely to be nonlinear; thus, we selected analyzing time to meaningful differences based on changes in UPDRS-III motor and MMSE scores (as described in the Outcomes subsection of the Methods section).
When estimating the associations for progression outcomes, we were forced to restrict our analysis to an uncensored subset of the cohort for whom we had ascertained outcome information (n = 192). To account for the possibility of selection bias from right censoring, we used inverse probability of censoring weights (IPCW) to create a pseudopopulation mimicking the total population before censoring in distribution of measured covariates. We then estimated the associations between the PRS and progression outcomes in the pseudopopulation. The outcomes of participants lost to or unavailable for follow-up are represented in the pseudopopulation by increasing the weight given to the outcomes of participants with similar measured covariates who were included (ie, had outcome information). We used logistic regression to calculate the probability of being censored, including covariates in the model that may be related to loss to follow-up and PD progression (age at PD diagnosis, sex, years of schooling, baseline MMSE score, baseline UPDRS-III score, and H&Y stage 3) and the PRS.
We conducted sensitivity analyses excluding the 2 GBA (OMIM 606463) SNPs (rs35749011 and rs114138760) from the PRS to assess whether results were driven by GBA. We used SAS software (version 9.4; SAS Institute) for analyses. Unless otherwise indicated, data are expressed as mean (SD).
Results
Of the 285 patients undergoing genotyping, 160 were men (56.1%) and 125 were women (43.9%); the mean age at diagnosis was 69.1 (10.4) years. Demographic and outcome frequencies and characteristics of the European ancestry–only cohort can be found in Table 1. The mean duration of PD at the baseline examination was 2.0 (1.4) years. The cohort was followed up for a mean of 5.3 (2.1) years for symptom progression (ie, 7.3 [2.8] years after onset of disease).
Of the 285 European ancestry–only participants enrolled at baseline, 166 (58.2%) died, with a mean time to death or censoring from baseline of 8.1 (3.7) years. Among the 192 participants with follow-up data, the mean change in the MMSE was −0.9 (2.5) points per 5 years. However, among the 32 of 191 patients with a decrease of at least 4 points (16.8%), the mean change was −5.1 (3.7) points per 5 years. Among the 183 patients with data available, the mean change in the UPDRS-III score was 8.2 (12.5) points per 5 years and 24.4 (18.7) points per 5 years among the 41 patients with an increase in score of 20 points or more (22.4%) (Table 1). Correlations among our outcome results in the follow-up cohort can be found in eTable 2 in the Supplement. Although motor outcomes (change in the UPDRS-III score and H&Y stage 3) were correlated (ρ = 0.43; P < .001), the cognitive outcome was only weakly correlated with other outcomes (range, ρ = 0.17 to ρ = 0.26).
Table 2 provides the results for the PRS and each outcome analyzed. Estimates for progression events were obtained using IPCW; eTable 3 in the Supplement gives the estimates from analyses that did not apply IPCW. We did not observe an association between the PRS and survival. However, we found that a higher PRS was associated with faster time to cognitive and motor events. We found that the PRS was associated with faster (4-point) decrease on the MMSE, such that a 1-SD increase in PRS corresponds to an HR of 1.44 (95% CI, 1.00-2.07). The effect size remained similar when we removed GBA from the PRS (HR, 1.42; 95% CI, 0.98-2.07). A higher PRS also tended to be associated with motor symptom progression, including a 20-point UPDRS-III increase (HR, 1.42; 95% CI, 1.00-2.01) and progression to H&Y stage 3 (HR, 1.34; 95% CI, 1.00-1.79). Again, results were similar and formally statistically significant when we removed GBA SNPs from the score for a UPDRS-III 20-point decrease (HR, 1.50; 95% CI, 1.05-2.14) and progression to H&Y stage 3 (HR, 1.36; 95% CI, 1.01-1.83; Table 2).
Table 2. Estimated HRs for Clinical Outcomes in PD and PRSa.
Outcome | Full PRS | PRS excluding GBA loci | Pihlstrøm et al, 2016 | |||
---|---|---|---|---|---|---|
HR (95% CI) | P Value | HR (95% CI) | P Value | HR (95% CI) | P Value | |
Survival | 1.08 (0.79-1.47) | .62 | 1.09 (0.78-1.52) | .63 | 1.13 (0.88-1.45) | .32 |
Time to MMSE 4-point decreaseb | 1.44 (1.00-2.07) | .049 | 1.42 (0.98-2.07) | .07 | NA | NA |
Time to UPDRS III 20-point increasec | 1.42 (1.00-2.01) | .051 | 1.50 (1.05-2.14) | .03 | NA | NA |
Time to conversion to H&Y stage ≥3d | 1.34 (1.00-1.79) | .054 | 1.36 (1.01-1.83) | .045 | 1.29 (1.06-1.56) | .01 |
Abbreviations: HR, hazard ratio; H&Y, Hoehn & Yahr Scale; MMSE, Mini-Mental State Examination; NA, not applicable (outcome not investigated); PD, Parkinson disease; PRS, polygenic risk score; UPDRS-III, Unified Parkinson’s Disease Rating Scale part III.
Cox proportional hazards regression models were used to estimate HRs, including sex and age at diagnosis as covariates. Estimates for time to MMSE, UPDRS-III, and H&Y events were obtained using inverse probability of censoring weighting. P values were calculated using the Wald χ2 test.
Scores range from 0 to 30, with lower scores indicating worse cognitive function.
Scores range from 0 to 108, with higher scores indicating worse motor symptoms.
Stages range from 1 to 5, with higher stages indicating worse motor symptoms.
Discussion
We assessed the association of a PRS with disease progression in a longitudinal population-based cohort of patients with PD. We newly suggest that the PRS, based on the established PD GWAS risk loci, is associated with cognitive decline and validates previous findings of a collective association of these risk variants with motor symptom progression. Furthermore, we support the previous observation that PD risk variants are not cumulatively associated with survival among patients.
Cognitive impairment and dementia are well established disorders in PD. As many as 80% of patients with PD who are alive 10 years after diagnosis are expected to develop dementia. Despite the high prevalence, our understanding of pathogenic mechanisms is limited, and treatments are largely unsuccessful. To our knowledge, all patient cohorts investigating cognitive impairment in PD have used candidate gene approaches. For instance, GBA, one of the most important genetic risk factors for PD, has also been implicated in cognitive impairment in PD. Other studies have assessed the role of LRRK2, MAPT, and SNCA for dementia in PD, but results have often been inconclusive or not been replicated independently. For the first time to our knowledge, we linked the cumulative burden of PD genetic risk factors with patients’ cognitive decline.
Although the MMSE is among the most widely used screening instruments for cognitive impairment, not all changes in score reflect true clinical change. Furthermore, multiple cut points have been suggested as thresholds for cognitive impairment and dementia, mostly 26 or less to 24 or less. Multiple independent studies have shown that changes of 3 to 4 points in MMSE score during longer intervals are necessary to conclude with 90% confidence that an individual has experienced a reliable functional change. Thus, we selected a 4-point decrease in MMSE score to define a meaningful cognitive decline (by definition, all patients with a 4-point decrease will have scores ≤26).
The only study to explore progression of motor symptoms with a PRS (based on 19 PD SNPs) followed up 336 Nordic patients in tertiary care and reported faster progression to H&Y stage 3 with increasing score (HR per 1 SD, 1.29; 95% CI, 1.06-1.56). Because PD is a gradually progressive disorder, moving from one H&Y stage to another generally takes several years, and H&Y stage 3 signifies the point when disability advances from mild to moderate and the appearance of postural instability. We have replicated this finding in our own community-based study (HR per 1 SD, 1.34; 95% CI, 1.00-1.79), providing additional evidence for a multiloci genetic component in PD motor progression.
We also examined changes in UPDRS-III motor scores. Shulman et al reported that changes of 2.5 to 5.2 points on the UPDRS-III represent clinically meaningful differences, with 10.8 points corresponding to a 1-stage change on the H&Y. We selected a 20-point increase in UPDRS-III score, corresponding to a clinically meaningful 4-point annual change in score during follow-up. We found a higher PRS to be associated with a faster time to a 20-point increase. As expected, an increase of 20 points on the UPDRS-III and conversion to H&Y stage 3 were correlated in our population (Spearman coefficient, r = 0.43; P < .001) (eTable 2 in the Supplement), indicating that both measures likely capture some of the same features of motor progression. The UPDRS-III and H&Y were assessed throughout the study by the same team of movement disorder specialists, led by one of us (J.M.B.), trained to evaluate patients in a standardized fashion. Thus, we did not expect much misclassification owing to differences in how clinicians conducted examinations. However, 89 of our participants (31.2%) could not perform at least 1 neurologic examination while in a functional off-medication state. We estimated UPDRS-III off-scores based on the study population means. However, this procedure is still likely to cause some misclassification of motor severity for patients with on-scores. We expect this misclassification to be nondifferential with respect to the PRS because the PRS does not predict medication status at any of the examinations. In addition, not enough patients had only on-score examinations to determine whether our off-score findings are consistent across medication status. This determination would be interesting when considering whether attributed genetic effects may also be related to levodopa responsiveness. Furthermore, although the MMSE was done after the UPDRS-III motor examinations, patients were allowed to take PD medications as needed after motor examinations.
The influence of GBA mutations on PD risk is well established. The weight of evidence supports that carriers of GBA mutations are not only at a higher risk of PD but also have an earlier age at onset and are more likely to develop cognitive dysfunction. Thus, we conducted sensitivity analyses after excluding variants in the GBA locus to determine whether our results for the PRS were driven by GBA. Estimated effect sizes did not change meaningfully (Table 2), suggesting that the remaining multiple genetic variants together contribute to faster progression cumulatively.
Strengths and Limitations
Our study is one of less than a handful of population-based prospective PD cohorts worldwide and the only study, to our knowledge, to investigate PD risk loci with a PRS and cognitive decline. Although we were unable to follow up all patients with PD enrolled at baseline because loss to follow-up occurred primarily owing to death and illness, we conducted IPCW statistical analyses to account for selective survival. This form of internal adjustment corrects for censoring, which is modeled as a function of measured baseline risk factors and PD symptom levels that affect censoring and the PD progression end points under study. However, this method can only account for factors included in the censoring model. Other unmeasured factors likely influence loss to follow-up, and thus some remaining selection bias is possible.
A notable strength in our study is the well characterized PD population. All our patients were personally examined by the same UCLA movement disorder specialists throughout the study, which minimizes outcome misclassification. Furthermore, follow-up began early in the disease course (within 3 years of diagnosis), allowing us to track the natural history of progression. Because of our community-based design, our results are more generalizable to average PD populations than patient cohorts assembled at tertiary care centers.
Conclusions
Ultimately, identifying genetic markers associated with faster progression may help elucidate pathogenesis and inform further research. Although replication is needed, our results support the collective involvement of PD susceptibility risk alleles in cognitive and motor decline, suggesting that these alleles may be associated with not only PD susceptibility but also disease progression in multiple domains. Our findings support a polygenic architecture contributing to PD progression, as has been suggested for PD susceptibility, and suggest that progression in PD may, at least in part, be driven by an accumulation of many common genetic variants, each individually having a relatively small effect size.
eTable 1. PD Risk Variants Included in the Calculation of the Genetic Risk Score
eTable 2. Correlation Among the Outcome Events Under Study in the Follow-up Cohort
eTable 3. Estimated Hazards for Clinical Outcomes in PD and Genetic Risk Score Without IPCW
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
eTable 1. PD Risk Variants Included in the Calculation of the Genetic Risk Score
eTable 2. Correlation Among the Outcome Events Under Study in the Follow-up Cohort
eTable 3. Estimated Hazards for Clinical Outcomes in PD and Genetic Risk Score Without IPCW