Name
Title | ||
|---|---|---|
Knowledge-driven binning approach for rare variant association analysis: application to neuroimaging biomarkers in Alzheimer's disease. |
Abstract | ||
|---|---|---|
Our novel binning approach identified rare variants in FANCC as well as 7 evolutionary conserved regions significantly associated with a LOAD-related neuroimaging endophenotype. FANCC (fanconi anemia complementation group C) has been shown to modulate TLR and p38 MAPK-dependent expression of IL-1β in macrophages. Our results warrant further investigation in a larger independent cohort and demonstrate that the biological knowledge-driven binning approach is a powerful strategy to identify rare variants associated with AD and other complex disease. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1186/s12911-017-0454-0 | BMC Med. Inf. & Decision Making |
Keywords | Field | DocType |
Alzheimer’s disease,Imaging genomics,Rare variant analysis | Human genetics,Entorhinal cortex,Endophenotype,Multiple comparisons problem,Genome-wide association study,Genetic association,Neuroimaging,Bioinformatics,Minor allele frequency,Medicine | Journal |
Volume | Issue | ISSN |
17 | S-1 | 1472-6947 |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dokyoon Kim | 1 | 0 | 1.69 |
| Anna Okula Basile | 2 | 2 | 1.23 |
| Lisa Bang | 3 | 0 | 0.34 |
| Emrin Horgusluoglu | 4 | 0 | 0.34 |
| SeungGeun Lee | 5 | 0 | 1.35 |
| Marylyn D. Ritchie | 6 | 692 | 86.79 |
| Saykin Andrew J | 7 | 631 | 66.57 |
| Nho Kwangsik | 8 | 138 | 14.59 |