Updated 29 August 2007
1. Introduction
Parkinson's disease (PD) is a complex and heterogeneous disorder in both nosology and genetics (Forman, 2005). To date, mutations in six genes have been identified to cause predominantly early-onset parkinsonism, which typically follows Mendelian inheritance (Farrer, 2006). PD without obvious familial aggregation ("idiopathic PD"), on the other hand, is likely governed by a variety of genetic and non-genetic factors that define an individual's risk to develop the disorder, as well as onset age, clinical presentation and progression (Pardo, 2005). It is still a matter of debate to which extent genetic factors contribute to PD risk in cases with onset beyond 50 years (Tanner, 1999; Sveinbjornsdottir, 2000; Maher, 2002; de la Fuente-Fernandez, 2003; Wirdefeldt, 2004; Lin, 2005).
In the past decade, literally hundreds of reports have been published claiming or refuting genetic association between putative PD genes and disease risk, onset age variation, or other phenotypic variables. We estimate that 40 to 80 PD genetic association studies are currently being published annually from research groups worldwide. For the public but also for the PD genetics research community this wealth of information is becoming increasingly more difficult to follow, evaluate, and much less to interpret.
2. Database Organization and Methods
Overview
The goal of the PDGene database is to serve as a comprehensive, unbiased, publicly available and regularly updated collection of published genetic association studies performed on PD. Eligible publications are identified following systematic searches of scientific literature databases, as well as the table of contents of journals in genetics, neurology, and psychiatry. Data selected for display summarize key characteristics of the investigated study cohorts (e.g., gene overview), as well as genotype distributions in cases and controls (e.g., polymorphism details). For polymorphisms with genotype data in at least
four case-control samples, continuously updated random-effects meta-analyses
are presented (see
meta-analysis methods). Note that data obtained from family-based studies
are not included in the meta-analyses, as crude odds ratios cannot be readily
calculated from overall genotype distributions. However, these studies and
their qualitative results are still listed on the gene-summary pages of the
PDGene website (see
Table 2 for example).
To ensure the highest degree of scientific objectivity, only studies
published in peer-reviewed journals available in English are considered for
inclusion into the database. In particular, this precludes the inclusion of
data presented only in abstracted form, e.g. at scientific meetings. We
encourage authors of original reports fulfilling the above criteria to submit their data as soon as
their work is accepted for publication.
Meta-Analysis Methods
For all polymorphisms with minor allele
frequencies in healthy controls >1%, and for which case-control genotype
data are available in four or more independent samples, crude odds ratios (ORs)
and 95 percent confidence intervals (CIs) are calculated from the reported
allele distributions for each study. Summary ORs and 95 percent CIs are calculated using the DerSimonian and Laird (1986) random-effects model, which utilizes weights that
incorporate both within-study and between-study variance. This procedure is
done including all studies irrespective of ethnicity (denoted by "All
Studies" on the meta-analysis figures), and repeated after exclusion of
the initial study ("All Excl Initial Study"), after exclusion of
studies in which a deviation of Hardy-Weinberg Equilibrium (HWE) was detected
in controls ("All Excl HWE Deviations"), and after exclusion of samples
of non-Caucasian ancestry ("All Caucasian Studies"). Overlapping
samples (of which usually only the largest is included), studies with missing
data, or control samples deviating from HWE are indicated on the meta-analysis
graphs. Please note, that when only a few studies are included in the meta-analyses
(i.e. less than ~10), the random effects model may yield summary ORs and
confidence bounds that are slightly anti-conservative.
To allow a visual assessment of the presence
of publication bias (or other sorts of reporting bias), we use a Begg modified
funnel plot which depicts the allele-specific OR (on a logarithmic scale)
against its standard error for each study (Egger, 1997) including studies of
all ethnicities. Note that the power to detect deviations from a symmetrical
distribution is limited, especially for analyses based on less than ~20
individual studies.
Inclusion of Genome-wide Association (GWA) Analyses
The systematic inclusion of data from
large-scale studies and GWA analyses represents a conceptual and computational
challenge for any genetic database. We have devised the following step-wise
protocol, which we believe allows us to capture the most relevant genetic information
without the need to include every data-point from these studies. Note that this
feature of PDGene is new and still under development. Please visit this page to see a summary of all published large-scale
studies currently included in PDGene.
Stage I: Represents the inclusion
of genes and polymorphisms “featured” or
highlighted by the authors of the large-scale study, usually because they show
some degree of genetic association after completion of all analyses, e.g.
testing multiple independent samples. These genes and polymorphisms probably
represent the most important findings of each large-scale analysis and are
therefore included here with highest priority. Genomic loci that do not map within any known gene are represented by a surrogate name specifying the cytogenetic location (e.g. “GWA_1q25.12”). This stage has already been
implemented in the current version of PDGene (e.g. for the SEMA5A gene featured in the GWA study by Maraganore et al. [2005]).
For large-scale/GWA
studies that have made their genotype data publicly available, we will also make use of “non-featured” genotype
distributions, i.e. of polymorphisms not believed to be associated with PD in
the original publications:
Stage II: Will add large-scale/GWA
genotype data for polymorphisms already available in PDGene, i.e. usually derived from candidate gene studies. Large-scale/GWA data for
such overlapping polymorphisms will be added to the gene-specific entries and,
if genotype data is then available in a total of at least four independent
case-control samples, included and displayed in the meta-analyses. This stage adds valuable information to the existing PDGene meta-analyses as it is derived from assessments that are largely
unbiased with respect to gene function, in contrast to most conventional
candidate gene studies. This stage has been implemented to PDGene using the publicly available data from the two GWA studies performed in PD to date (Maraganore, 2005; Fung, 2006).
Stage III: Applies to GWA studies
only. If genotype distributions are publicly available for multiple GWA scans,
we will perform systematic meta-analyses for all markers overlapping in at
least four independent case-control samples. Only those showing significant
summary ORs will be displayed on the PDGene website. The threshold of
declaring statistical significance (resulting in being displayed at the
front-end of the database) in this context will be more stringent, due to the
large number of tests performed (i.e. P-values of the summary ORs <<0.05).
Procedures for implementing this stage, and the definition of appropriate
threshold criteria is currently underway and will follow guidelines suggested previously (Evangelou, 2007). This feature is not yet available in PDGene.
For more details on inclusion criteria, literature searches, data-management
procedures, statistical analyses, and online database structure, please see Bertram et
al. (2007).
3. Summary of Meta-analysis Highlights:
The "Top Results" List
In an effort to facilitate the
identification of the most promising meta-analysis results available in
PDGene, a continuously updated list displaying the most strongly associated
genes ("Top Results") has been added to the homepage. The
list is ranked by effect size, and only includes genes that contain at least
one variant showing a nominally significant summary OR in the analysis of all
ethnic groups (“All”), or those limited to samples of Caucasian ancestry
(“Caucasian only”). While we believe that this list represents an up-to-date
summary of particularly promising PD candidate genes that warrant follow-up
with high priority, we note that many of these may represent false-positive
findings, in particular those based on small (<10) sample sizes.
4. Mendelian PD Genes
Please note also that the PDGene database will not sample and catalogue reports of causal mutations leading to PD or parkinsonism of classic Mendelian inheritance (such as disease-causing mutations in a-synuclein or parkin), but will only focus on genetic association studies probably governed by a more complex (and largely unknown) array of genetic transmission. For a collection of Mendelian PD genes, please consult the Parkinson's disease Mutation Database curated by the Parkinson's Institute, or the Parkinson's disease Mutation Database curated by Indiana University. Note that despite the exclusion of disease-causing mutations, data from bona fide association studies using common polymorphisms in any of the Mendelian PD genes will be included and meta-analyzed for PDGene.
References
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Farrer, M.J. (2006). "Genetics of Parkinson disease: paradigm shifts and future prospects." Nat Rev Genet 7(4):306-18.
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Maraganore DM, de Andrade M, Lesnick TG, Strain KJ, Farrer MJ, Rocca WA, Pant PV, Frazer KA, Cox DR, Ballinger DG. "High-resolution whole-genome association study of Parkinson disease." Am J Hum Genet. 2005 Nov;77(5):685-93.
Pardo, L.M., van Duijn, C.M. (2005). "In search of genes involved in neurodegenerative disorders." Mutat Res 30;592(1-2):89-101.
Tanner, C. M., R. Ottman, et al. (1999). "Parkinson disease in twins: an etiologic study." Jama 281: 341-6.
Sveinbjornsdottir S, Hicks AA, et al (2000). "Familial aggregation of Parkinson's disease in Iceland." N Engl J Med 343(24):1765-70.
Wirdefeldt K, Gatz M, et al. (2004). "No evidence for heritability of Parkinson disease in Swedish twins." Neurology 63(2):305-11.
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