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Logo of neurologyNeurologyAmerican Academy of Neurology
Neurology. 2010 September 21; 75(12): 1055–1061.
PMCID: PMC2942062

CSF amyloid β 1-42 predicts cognitive decline in Parkinson disease(e Pub ahead of print)

A. Siderowf, MD, MSCE, S.X. Xie, PhD, H. Hurtig, MD, D. Weintraub, MD, J. Duda, MD, A. Chen-Plotkin, MD, L.M. Shaw, PhD, V. Van Deerlin, MD, PhD, J.Q. Trojanowski, MD, PhD, and C. Clark, MD



Cognitive decline associated with Parkinson disease (PD) is common and highly disabling. Biomarkers that help identify patients at risk for cognitive decline would be useful additions to the clinical management of the disease.


A total of 45 patients with PD were enrolled in this prospective cohort study and had at least 1 yearly longitudinal follow-up evaluation. CSF was collected at baseline and cognition was assessed at baseline and follow-up visits using the Mattis Dementia Rating Scale (DRS-2). CSF was tested for amyloid β 1-42 (Aβ1-42), p-tau181p, and total tau levels using the Luminex xMAP platform. Mixed linear models were used to test for associations between baseline CSF biomarker levels and change in cognition over time.


Lower baseline CSF Aβ1-42 was associated with more rapid cognitive decline. Subjects with CSF Aβ1-42 levels ≤192 pg/mL declined an average of 5.85 (95% confidence interval 2.11–9.58, p = 0.002) points per year more rapidly on the DRS-2 than subjects above that cutoff, after adjustment for age, disease duration, and baseline cognitive status. CSF total tau and p-tau181p levels were not significantly associated with cognitive decline.


Reduced CSF Aβ1-42 was an independent predictor of cognitive decline in patients with PD. This observation is consistent with previous research showing that Alzheimer disease pathology contributes to cognitive impairment in PD. This biomarker may provide clinically useful prognostic information, particularly if combined with other risk factors for cognitive impairment in PD.


= Alzheimer disease;
= Alzheimer's Disease Neuroimaging Initiative;
= confidence interval;
= dementia with Lewy bodies;
= Dementia Rating Scale (version 2);
= Hoehn & Yahr;
= Parkinson disease;
= Parkinson disease dementia.

Cognitive impairment is common in Parkinson disease (PD), with dementia occurring in up to 80% of patients over the course of their illness.1 When dementia is present, it worsens disability,2 results in greater caregiver burden,3 and increases mortality.4 Clinical features including older age, male sex, lack of tremor, greater postural instability, and subtle impairments on cognitive tests are risk factors for more severe cognitive impairment and progression to PD dementia (PDD).5,6

In addition to these clinical features, biomarkers could potentially improve the ability to predict risk for cognitive impairment and PDD. Among currently available candidate biomarkers, CSF measures of Alzheimer disease (AD) pathology including Aβ1-42, tau, and p-tau181p have attractive properties including validated assessment methods7 and relevance to putative components of the underlying pathology in PDD and dementia with Lewy bodies (DLB).8 Both CSF Aβ1-42 and tau levels have been associated with impaired cognition in cross-sectional studies of patients with PD and DLB.9,10 In the present longitudinal study, we tested whether CSF Aβ1-42, tau, and p-tau181p could predict risk of subsequent cognitive decline in patients with PD. We hypothesized that subjects with biomarker profiles similar to those seen in patients with AD would show the greatest cognitive decline.



Patients aged 60 or older with a diagnosis of PD based on British Brain Bank criteria11 and a range of cognitive function were recruited to the University of Pennsylvania Udall Center for this study from the Parkinson's Disease and Movement Disorders Center at University of Pennsylvania. No subjects met criteria for DLB.12 A total of 45 subjects contributed spinal fluid samples and had at least one yearly follow-up visit, and were therefore eligible for 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 administration of any study procedure.


The clinical and neuropsychological evaluation was administered by trained research staff. Demographic and general clinical information was collected in PD-DOC recommended format ( Evaluations were conducted between August 2006 and December 2009.

Neuropsychological assessment.

Cognitive status was assessed using the Mattis Dementia Rating Scale (version 2) (DRS-2).13 The DRS-2 is a detailed measure of general cognitive ability. It contains subscales that measure specific cognitive domains: memory, attention, initiation/perseveration, construction, and conceptualization. It has been validated in patients with PD,14 and a cutoff score of ≤123 has been shown to accurately identify patients with PDD.15 The same study reported a mean DRS score of 133 for patients with PD without dementia.

Motor examination.

Clinical examinations, including Hoehn & Yahr (H&Y) staging,16 were conducted by the patients' treating doctors who are movement disorders specialists. Motor examinations were conducted while patients were receiving their regularly scheduled dopaminergic medications.

CSF analysis.

CSF samples were obtained by lumbar puncture using a 20- or 24-gauge spinal needle as described in the Alzheimer's Disease Neuroimaging Initiative (ADNI) procedures manual ( CSF was divided into aliquots (0.5 mL) and stored in bar code–labeled polypropylene vials at −80°C. Aβ1-421-42, tau, and p-tau181p were measured using the multiplex xMAP Luminex platform (Luminex Corp, Austin, TX) with Innogenetics (INNO-BIA AlzBio3; Ghent, Belgium; for research use only reagents) immunoassay kit–based reagents. Full details for this combination of immunoassay reagents and analytical platform are provided elsewhere.17 Reliability studies ( show that the day-to-day reproducibility for these 3 biomarkers varies by less than 10%.

APOE genotyping.

DNA was extracted from EDTA blood samples using commercial reagents (FlexiGene, Oiagen, Valencia, CA). DNA was available for 43 of the 45 participants. Two single nucleotide polymorphisms (rs7412 and rs429358) in APOE were genotyped using allelic discrimination assays with TaqMan reagents (Applied Biosystems, Foster City, CA) on an ABI7500. The APOE genotypes (ε2, ε3, and ε4) were assigned by incorporating the genotyping results from both single nucleotide polymorphisms into an algorithm.


Descriptive statistics for clinical and CSF variables (Aβ1-42, tau, p-tau181p, and their ratios: tau/Aβ1-42 and p-tau181p/Aβ1-42) were calculated. Linear mixed-effects models were used to test for associations between baseline CSF biomarkers and cognitive decline as measured by the DRS-2.18 A linear mixed-effect model accounts for within-person correlations over time, and allows for variable length of follow-up between subjects. These models can also accommodate varying time intervals between assessments. Each subject in this mixed-effect model can be thought of as having his or her own linear regression model, and the population parameters can be obtained by averaging across the individual regression coefficients. In our implementation, the intercept and the regression coefficients for the follow-up time were treated as random effects such that each subject has a unique intercept and regression coefficient for the follow-up time. The population mean coefficients for the follow-up time were obtained by averaging across the subject-specific regression coefficients for the follow-up time. This population mean coefficient estimated the average annual change for the DRS-2 over time, and accounts for differences in baseline DRS-2 scores. The interaction term time × CSF biomarker represents the effect of the baseline biomarker on change in DRS-2 score over time. It can be interpreted as the annualized change in DRS-2 score for each one unit change in a given biomarker. In addition to considering Aβ1-42, tau, and p-tau181p as continuous measures, we also examined the effect of being at or below the Aβ1-42 cutoff of 192 pg/mL. This level has been associated with the greatest diagnostic accuracy in separating patients with AD from age-matched controls.7 In this case, the time × Aβ1-42 group interaction can be interpreted as the between-group difference in annualized rate of DRS-2 decline. Analogous tests were performed for subscales of the DRS-2.

Potential confounding variables including age, gender, education, H&Y stage, and disease duration were tested in bivariable analysis. Only age, H&Y stage, and disease duration were associated with DRS-2 score below the p < 0.1 cutoff, and were included in subsequent models. With the exception of APOE genotype, complete data were available for 45 subjects. APOE status was available for 42 of 45 subjects, and the association between APOE ε4 carrier status and cognitive decline was tested in this subset of subjects.

All analyses were conducted at a 2-sided α = 0.05 significance level, without adjustment for multiple comparisons. Analyses were carried out using Stata version 10 (College Station, TX).


Subject characteristics and cognitive status.

At the time of this analysis, 45 subjects had at least 1 yearly follow-up clinical evaluation, 20 had 2 follow-up evaluations, and 3 were evaluated 3 years after baseline. None have been lost to follow-up or withdrawn consent. For the entire cohort, the annualized rate of decline in DRS-2 was 3.4 points (±0.96). Baseline demographic characteristics are shown in table 1.

Table thumbnail
Table 1 Baseline characteristics of 45 patients with Parkinson disease

Association between CSF biomarkers and baseline cognitive status.

We found no association between CSF biomarkers and baseline cognitive status (table 2). The result was the same with or without adjustment for covariates. At baseline, 6 subjects were below the DRS-2 cutoff of 123 that is associated with a diagnosis of dementia.15 There were no differences in biomarker values for these subjects compared to those with DRS-2 scores >123. For example, mean CSF Aβ1-42 was 226 pg/mL (SD 77) in subjects with DRS-2 scores >123 and 210 pg/mL (SD 60) in subjects ≤123 (p = 0.63). However, the small number of subjects with low baseline DRS-2 scores limits our ability to make this comparison.

Table thumbnail
Table 2 CSF biomarkers as predictors of deterioration on the DRS-2

Association between CSF biomarkers and longitudinal change in cognition.

Reduced CSF Aβ1-42 was strongly associated with decline in cognitive function over time (table 2). Results were similar in unadjusted analysis (β = 0.041; 95% confidence interval [CI] 0.015 to 0.066), and with adjustment for age, disease duration, and baseline H&Y stage (β = 0.040; 95% CI 0.015 to 0.066). There was no association of either total tau or p-tau181p and greater cognitive decline. In addition, there was no association between tau/Aβ1-42 and p-tau181p/Aβ1-42 ratios and change in cognition. This was true in spite of the strong relationship between Aβ1-42 and cognitive decline. Adding tau or p-tau181p in a combined metric actually diminished the effect of Aβ1-42 alone.

A CSF Aβ1-42 level of ≤192 pg/mL has been suggested as a useful diagnostic cutoff for AD.7 We tested whether subjects in our cohort with CSF Aβ1-42 below this level were at greater risk for cognitive decline, and found that those with Aβ1-42 levels ≤192 had an annualized decline in DRS score that was 6.1 points greater (95% CI 2.33 to 9.79) than those with Aβ1-42 levels above 192 pg/mL. This association was quite similar after adjustment for age, disease duration, and baseline H&Y stage (5.8 points greater; 95% CI 2.11 to 9.58). After 2 years, the mean adjusted DRS-2 score for subjects with low baseline Aβ1-42 levels had fallen below the published cutoff for dementia of 123 on the DRS-2, while the mean adjusted score for subjects with Aβ1-42 levels above 192 remained above 130 (figure).

figure znl0361080390001
Figure 1 Change over time in mean Dementia Rating Scale (version 2) (DRS-2) total score

Associations with APOE status.

Fifteen subjects carried at least one APOE ε4 allele (one subject was homozygous). CSF Aβ1-42 levels were substantially lower in these subjects (182 pg/mL vs 251 pg/mL; p = 0.004). CSF tau and p-tau181p levels were not significantly different for APOE ε4 allele carriers compared to noncarriers (tau: 46 vs 55; p = 0.35; p-tau181p: 18 vs 19; p = 0.836). Without adjustment for CSF Aβ1-42, having at least one APOE ε4 copy was associated with an increase in the rate of cognitive decline compared to noncarriers that approached significance (difference = 3.96 DRS-2 points/year, 95% CI −0.39 to 8.32; p = 0.075). However, the association with of APOE ε4 allele status was no longer present after adjustment for CSF Aβ1-42 level (difference = 1.29 points/year, 95% CI −3.15 to 5.73; p = 0.569). No other APOE genotypes were associated with cognitive decline (data not shown).

Association between CSF biomarkers and change in individual cognitive domains.

Low CSF Aβ1-42 was significantly (p < 0.05) associated with declines in multiple subscales of the DRS-2. The largest effect size was seen for the attention subscale (β = 0.011, SE = 0.0034). There were also significant associations with change in conceptualization (β = 0.0078, SE = 0.0033) and memory (β = 0.0086, SE = 0.0042). The association with the initiation/perseveration subscale approached significance (β = 0.011, SE = 0.0064, p = 0.06). There was no significant association with the construction subscale. These findings suggest an association with global cognitive decline, rather than an association limited to one cognitive domain.


Low baseline CSF Aβ1-42 levels were a strong predictor of subsequent cognitive decline in this cohort of patients with PD. Neither tau nor p-tau181p was associated with cognitive decline, and ratios of p-tau181p and tau to Aβ1-42 were no better predictors than Aβ1-42 alone. The effects sizes we observed are likely to be clinically meaningful. Based on our data, a patient with CSF Aβ1-42 below the diagnostic cutoff of 192 pg/mL would be predicted to progress from essentially normal cognition to a level consistent with PDD within a 2-year period of follow-up. Decline was observed across multiple cognitive domains, suggesting an anatomically generalized, rather than focal, degeneration.

We found no association between biomarker levels and baseline cognitive status, even after adjustment for disease duration. This may be due to a number of factors including the small number of patients with PD with a DRS-2 score in the dementia range (i.e., ≤123) or biases inherent in cross-sectional analyses. Our results are also consistent, however, with the hypothesis that biomarker abnormalities precede clinical cognitive decline.

Similar cross-sectional studies have not found a relationship between CSF Aβ1-42 levels or plasma Aβ levels and cognitive status in patients with AD.19,20 However, recent studies have documented that reductions in CSF Aβ1-42 are associated with risk of subsequent cognitive decline. In the ADNI cohort, lower CSF Aβ1-42 levels (and elevated tau) were associated with increased risk of conversion from mild cognitive impairment to AD.7 In another AD cohort, lower CSF Aβ1-42 and elevated p-tau181p (to a greater extent than total tau) predicted more rapid cognitive decline.21 Finally, a recent study showed that alterations in various Aβ peptides in plasma were associated with risk of subsequent dementia.22

Lower levels of CSF amyloid-β peptides, specifically Aβ1-42, reflect underlying amyloid pathology.23,24 Some have hypothesized that in AD, lower Aβ1-42 levels in the spinal fluid may be related to sequestration of the peptide from CSF into amyloid plaques.25 In Lewy body disorders, the picture is more complicated. Decreased levels of Aβ1-42 have been demonstrated in CSF from patients with DLB compared to normal controls.9,26 In patients with PDD, modest reductions in CSF Aβ1-42 have been shown compared to normal controls,27,28 and in PD without dementia, Aβ1-42 levels are not consistently reduced.9 Increased CSF levels of total tau and p-tau181p have been associated with impaired cognitive performance in patients with PD and PDD.10 These differences in CSF Aβ1-42 across the spectrum of Lewy body disorders may reflect a gradient in the relative contribution of amyloid pathology to DLB, PDD, and PD without dementia, respectively. Such a hypothesis is consistent with neuropathologic data showing that amyloid plaque pathology is common in DLB and present to a lesser degree in PDD.29 If lower CSF Aβ1-42 levels reflect greater amyloid plaque burden in patients with PD at risk for cognitive decline, then this in turn argues for an important role for amyloid pathology in the development of dementia in PD.

The presence of at least one APOE ε4 allele is an established risk factor for amyloid aggregation and AD.30 A meta-analysis of the published studies on the relationship between APOE genotype and risk of dementia in PD31 found modestly increased risk associated with the ε4 allele, and no definite associations with other alleles. We found a modest association that approached significance between APOE ε4 carrier status and rate of cognitive decline, with carriers of at least one copy of the ε4 allele having more rapid cognitive decline. However, this association was substantially smaller than the association with CSF Aβ1-42, and was no longer significant after adjustment for CSF Aβ1-42 level. Moreover, consistent with previous studies,32 baseline CSF Aβ1-42 was significantly lower in subjects with at least one APOE ε4 allele. These findings argue that the APOE4 genotype and Aβ1-42 may function in the same pathway, but that CSF Aβ1-42 is more directly related, and more predictive of cognitive decline in PD than APOE genotype. Interestingly, there is evidence that reduced CSF Aβ1-42 may confer greater risk for conversion from mild cognitive impairment to AD in APOE ε4 noncarriers.33 Studies with larger sample size and longitudinal design may help clarify the relationship between APOE ε4 status and other genetic traits such as tau haplotype34 and dementia risk in PD.

Several limitations of our study should be acknowledged. First, we studied a relatively small sample of patients with PD and for a relatively brief period of time. As a result, we are not able to perform subgroup analyses, such as examining the association between CSF Aβ1-42 and cognitive decline in men vs women or in recently diagnosed vs established cases of PD. We were able to detect an association of CSF Aβ1-42 level with cognitive decline because the DRS-2 is a relatively precise, continuous measure of cognitive status, and because of the longitudinal design of our study. Our findings should be replicated in larger groups of patients, and in longer studies that examine the risk of conversion to a clinical diagnosis of PDD. Second, our results do not address whether the association between reduced Aβ1-42 and cognitive decline is specific to PD. Similar declines in cognition have been observed in apparently healthy populations.35 Our results may reflect the effects of the primary underlying pathologic process in PDD, or simply coexisting AD pathology that modifies CSF Aβ1-42 levels and also may, in part, underlie cognitive impairment in PD. One means to address this issue would be to study additional CSF biomarkers. Recently, specific subtypes of amyloid peptides such as Aβ1–40 have been shown to differentiate PDD from DLB and may be a more specific marker of cortical Lewy body pathology.9 In addition, assays for α-synuclein pathology are under development, and may be useful in determining prognosis in patients with PD.36

These limitations are opportunities for future research. Nonetheless, our study remains significant in that it demonstrates the ability of a CSF biomarker to provide prognostic information for patients with PD on the risk of cognitive decline. In the future, biological data such as CSF Aβ1-42 level could be combined with clinical information that has been associated with risk of PDD to provide better predictive accuracy than either type of information alone.


The authors thank their colleagues in the University of Pennsylvania Udall Center and the Parkinson's Disease and Movement Disorders Center for their contributions to the studies reported here. J.Q.T. is the William Maul Measy-Truman G. Schnabel Jr. MD Professor of Geriatric Medicine and Gerontology. The authors also thank their patients and their families without whom this research would not be possible.


Dr. Siderowf serves on a scientific advisory board for and has received speaker honoraria from Teva Pharmaceutical Industries Ltd.; serves/has served as a consultant to Supernus Pharmaceuticals, Inc., Teva Pharmaceutical Industries Ltd., Merck Serono, and Schering-Plough Corp.; receives research support from the NIH (NINDS U10 NS0444451 [site PI], NINDS P50 NS053488 [Co-I], NINDS R43NS0636071 [Co-I], and NINDS R01NS065087 [Co-I]), the US Department of Defense, and the Department of Health, Commonwealth of Pennsylvania; and has served as a consultant on manganese litigation. Dr. Xie receives research support from the NIH/NINDS (NS053488 [coinvestigator and core director]). Dr. Hurtig served on a grant review panel for the Michael J. Fox Foundation for Parkinson's Research; serves on the editorial board of Parkinsonism and Related Disorders; serves as Movement Disorders Section Editor for UpToDate; has received speaker honoraria from Teva Pharmaceutical Industries Ltd.; receives research support from Teva Pharmaceutical Industries Ltd., Boehringer Ingelheim, Bayer Schering Pharma, Kyowa Hakko Kirin Pharma, Inc., PRA International, Novartis, GlaxoSmithKline, Avid Radiopharmaceuticals, Inc., St Jude Medical, Amarin Corporation, Prestwick Pharmaceutical, Inc., HP Therapeutics Foundation, Inc., Cephalon, Inc., NIH (NINDS P50 NS053488-01 [core leader and PI] and NINDS U10 NS044451-023 [site PI]); and holds stock in Teva Pharmaceutical Industries Ltd. Dr. Weintraub has served on a scientific advisory board for Boehringer Ingelheim; serves on the editorial board of Movement Disorders; has received honoraria from Boehringer Ingelheim, ACADIA Pharmaceuticals Inc., GE Healthcare, Novartis, Osmotica Pharmaceutical Corp., BrainCells Inc., Merck Serono, Sanofi-Aventis, Johnson & Johnson, Solvay Pharmaceuticals, Inc., and Pfizer Inc.; and receives research support from Boehringer Ingelheim, the NIH (K23 MH067894 [PI]), the Penn Center for Excellence in Research on Neurodegenerative Diseases (CERND), and the Michael J. Fox Foundation for Parkinson's Research. Dr. Duda served on a grant review panel for the Michael J. Fox Foundation for Parkinson's Research; serves/has served on a scientific advisory boards for Boehringer Ingelheim, the Lewy Body Dementia Association, and the Lewy Body Society; has received honoraria for interviews for articles in the PD Monitor and Commentary, a publication supported by an educational grant from Teva Pharmaceutical Industries Ltd.; 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 [Co-I], RO1 NS44266 [Co-I]), the Michael J. Fox Foundation, the Department of Health, Commonwealth of Pennsylvania, and the Samueli Foundation; and holds stock in C.R. Bard, Inc., Celgene, Clarient, and Johnson & Johnson. Dr. Chen-Plotkin receives research support from the Burroughs Wellcome Fund and the NIH (K08 AG033101 [PI]). Dr. Shaw has served on a scientific advisory board for Bristol-Myers Squibb; has received funding for travel and speaker honoraria from Pfizer Inc.; serves on the editorial board of Therapeutic Drug Monitoring; may potentially receive revenue for patent pending re: O-methylated rapamycin derivatives for alleviation and inhibition of lymphoproliferative disorders, licensed by the University of Pennsylvania to Novartis; receives royalties from publication of Applied Pharmacokinetics and Pharmacodynamics: Principles of Therapeutic Drug Monitoring (Wolters Kluwer/Lippincott Williams & Wilkins, 2005); receives research support from the NIH (AG024904 [Co-PI Biomarker Core Laboratory] and 1RC 2AG-036535 (ARRA) [PI Biomarker Core Laboratory]); and receives board of directors' compensation and holds stock options in Saladax Biomedical. Dr. Van Deerlin serves on the editorial board of Molecular Diagnosis and Therapy; has a patent pending re: Compositions and methods for the treatment of frontotemporal lobar degeneration with TDP-43 inclusions; receives royalties from the publication of Molecular Pathology in Clinical Practice (Springer, 2007); and receives research support from the NIH (NS053488 [Neuropathology and Genetics Core, Core Co-Leader] and AG010124 [Neuropathology Core, Co-I]). Dr. Trojanowski has received funding for travel and honoraria from Takeda Pharmaceutical Company Ltd.; has received speaker honoraria from Pfizer Inc.; serves as an Associate Editor of Alzheimer's & Dementia; may accrue revenue on patents re: Modified avidin-biotin technique, Method of stabilizing microtubules to treat Alzheimer's disease, Method of detecting abnormally phosphorylated tau, Method of screening for Alzheimer's disease or disease associated with the accumulation of paired helical filaments, Compositions and methods for producing and using homogeneous neuronal cell transplants, Rat comprising straight filaments in its brain, Compositions and methods for producing and using homogeneous neuronal cell transplants to treat neurodegenerative disorders and brain and spinal cord injuries, Diagnostic methods for Alzheimer's disease by detection of multiple MRNAs, Methods and compositions for determining lipid peroxidation levels in oxidant stress syndromes and diseases, Compositions and methods for producing and using homogenous neuronal cell transplants, Method of identifying, diagnosing and treating alpha-synuclein positive neurodegenerative disorders, Mutation-specific functional impairments in distinct tau isoforms of hereditary frontotemporal dementia and parkinsonism linked to chromosome-17: genotype predicts phenotype, Microtubule stabilizing therapies for neurodegenerative disorders, and Treatment of Alzheimer's and related diseases with an antibody; and receives research support from the NIH (NIA P01 AG 09215-20 [PI], NIA P30 AG 10124-18 [PI], NIA PO1 AG 17586-10 [Project 4 Leader], NIA 1PO1 AG-19724-07 [Core C Leader], NIA 1 U01 AG 024904-05 [Co-PI Biomarker Core Laboratory], NINDS P50 NS053488-02 [PI], NIA UO1 AG029213-01 (Co-I); RC2NS069368 (PI), RC1AG035427 (PI), and NIA P30AG036468 [PI]) and the Marian S. Ware Alzheimer Program. Dr. Clark serves as Medical Director of and holds stock options in Avid Radiopharmaceuticals, Inc.; has served on scientific advisory boards for Elan Corporation and Wyeth; and receives research support from the Department of Health, Commonwealth of Pennsylvania.


Address correspondence and reprint requests to Dr. Andrew Siderowf, Department of Neurology, 330 South 9th Street, Second Floor, Philadelphia, PA 19107 ude.nnepu.shpu@fworedis.werdna.

Editorial, page 1036.

e-Pub ahead of print on August 18, 2010, at

Study funding: Supported 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.

Disclosure: Author disclosures are provided at the end of the article.

Received January 5, 2010. Accepted in final form April 27, 2010.


1. Aarsland D, Andersen K, Larsen JP, Lolk A, Kragh-Sorensen P. Prevalence and characteristics of dementia in Parkinson disease: an 8-year prospective study. Arch Neurol 2003;60:387–392. [PubMed]
2. Cahn DA, Sullivan EV, Shear PK, Pfefferbaum A, Heit G, Silverberg G. Differential contributions of cognitive and motor component processes to physical and instrumental activities of daily living in Parkinson's disease. Arch Clin Neuropsychol 1998;13:575–583. [PubMed]
3. Aarsland D, Larsen JP, Karlsen K, Lim NG, Tandberg E. Mental symptoms in Parkinson's disease are important contributors to caregiver distress. Int J Geriatr Psychiatry 1999;14:866–874. [PubMed]
4. Buter TC, van den Hout A, Matthews FE, Larsen JP, Brayne C, Aarsland D. Dementia and survival in Parkinson disease: a 12-year population study. Neurology 2008;70:1017–1022. [PubMed]
5. Stern Y, Marder K, Tang MX, Mayeux R. Antecedent clinical features associated with dementia in Parkinson's disease. Neurology 1993;43:1690–1692. [PubMed]
6. Uc EY, McDermott MP, Marder KS, et al. Incidence of and risk factors for cognitive impairment in an early Parkinson disease clinical trial cohort. Neurology 2009;73:1469–1477. [PMC free article] [PubMed]
7. Shaw LM, Vanderstichele H, Knapik-Czajka M, et al. Cerebrospinal fluid biomarker signature in Alzheimer's disease neuroimaging initiative subjects. Ann Neurol 2009;65:403–413. [PMC free article] [PubMed]
8. Emre M, Aarsland D, Brown R, Burn D, et al. Clinical diagnostic criteria for dementia associated with Parkinson's disease. Mov Disord 2007;22:1689–1707. [PubMed]
9. Bibl M, Mollenhauer B, Esselmann H, et al. CSF amyloid-beta-peptides in Alzheimer's disease, dementia with Lewy bodies and Parkinson's disease dementia. Brain 2006;129:1177–1187. [PubMed]
10. Compta Y, Marti MJ, Ibarretxe-Bilbao N, et al. Cerebrospinal tau, phospho-tau, and beta-amyloid and neuropsychological functions in Parkinson's disease. Mov Disord 2009;24:2203–2210. [PubMed]
11. Hughes AJ, Daniel SE, Lees AJ. The clinical features of Parkinson's disease in 100 histologically proven cases. Adv Neurol 1993;60:595–599. [PubMed]
12. McKeith IG, Dickson DW, Lowe J, et al. Diagnosis and management of dementia with Lewy bodies: third report of the DLB Consortium. Neurology 2005;65:1863–1872. [PubMed]
13. Mattis S. Dementia Rating Scale. Odessa, FL: Psychological Assessment Resources; 1988.
14. Brown GG, Rahill AA, Gorell JM, et al. Validity of the Dementia Rating Scale in assessing cognitive function in Parkinson's disease. J Geriatr Psychiatry Neurol 1999;12:180–188. [PubMed]
15. Llebaria G, Pagonabarraga J, Kulisevsky J, et al. Cut-off score of the Mattis Dementia Rating Scale for screening dementia in Parkinson's disease. Mov Disord 2009;23:1546–1550. [PubMed]
16. Hoehn MM, Yahr MD. Parkinsonism: onset, progression and mortality. Neurology 1967;17:427–442. [PubMed]
17. Olsson A, Vanderstichele H, Andreasen N, et al. Simultaneous measurement of β-amyloid(1-42), total tau, and phosphorylated tau (Thr181) in cerebrospinal fluid by the xMAP technology. Clin Chem 2005;51:336–345. [PubMed]
18. Laird NM, Ware JH. Random-effects models for longitudinal data. Biometrics 1982;38:963–974. [PubMed]
19. Galasko D, Chang L, Motter R, et al. High cerebrospinal fluid tau and low amyloid β42 levels in the clinical diagnosis of Alzheimer disease and relation to apolipoprotein E genotype. Arch Neurol 1998;55:937–945. [PubMed]
20. Samuels SC, Silverman JM, Marin DB, et al. CSF beta-amyloid, cognition, and APOE genotype in Alzheimer's disease. Neurology 1999;52:547. [PubMed]
21. Kester MI, van der Vlies AE, Blankenstein MA, et al. CSF biomarkers predict rate of cognitive decline in Alzheimer disease. Neurology 2009;73:1353–1358. [PubMed]
22. Lambert JC, Schraen-Maschke S, Richard F, et al. Association of plasma amyloid beta with risk of dementia: the prospective Three-City Study. Neurology 2009;73:847–853. [PubMed]
23. Clark CM, Xie S, Chittams J, et al. Cerebrospinal fluid tau and beta-amyloid: how well do these biomarkers reflect autopsy-confirmed dementia diagnoses? Arch Neurol 2003;60:1696–1702. [PubMed]
24. Shaw LM, Korecka M, Clark CM, Lee VM, Trojanowski JQ. Biomarkers of neurodegeneration for diagnosis and monitoring therapeutics. Nat Rev Drug Discov 2007;6:295–303. [PubMed]
25. Motter R, Vigo-Pelfrey C, Kholodenko D, et al. Reduction of beta-amyloid peptide42 in the cerebrospinal fluid of patients with Alzheimer's disease. Ann Neurol 1995;38:643–648. [PubMed]
26. Andreasen N, Minthon L, Davidsson P, et al. Evaluation of CSF-tau and CSF-Abeta42 as diagnostic markers for Alzheimer disease in clinical practice. Arch Neurol 2001;58:373–379. [PubMed]
27. Mollenhauer B, Bibl M, Trenkwalder C, et al. Follow-up investigations in cerebrospinal fluid of patients with dementia with Lewy bodies and Alzheimer's disease. J Neural Transm 2005;112:933–948. [PubMed]
28. Mollenhauer B, Trenkwalder C. Neurochemical biomarkers in the differential diagnosis of movement disorders. Mov Disord 2009;24:1411–1426. [PubMed]
29. Lippa CF, Duda JE, Grossman M, et al. DLB and PDD boundary issues: diagnosis, treatment, molecular pathology, and biomarkers. Neurology 2007;68:812–819. [PubMed]
30. Strittmatter WJ, Saunders AM, Schmechel D, et al. Apolipoprotein E: high-avidity binding to beta-amyloid and increased frequency of type 4 allele in late-onset familial Alzheimer disease. Proc Nat Acad Sci USA 1993;90:1977–1981. [PubMed]
31. Huang X, Chen P, Kaufer DI, Troster AI, Poole C. Apolipoprotein E and dementia in Parkinson disease: a meta-analysis. Arch Neurol 2006;63:189–193. [PubMed]
32. Prince JA, Zetterberg H, Andreasen N, Marcusson J, Blennow K. APOE ε4 allele is associated with reduced cerebrospinal fluid levels of Aβ42. Neurology 2004;62:2116–2118. [PubMed]
33. Kester MI, Verwey NA, van Elk EJ, Blankenstein MA, Scheltens P, van der Flier WM. Progression from MCI to AD: predictive value of CSF Aβ42 is modified by APOE genotype. Neurobiol Aging Epub 2009 Sep 10. [PubMed]
34. Williams-Gray CH, Evans JR, Goris A, et al. The distinct cognitive syndromes of Parkinson's disease: 5 year follow-up of the CamPaIGN cohort. Brain 2009;132:2958–2969. [PubMed]
35. Gustafson DR, Skoog I, Rosengren L, Zetterberg H, Blennow K. Cerebrospinal fluid beta-amyloid 1-42 concentration may predict cognitive decline in older women. J Neurol Neurosurg Psychiatry 2007;78:461–464. [PMC free article] [PubMed]
36. El Agnaf OM, Salem SA, Paleologou KE, et al. Detection of oligomeric forms of alpha-synuclein protein in human plasma as a potential biomarker for Parkinson's disease. FASEB J 2006;20:419–425. [PubMed]

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