Apolipoprotein E and Dementia in Parkinson Disease

Department of Neurology, University of North Carolina School of Medicine, Chapel Hill 27599-7025, USA.
JAMA Neurology (Impact Factor: 7.42). 03/2006; 63(2):189-93. DOI: 10.1001/archneur.63.2.189
Source: PubMed


To understand the relationship of apolipoprotein E (APOE) polymorphism to dementia in Parkinson disease (PD) because the APOE epsilon4 allele is linked to Alzheimer disease.
We reviewed MEDLINE, BIOSIS Previews, and ISI Web of Science from January 1, 1966, to May 7, 2004, supplemented by citation analysis from retrieved articles.
Case-control studies using clinical or pathologic criteria for PD and dementia, and with complete APOE genotype frequencies data.
We compared estimated prevalence odds ratios for dementia in PD in relation to each allele. We also looked for evidence of heterogeneity and publication bias and performed a stratified analysis on several study characteristics.
Data analyses suggest publication bias and heterogeneity of source data for the epsilon4 allele (homogeneity P = .2; Begg and Mazumdar, P = .06; and Egger et al, P = .1). The estimated odds ratios for development of dementia in PD are 1.6 for epsilon4 (95% confidence interval, 1.0-2.5); 1.3 for epsilon2 (95% confidence interval, 0.73-2.4); and 0.54 for epsilon3 (95% confidence interval, 0.18-1.6). The odds ratio estimates for epsilon4 were higher for studies published in 1996 or later (2.3 vs 1.0) and for studies conducted outside North American sites (2.4 vs 1.2).
The APOE epsilon4 allele appears to be associated with a higher prevalence of dementia in PD. Publication bias and heterogeneous source data may, however, confound this conclusion. Confirmatory studies that use standardized and validated diagnostic criteria for dementia in PD are needed.

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    • "These techniques can be used to assist the diagnosis process and differentiate PD from essential tremor and other neurodegenerative disorders that may exhibit similar characteristics of PD patients (M. M. Lewis et al., 2007; Dastgheib, Lithgow, and Moussavi, 2011; Huang et al., 2006). While these diagnosis techniques have been proven to be effective at accurately diagnosing PD, greater than 50% of the dopaminergic neurons are lost by the time that a patient is clinically diagnosed with PD, making early-stage detection challenging and critically important for neuroprotective efforts (Gil and Manuel, 2009). "
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    ABSTRACT: Parkinson's disease (PD) is the second most common neurological disorder after Alzheimer's disease. Key clinical features of PD are motor-related and are typically assessed by healthcare providers based on qualitative visual inspection of a patient's movement/gait/posture. More advanced diagnostic techniques such as computed tomography scans that measure brain function, can be cost prohibitive and may expose patients to radiation and other harmful effects. To mitigate these challenges, and open a pathway to remote patient-physician assessment, the authors of this work propose a data mining–driven methodology that uses low cost, non-invasive sensors to model and predict the presence (or lack therefore) of PD movement abnormalities and model clinical subtypes. The study presented here evaluates the discriminative ability of non-invasive hardware and data mining algorithms to classify PD cases and controls. A 10-fold cross-validation approach is used to compare several data mining algorithms in order to determine that which provides the most consistent results when varying the subject gait data. Next, the predictive accuracy of the data mining model is quantified by testing it against unseen data captured from a test pool of subjects. The proposed methodology demonstrates the feasibility of using non-invasive, low cost, hardware and data mining models to monitor the progression of gait features outside of the traditional healthcare facility, which may ultimately lead to earlier diagnosis of emerging neurological diseases.
    Full-text · Article · Oct 2015
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    • "The APOE gene polymorphisms are associated with many other diseases. A meta-analysis showed that APOE ϵ4 allele appeared to be associated with a higher prevalence of dementia in Parkinson disease [44]. A meta-analysis suggested that the APOE ϵ4 isoform was a genetic factor that might influence the age at onset of temporal lobe epilepsy [45]. "
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    ABSTRACT: Studies investigating the association between the apolipoprotein E (APOE) gene polymorphism and the risk of intracerebral hemorrhage (ICH) have reported conflicting results. We here performed a meta-analysis based on the evidence currently available from the literature to make a more precise estimation of this relationship. Published literature from the National Library of Medline and Embase databases were retrieved. Odds ratio (OR) and 95% confidence interval (CI) were calculated in fixed- or random-effects models when appropriate. Subgroup analyses were performed by race. This meta-analysis included 11 case-control studies, which included 1,238 ICH cases and 3,575 controls. The combined results based on all studies showed that ICH cases had a significantly higher frequency of APOE epsilon4 allele (OR= 1.42, 95% CI= 1.21,1.67, P<0.001). In the subgroup analysis by race, we also found that ICH cases had a significantly higher frequency of APOE epsilon4 allele in Asians (OR= 1.52, 95% CI= 1.20,1.93, P<0.001) and in Caucasians (OR= 1.34, 95% CI= 1.07,1.66, P=0.009). There was no significant relationship between APOE epsilon2 allele and the risk of ICH. Our meta-analysis suggested that APOE epsilon4 allele was associated with a higher risk of ICH.
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    • "Although not associated with higher PD risk, ApoE ε4 tended to be associated with about 60% higher risk of dementia among PD patients, which was consistent with the previous two meta-analyses: OR=1.6 [95% CI (1.0–2.5)] (Huang, et al., 2006) and 1.74 [95% CI (1.36–2.23), p= 0.0001] (Williams-Gray, et al., 2009). "
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    ABSTRACT: We examined apolipoprotein E (ApoE) genotypes in relation to Parkinson's disease (PD) among 786 cases and 1537 controls, all non-Hispanic Caucasians. Odds ratios (ORs) and 95% confidence intervals (CIs) were derived from multivariate logistic regression models, adjusting for year of birth, sex, smoking status, daily caffeine intake, and family history of PD. Compared with participants with ApoE ε33, ε4 carriers (ε34/ε44) had significantly lower odds for having PD (OR, 0.75; 95% CI, 0.59-0.94; p = 0.01), whereas ε2 carriers (ε23/ε22) did not (OR, 0.95; 95% CI, 0.73-1.24; p = 0.71). Subgroup analyses showed similar results. In addition, we conducted a meta-analysis which confirmed our primary findings (ε34/ε44 vs. ε33: OR, 0.90; 95% CI, 0.81-0.99; p = 0.024 and ε23/ε22 vs. ε33: OR, 1.10; 95% CI, 0.97-1.23; p = 0.13). In PD patients, the prevalence of dementia appeared to be higher among ε4 carriers (compared with ε33: OR, 1.59; 95% CI, 0.98-2.58; p = 0.06), but lower among ε2 carriers (OR, 0.75; 95% CI, 0.40-1.42; p = 0.38), although neither test was statistically significant. Our study suggested that the ApoE ε4 allele may be associated with a lower PD risk among non-Hispanic Caucasians.
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