scholarly journals Association Study of Genetic Variants inCDKN2A/CDKN2BGenes/Loci with Late-Onset Alzheimer's Disease

2011 ◽  
Vol 2011 ◽  
pp. 1-4
Author(s):  
Andrea Tedde ◽  
Irene Piaceri ◽  
Silvia Bagnoli ◽  
Ersilia Lucenteforte ◽  
Uwe Ueberham ◽  
...  

Alzheimer's disease (AD) is the most common form of dementia clinically characterized by progressive impairment of memory and other cognitive functions. Many genetic researches in AD identified one common genetic variant (ε4) in Apolipoprotein E (APOE) gene as a risk factor for the disease. Two independent genome-wide studies demonstrated a new locus on chromosome 9p21.3 implicated in Late-Onset Alzheimer's Disease (LOAD) susceptibility in Caucasians. In the present study, we investigated the role of three SNP's in theCDKN2Agene (rs15515, rs3731246, and rs3731211) and one in theCDKN2Bgene (rs598664) located in 9p21.3 using an association case-control study carried out in a group of Caucasian subjects including 238 LOAD cases and 250 controls. The role ofCDKN2AandCDKN2Bgenetic variants in AD is not confirmed in our LOAD patients, and further studies are needed to elucidate the role of these genes in the susceptibility of AD.

2019 ◽  
Author(s):  
Javier de Velasco Oriol ◽  
Edgar E. Vallejo ◽  
Karol Estrada ◽  

AbstractAlzheimer’s disease (AD) is the leading form of dementia. Over 25 million cases have been estimated worldwide and this number is predicted to increase two-fold every 20 years. Even though there is a variety of clinical markers available for the diagnosis of AD, the accurate and timely diagnosis of this disease remains elusive. Recently, over a dozen of genetic variants predisposing to the disease have been identified by genome-wide association studies. However, these genetic variants only explain a small fraction of the estimated genetic component of the disease. Therefore, useful predictions of AD from genetic data could not rely on these markers exclusively as they are not sufficiently informative predictors. In this study, we propose the use of deep neural networks for the prediction of late-onset Alzheimer’s disease from a large number of genetic variants. Experimental results indicate that the proposed model holds promise to produce useful predictions for clinical diagnosis of AD.


BMC Neurology ◽  
2011 ◽  
Vol 11 (1) ◽  
Author(s):  
Giovanni Zuliani ◽  
Michela Perrone Donnorso ◽  
Cristina Bosi ◽  
Angelina Passaro ◽  
Edoardo Dalla Nora ◽  
...  

2011 ◽  
Vol 6 (1) ◽  
pp. 54 ◽  
Author(s):  
Minerva M Carrasquillo ◽  
Olivia Belbin ◽  
Talisha A Hunter ◽  
Li Ma ◽  
Gina D Bisceglio ◽  
...  

2004 ◽  
Vol 366 (3) ◽  
pp. 268-271 ◽  
Author(s):  
Yonghong Li ◽  
Kristina Tacey ◽  
Lisa Doil ◽  
Ryan van Luchene ◽  
Veronica Garcia ◽  
...  

2004 ◽  
Vol 33 (3) ◽  
pp. 258-266 ◽  
Author(s):  
Laura Fratiglioni ◽  
Anders Ahlbom ◽  
Matti Viitanen ◽  
Bengt Winblad

Neurology ◽  
1987 ◽  
Vol 37 (8) ◽  
pp. 1295-1295 ◽  
Author(s):  
V. Chandra ◽  
V. Philipose ◽  
P. A. Bell ◽  
A. Lazaroff ◽  
B. S. Schoenberg

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