| Title |
Impact of Common Variations in PLD3 on Neuroimaging Phenotypes in Non-demented Elders
|
|---|---|
| Published in |
Molecular Neurobiology, August 2015
|
| DOI | 10.1007/s12035-015-9370-4 |
| Pubmed ID | |
| Authors |
Chong Wang, Hui-Fu Wang, Meng-Shan Tan, Ying Liu, Teng Jiang, Dao-Qiang Zhang, Lan Tan, Jin-Tai Yu, Alzheimer’s Disease Neuroimaging Initiative |
| Abstract |
Rare variants of phospholipase D3 (PLD3) have been identified as Alzheimer's disease (AD) susceptibility loci, whereas little is known about the potential role of common variants in the progression of AD. To examine the impact of genetic variations in PLD3 on neuroimaging phenotypes in a large non-demented population. A total of 261 normal cognition (NC) and 456 mild cognitive impairment (MCI) individuals from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database are included in our analysis. Multiple linear regression models were applied to examine the association between four single-nucleotide polymorphisms (SNPs; rs7249146, rs4490097, rs12151243, and rs10407447) with the florbetapir retention on florbetapir 18F amyloid positron emission tomography (AV45-PET), the cerebral metabolic rate for glucose (CMRgl) on 18F-fluorodeoxyglucose PET (FDG-PET), and regional volume on magnetic resonance imaging (MRI) at baseline and in the cohort study. We did not detect any significant associations of PLD3 SNPs with florbetapir retention on AV45-PET. In the analysis of FDG-PET, rs10407447 was associated with the CMRgl in the left angular gyrus and bilateral posterior cingulate cortex in the MCI group. Regarding the MRI analysis, rs10407447 was also associated with bilateral inferior lateral ventricle and lateral ventricle volume in MCI group. The main findings of our study provide evidence that support the possible role of PLD3 common variants in influencing AD-related neuroimaging phenotypes. Nevertheless, further work is necessary to explain the functional mechanisms of differences and confirm the causal variants. |
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 38 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 5 | 13% |
| Other | 3 | 8% |
| Professor | 3 | 8% |
| Student > Ph. D. Student | 3 | 8% |
| Student > Bachelor | 2 | 5% |
| Other | 7 | 18% |
| Unknown | 15 | 39% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 4 | 11% |
| Medicine and Dentistry | 4 | 11% |
| Neuroscience | 4 | 11% |
| Unspecified | 2 | 5% |
| Agricultural and Biological Sciences | 1 | 3% |
| Other | 5 | 13% |
| Unknown | 18 | 47% |
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 02 February 2017.
All research outputs
#2,704,526
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Outputs from Molecular Neurobiology
#351
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#36,263
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Outputs of similar age from Molecular Neurobiology
#12
of 117 outputs
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