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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Mov Disord. Author manuscript; available in PMC 2013 April 1.
Published in final edited form as:
Published online 2012 February 16. doi:  10.1002/mds.24946
PMCID: PMC3323737

Genetic influences on cognitive decline in Parkinson's disease

J.F. Morley, MD, PhD,1,6 S.X. Xie, PhD,2,5 H.I. Hurtig, MD,1,5 M.B. Stern, MD,1,5 A. Colcher, MD,1,5 S. Horn, DO,1,5 N. Dahodwala, MD,1 J.E. Duda, MD,1,5,6 D. Weintraub, MD,3,5,6 A.S. Chen-Plotkin, MD,1,5 V. Van Deerlin, MD, PhD,4,5 D. Falcone, MS,4,5 and A. Siderowf, MD, MSCE1,5



The role of genetic factors in cognitive decline associated with Parkinson's disease is unclear. We examined whether variations in apolipoprotein E, microtubule-associated protein tau or catechol-O-methytransferase genotypes are associated with cognitive decline in Parkinson's disease.


We performed a prospective cohort study of 212 patients with a clinical diagnosis of Parkinson's disease. The primary outcome was change in Mattis Dementia Rating Scale version 2 score. Linear mixed-effects models and survival analysis were used to test for associations between genotypes and change in cognitive function over time.


The ε4 allele of apoliporotein E was associated with more rapid decline (loss of 2.9 (95% CI, 1.7–4.1) more points/year, p<0.001) in total score and an increased risk of a ≥10 pointdrop during the follow-up period (HR 2.8, 95% CI 1.4–5.4, p=0.003). Microtubule-associated protein tau haplotype and catechol-O-methytransferase genotype were associated with measures of memory and attention, respectively, over the entire followup period but not with the overall rate of cognitive decline.


These results confirm and extend previously described genetic associations with cognitive decline in Parkinson's disease and imply that individual genes may exert effects on specific cognitive domains or at different disease stages. Carrying at least one apolipoprotein E ε4 allele is associated with more rapid cognitive decline in Parkinson's disease, supporting the idea of a component of shared etiology between Parkinson's disease dementia and Alzheimer disease. Clinically, these results suggest genotyping can provide information about the risk of future cognitive decline for Parkinson's disease patients.

Keywords: Genetics, Parkinson's disease, Cognitive symptoms, Apolipoprotein E, Microtubule-associated protein tau


Cognitive impairment is common in Parkinson's disease (PD) and is associated with increased morbidity and mortality.(1) Estimates of dementia prevalence in PD vary depending on the population studied(2) but it increases with disease duration. Mild cognitive deficits may be indentified in approximately 20% of newly diagnosed patients,(3) and dementia occurs in up to 80% of patients over the course of the disease.(4, 5)

The rate and intensity with which cognitive problems develop vary substantially among individuals.(6) Clinical characteristics that are measured at time of diagnosis, including older age, sex, poor semantic fluency or inability to copy intersecting pentagons, have been associated with increased rates of cognitive decline and conversion to dementia.(7, 8) Biologic markers associated with cognitive decline, including genetic polymorphisms and analytes measurable in CSF or blood,(9, 10) may provide additional information on risk and help understand the biological basis for clinical heterogeneity.

Some genes previously associated with cognitive impairment in PD (e.g., α-synuclein(11), catechol-O-methyltransferase (COMT)(12)) implicate dopaminergic systems in the pathophysiology of cognitive impairment in PD. Other genes, such as, apoliporotein E (APOE) and microtubule-associated protein tau (MAPT), are of particular interest because of their known association with dementia in other neurodegenerative diseases, such as Alzheimer's disease (AD) and atypical Parkinsonian syndromes including progressive supranuclear palsy and corticobasal degeneration.(13, 14)

Studies investigating the association of individual genes with cognitive function in PD have yielded conflicting results, and have been limited by small samples or cross-sectional designs.(1518) Analysis of one small prospective cohort did not suggest a relationship between APOE genotype and cognitive decline in PD.(19) Only one cohort of more than 100 PD patients has been described with prospective assessment of cognitive abilities and examination of multiple genotypes. In this cohort of recently diagnosed PD patients, cognitive decline was strongly associated with MAPT haplotype but not APOE genotype.(8, 2022) Additionally, COMT genotype was associated with poor performance on frontally-based tasks, perhaps through an interaction with dopaminergic tone or medications, but not with a significantly increased risk of dementia.(12, 21, 23) In the present study, we sought to determine the association of APOE, MAPT and COMT genotype with cognitive performance in PD, measured by mean annual change in DRS-2 score and risk of experiencing at least a 10- point decline in DRS-2 score.



Patients 60 years of age or older having a diagnosis of PD based on UK Brain Bank criteria(24) and with a range of cognitive function were recruited to the University of Pennsylvania Udall Center of Excellence in Parkinson’s Disease Research. No subjects met criteria for dementia with Lewy bodies.(25) A total of 212 subjects who were assessed for the genotypes of interest and had at least one annual follow-up visit were included in this analysis.

Standard protocol approvals, registrations and consents

The study was approved by the University of Pennsylvania Institutional Review Board. Informed consent was obtained prior to any study procedure.


Clinical and neuropsychological assessments were administered by trained research staff. Demographic and general clinical information were collected in PD-DOC ( recommended format. Evaluations were completed between August 2006 and March 2011.


DNA was extracted from peripheral blood following the manufacturer’s protocols (Flexigene (Qiagen) or QuickGene DNA whole blood kit L (Autogen). Genotyping was performed using real-time allelic discrimination with Applied Biosystem (ABI) TaqMan probes. The following SNPs were genotyped with the corresponding ABI assay by design: MAPT (rs1052553, C_7563736_10), COMT p.V158M (rs4680, C_25746809_50), and APOE (rs7412, C_904973_10 and rs429358, C_3084793_20). Genotyping was performed on an ABI 7500 real-time instrument using standard conditions. Data were analyzed using ABI 7500 Software v2.0.1.

Neuropsychological assessment

Cognitive function was assessed with the Mattis Dementia Rating Scale (version 2, DRS-2).(26) The DRS-2 is a well-characterized measure of general cognitive ability. It gives a total score and sub-scores for specific cognitive domains including: memory, attention, initiation/perseveration, construction and conceptualization. A total of 144 points are possible, with higher scores indicating better cognitive function. The DRS-2 has been validated for use in PD.(27)

Motor examination

Clinical assessments of motor function, including Hoehn & Yahr stage (H&Y) (28) and Unified Parkinson's Disease Rating Scale Part III (UPDRS-III) (29) were performed by trained examiners. Motor assessments were conducted while patients were taking their normal schedule of dopaminergic and other medications.

Statistical Analysis

Descriptive statistics for demographic, clinical and neuropsychological variables were calculated. Based on prior reports of genotype-phenotype associations(12, 20, 30) the cohort was dichotomized based on the following genotypes : 1) APOE: ε4 carrier vs. not; 2) APOE: ε2 carrier vs. not ; (3) MAPT genotype: H1/H1 vs. other; 4) COMT: Met/Met vs. other. Between group differences in baseline demographic, clinical and neuropsychological variables were assessed using t-tests, chi-squared tests or Wilcoxon-Mann-Whitney tests as appropriate (Table 1). Linear mixed-effects models (31) were used to test for associations between different genotypes and changes in cognitive function over time as measured by the DRS-2 and its sub-scales. Linear mixed- effects models account for within-subject correlations over time and accommodate both variable length of follow-up for different subjects and variation in the interval between assessments. In our analysis, the intercept and regression coefficients for the follow-up time were treated as random effects such that each individual has a unique intercept and regression coefficient for the follow-up time. Population mean coefficients for the follow-up time were then obtained by averaging the subject-specific regression coefficients for follow-up time. The population mean regression coefficient for the follow-up time estimates the annual change in DRS-2 score over time and accounts for differences in baseline DRS-2 scores. The interaction term "time x genotype" represents the effect of a given genotype on DRS-2 change over time and can be interpreted as the between-group difference in annual DRS-2 decline.

Table 1
Baseline cohort demographic and disease characteristics as a function of genotype.

We used a Cox proportional hazards regression model to examine factors associated with the risk of a 10- point drop from baseline DRS-2 score. A ten- point drop was chosen because it represents an unequivocal and clinically significant change in DRS score. Using robust norms for a 70 year old, a change from a score of 145 to 135 is a drop from the 98th to approximately the 25th percentile and a change from a score of 135 to 125 is a drop from the 25th to the 1st percentile(32). Failure time was measured from baseline assessment until reaching 10- point drop in DRS-2 score. We used a step-wise model selection procedure to decide the final model from the following baseline covariates: sex, APOE4 genotype (ε4 carrier), MAPT haplotype, COMT genotype, age, education, baseline DRS-2 score, disease duration, H&Y and UPDRS-III. Cox regression analysis was performed using SAS software version 9.2 (SAS Institute Inc., Cary, North Carolina). All other analyses were carried out using PASW version 18.0 (SPSS, Inc. Chicago, IL). All statistical tests were two-sided. Statistical significance was set at the 0.05 level.


Of the subjects in this analysis, 65 (31%) had a total of two evaluations (i.e., 1 year of follow-up), 60 (28%) had three evaluations, 78 (37%) had four evaluations and 9 (4%) had five evaluations. The annualized rate of decline in DRS-2 score in the entire cohort was 1.3 ± 0.43 (SEM) points. Baseline demographic and disease characteristics of the cohort are described in Table 1.

The frequency of variants at each of the loci of interest is summarized in Figure 1.A comparison of demographic and disease characteristics between genotype groups is shown in Table 1. These characteristics were similar between groups with the exception of higher UPDRS and H&Y in APOEε4 carriers (Table 1).

Figure 1
Distribution of genotypes in the cohort

Association of genetic variants with cognitive status

There were no significant differences in baseline DRS-2 scores among genotype groups for APOE, MAPT or COMT (Table 1). Linear mixed-effects models were used to examine the association of genotype with cognitive decline, estimated by the magnitude of the "gene x time" interaction term. The presence of the APOEε4allele was associated with a significantly higher annual rate of decline in DRS-2 score compared with all other APOE genotypes (Table 2). Further, APOEε4 carrier status was associated with higher risk of a 10- point decline in DRS-2 score during the follow-up period adjusting for age, sex, education, disease severity and duration and baseline DRS-2 score (adjusted hazard ratio 2.8, 95% CI 1.4–5.4, p=0.003; Figure 2). A total of 37 subjects experienced a ≥10- point decline during followup. APOEε2, MAPT H1/H1genotype and COMT Met/Met genotypes were not associated with change in DRS-2 score over time (Table 2).

Figure 2
APOEε4 carriers are at increased risk for clinically significant decline in cognitive function in PD
Table 2
Relationship between genotype and annual change in DRS-2 score

The effect of APOE genotype on cognitive decline was not domain-specific, as the ε4 allele was associated with more rapid decline in DRS-2 subscales measuring initiation, construction, conceptualization and memory (Table 3). COMT Met/Met genotype was associated with higher attention subscale scores over the entire study period (0.38 ± .13 points, p=0.03) but not with changes in the attention score over time (p=0.17). MAPT H1/H1 genotype was associated with lower scores in the memory subscale over the entire study period (0.47 ± 0.23 points, p=0.04) but not with changes in the memory score over time (p=0.49). There were no other significant associations between MAPT or COMT and DRS-2 subscale scores (data not shown).

Table 3
Association between APOEε4 and annual change in DRS-2 domain subscores


We found that DRS-2 scores declined nearly 3 points per year faster among APOEε4 carriers with PD (Table 2). It seems likely that this disparity should be clinically significant, as, if ongoing, it might be expected to result in a 10-15 point differential over 5 years. The difference between baseline DRS-2 score in our cohort and a commonly used cutoff for dementia (<124)(33)was approximately 10 points. Indeed, APOEε4 carrier status was associated with a 2.8-fold increased risk of a ≥10 point decline in DRS-2 score during follow-up (Figure 2). These results indicate that the more rapid decline in mean DRS-2 scores among APOEε4 carriers was not driven by large changes in only a few individuals. Also, carrier status was associated with increased risk for earlier onset of clinically significant cognitive decline. More rapid cognitive decline among APOEε4 carriers was observed across multiple cognitive domains, arguing for a diffuse, rather than focal, degenerative process.

Notably, however, APOE ε4 was not associated with changes on the DRS-2 attention subscale (Table 3). We did observe an association between COMT genotype and performance on a measure of attention, as has been described by others, and is thought to reflect modulation of a fronto-striatal network.(12, 21, 23) However, COMT genotype did not influence overall rates of DRS-2 score decline consistent with the hypothesis that these deficits represent a distinct cognitive phenotype that does not herald dementia.(21) In contrast, MAPT H1/H1 genotype was associated with worse performance only on the memory subscale of the DRS-2, perhaps suggesting a temporal lobe-predominant effect, as seen in AD. The idea that individual genetic factors could influence distinct cognitive domains is intriguing and warrants further investigation.

Our findings add to a growing body of evidence on the association of APOE with cognitive decline in PD. The ε2 allele has been associated with increased incidence of PD(34) and a potentially protective effect in dementia,(13) but we did not observe an association between the ε2 allele and cognitive decline. In cross-sectional analyses, the APOEε4 allele has been associated with higher risk of dementia in several studies,(17, 35, 36)whereas others have failed to find an effect.(15, 16, 18, 22)

A meta analysis summarizing some of these studies and examining 458 pooled PD cases (163 with dementia and 295 without) supported an association between APOE ε4 and cognitive decline(30) A more recent study updating this analysis (1145 PD cases, 501 PDD cases) found an overrepresentation of ε4 carriers amongst PDD cases (OR 1.74, 95% CI 1.36-2.23) but raised concerns that small samples, heterogeneity of odds ratios and publication bias may have confounded the finding(22). Together, these reports support an association between APOE and PDD but suggest that the effect size may be small. Further, they highlight many of the difficulties in trying to study longitudinal change with cross-sectional studies. In one community-based longitudinal study of 107 newly-diagnosed PD patients from Cambridge, UK followed for an average of 5 years, APOE genotype was not associated with the rate of cognitive decline in PD.(22)

That some studies should fail to find any effect of APOE genotype on cognitive status is surprising given the influence of this gene on cognitive decline in Alzheimer's disease and in the general population.(37, 38) One possibility is that PD patients are somehow "protected" from the effects of APOE variation, though it is unclear through what mechanism this might occur. Another explanation is that these studies failed to detect an effect due to lack of power or other factors. For example, in the longitudinal cohort described above,(22) detection of an association between cognitive decline and APOE genotype may have been obscured by smaller sample size and the use of the Folstein Mini-Mental State Examination (MMSE), a relatively insensitive measure of cognitive function in PD,(39) as the primary outcome measure.

We did not find a significant association between MAPT haplotype and rates of cognitive decline. The MAPT H1variant has been associated with a higher risk of PD and cognitive decline, and a specific sub-haplotype (H1p) has recently been implicated. (20, 40) However, several other studies failed to demonstrate a relationship between MAPT variants and dementia in PD.(16, 41) In the same longitudinal cohort from Cambridge, UK described above,(22) there was a faster rate of decline in MMSE scores among indivudials with the MAPT H1 variant.(20) All subjects developing dementia during the initial three year follow-up (11/109) carried the H1/H1 genotype,(20) and the increased risk persisted after 5 years.(21)

One key distinction between the present study and that of the Cambridge cohort is that we enrolled subjects primarily in the middle of the course of PD, while the other cohort was enrolled near the time of diagnosis. One explanation for the discrepancy in our findings is that different genetic mechanisms may subserve early versus late-onset cognitive decline in PD. These prior studies demonstrated an association between MAPT haplotype and cognitive decline within the first 5 years of diagnosis. Conversely, we found an association between APOE genotype and cognitive decline that occurs later in the course of PD.

Our findings cannot definitively establish whether the association we observed between APOE and cognitive decline is specific to PD or simply the previously described effect of APOE genotype on cognitive function that may be seen in otherwise healthy older individuals.(38) However, several lines of evidence support overlap in the pathology of PDD and AD. Alzheimer pathology is often observed in post-mortem PDD brains and abnormalities in aβ and Tau protein are possible biomarkers of cognitive change in PD.(10, 42) Disruption of APOE ameliorates aβ accumulation and neurodegeneration in a mouse model of PD,(43) thus this overlap may reflect interaction of ApoE with distinct neural substrates to produce the specific pattern of changes seen in PDD rather than superimposed, unrelated accumulation of AD pathology. In this study, we did not find that APOEε4 carriers had disproportionate memory impairments compared to other domains as would be expected if the effect of APOE genotype was simply due to co-existing AD pathology. Combined with our report of depressed aβ but not elevated CSF tau in PD patients,(10) this finding suggests that the accelerated cognitive decline observed in APOE carriers is not simply due to an increased risk of coexisting AD, but rather a disease-specific effect of APOE gene status on cognition in PD.

The prospective design and size of the longitudinal cohort are strengths of the present study. However, these results should be interpreted in the context of several limitations. Education level in this cohort was high (mean 16 years), but observed DRS-2 scores were consistent with those in previously reported PD cohorts and education was not a significant covariate in any of our mixed-effects models or survival analysis. The majority of patients were followed for a relatively short period of time, and the number of subjects with more than 2 years of follow-up was modest compared with the size of the entire cohort. However, use of mixed-effects models accounts for variability in length of follow-up. The cohort was not incident and disease duration at enrollment varied widely, complicating an unbiased assessment of the time to onset of cognitive decline; however, adjustment for disease duration and other clinical characteristics in mixed effects models did not affect the associations observed. It should be noted that while mixed effects models account, in part, for variations in length of followup and disease duration, associations between genetic factors and longitudinal change or effects at a particular disease stage could have been underestimated.

Aging is a risk factor for countless human diseases, but appears to play a particularly important role in cognitive decline seen in neurodegenerative disorders and the general population. The previously described strong association between MAPT and cognitive decline in the Cambridge cohort was highly age-dependent(20, 21) , although we did not observe significant effects for gene*age interaction terms in our mixed effects models (not shown). Thus, the importance of aging in PD-associated cognitive decline may depend on particular genetic factors. Ultimately, cognitive changes over time in any given PD patient may reflect multiple, potentially overlapping, pathologic processes superimposed onto "normal" aging or specific gene-age interactions Although the present study was not powered to do so, investigating potential gene-gene interactions and their effect on cognitive status in PD may be of particular interest. As the effect size for any one factor may be relatively modest, future studies of larger prospective cohorts examining multiple candidate loci, perhaps in combination with other biologic markers, may be necessary to fully elucidate the predictive value and etiologic roles of these genes in neurodegenerative dementias including PDD.


We thank our colleagues in the Penn Udall Center and the Parkinson’s Disease and Movement Disorders Center for their contributions to the studies here which were supported by a Morris K. Udall Parkinson’s Disease Research Center of Excellence grant from NINDS (NS-053488). We thank Xiaoyan Han, M.S. for her assistance in the Cox regression analysis. We thank our patients and their families without whom this research would not be possible.


Disclosure: There are no relevant financial disclosures or conflicts of interest.


Morley: 2ABC, 3A. Xie: 2ABC,3B. Hurtig: 1ABC, 3B. Stern: 1C, 3B. Colcher: 1C, 3B. Horn: 1C, 3B. Dahodwala: 1C, 3B. Duda: 1C, 3B. Weintraub: 1C, 3B Chen-Plotkin: 1C, 3B. Van Deerlin: 1C, 3B. Falcone: 1C, 3B. Siderowf: 1ABC, 2AC, 3B.


This study was funded by a Morris K. Udall Parkinson’s Disease Research Center of Excellence grant from NINDS (NS-053488) and by SAP4100027296, a health research grant awarded by the Department of Health of the Commonwealth of Pennsylvania from the Tobacco Master Settlement Agreement under Act 2001-77. James Morley has received compensation for articles written in the PD Monitor and Commentary, a publication supported by an educational grant from Teva Neuroscience Sharon Xie reports no disclosures. Howard Hurtig is the Frank and Gwladys Elliott Professor of Neurology. He is funded by a Morris K. Udall Parkinson’s Disease Research Center of Excellence grant from NINDS (NS-053488). He owns stock in Teva Pharmaceuticals and received a speaking honorarium from Teva Neuroscience. Matthew Stern has received funds for consulting with Teva, Nupathe, Adamas, Cevitas, Ipsen and Merz, Inc. Amy Colcher has severed as a consultant for Teva Pharmaceuticals and Lundbeck Pharmaceuticals. Stacy Horn reports no disclosures. Nabilia Dahodwala receives research funding from the National Institutes of Health (K23 AG 034236) and the University of Pennsylvania. John Duda serves on scientific advisory boards for the Lewy Body Dementia Association and the Lewy Body Society; received compensation for interviews for articles in the PD Monitor and Commentary, a publication supported by an educational grant from Teva Neuroscience; receives honoraria for lectures or educational activities not funded by industry; and receives research support from the Department of Veterans Affairs [Biomedical Laboratory Research and Development Service Merit Award (PI), Cooperative Studies Program 468 (Site PI)], the NIH [RO1 NS41265-01 (Coinvestigator), RO1 NS44266 (Coinvestigator)], the Michael J. Fox Foundation, the Pennsylvania State Department of Health and the Samueli Foundation. Daniel Weintraub has received research support from Boehringer Ingelheim, National Institutes of Health, and Penn Center for Excellence in Research on Neurodegenerative Diseases (CERND). He has received consulting fees or honoraria from: Acadia Pharmaceuticals, Boehringer Ingelheim, General Electric, Merck Serono, Novartis Pharmaceuticals, Pfizer, Sanofi Aventis, Johnson and Johnson, and Solvay. Alice Chen-Plotkin is supported by a Burroughs Wellcome Fund Career Award for Medical Scientists and NIH K08 AG033101. Vivianna Van Deerlin reports no disclosures. Dana Falcone reports no disclosures. Andrew Siderowf is supported by a Morris K. Udall Parkinson’s Disease Research Center of Excellence grant from NINDS (NS-053488), and has been supported by SAP4100027296, a health research grant awarded by the Department of Health of the Commonwealth of Pennsylvania from the Tobacco Master Settlement Agreement under Act 2001-77. He has received consulting fees from Teva Neuroscience, Supernus Pharmaceuticals, Schering-Plough and Merck Serono. He has received speaking honorarium from Teva Neuroscience.


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