The overarching goal of this database is to serve as an unbiased, centralized, publicly available and regularly updated collection of genetic association studies performed on PD phenotypes. To ensure the highest degree of objectivity regarding the posted information, only studies published or in press in peer reviewed journals available in English are considered for inclusion into the database. We generally do no consider for inclusion data from abstracts presented at scientific meetings or findings reported in non-peer reviewed publications.
While we have made every possible effort to correctly represent the data of all studies fulfilling the above criteria we cannot exclude the possibility that some studies are cited incorrectly or were erroneously excluded. However, we are not able to make any warranty, either expressed or implied, with respect to the functioning and accuracy of this database. No responsibility is assumed by the authors and curators.
If you detect an error in the data posted on the database or want to submit general concerns, comments and suggestions about the database, please contact the Alzheimer Research Forum website. Finally, we encourage authors of original Parkinson's association studies either published or in press at a peer reviewed scientific journal to send us your data.
While the meta-analyses presented in this database take into account between-study heterogeneity by applying random effects models, they do not account for potential confounding due to publication bias, i.e. that the outcome or significance of any particular study directly influences its probability of publication. To some extent, the possibility of publication and other reporting biases is addressed by the I2 statistic and the logistic regression P-value listed on the "Top Results" page. However, reporting biases are generally difficult to measure and detect, and can never be excluded with 100% certainty.
Please note, that with only few studies included in the meta-analyses (i.e. less than 8-10), the random effects model may yield summary ORs that are slightly anti-conservative.