| Title |
Genetics of early-onset Parkinson's disease in Finland: exome sequencing and genome-wide association study
|
|---|---|
| Published in |
Neurobiology of Aging, February 2017
|
| DOI | 10.1016/j.neurobiolaging.2017.01.019 |
| Pubmed ID | |
| Authors |
Ari Siitonen, Michael A. Nalls, Dena Hernández, J. Raphael Gibbs, Jinhui Ding, Pauli Ylikotila, Connor Edsall, Andrew Singleton, Kari Majamaa |
| Abstract |
Several genes and risk factors are associated with Parkinson's disease (PD). Although many of the genetic markers belong to a common pathway, a unifying pathogenetic mechanism is yet to be found. Also, missing heritability analyses have estimated that only part of the genetic influence contributing to PD has been found. Here, we carried out whole-exome sequencing (WES) on 438 Finnish patients with early-onset PD. We also reanalyzed previous data from genome-wide association studies (GWAS) on the same cohort. Variants in the CEL gene/locus were associated with PD in both GWAS and WES analysis. Exome-wide gene-based association tests also identified the MPHOSPH10, TAS2R19, and SERPINA1 genes in the discovery data set (p < 2.5E-6). MPHOSPH10 had estimated odds ratio (OR) of 1.53, and the rs141620200 variant in SERPINA1 had OR of 1.27. We identified several candidate genes, but further investigation is required to determine the role of these genes in PD. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 59 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 9 | 15% |
| Researcher | 8 | 14% |
| Student > Ph. D. Student | 8 | 14% |
| Student > Bachelor | 7 | 12% |
| Other | 4 | 7% |
| Other | 8 | 14% |
| Unknown | 15 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 16 | 27% |
| Agricultural and Biological Sciences | 9 | 15% |
| Neuroscience | 5 | 8% |
| Medicine and Dentistry | 4 | 7% |
| Computer Science | 2 | 3% |
| Other | 4 | 7% |
| Unknown | 19 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 May 2017.
All research outputs
#3,205,236
of 25,394,764 outputs
Outputs from Neurobiology of Aging
#1,017
of 4,418 outputs
Outputs of similar age
#62,296
of 424,744 outputs
Outputs of similar age from Neurobiology of Aging
#29
of 90 outputs
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We're also able to compare this research output to 90 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.