Literature DB >> 22402018

Implication of common and disease specific variants in CLU, CR1, and PICALM.

Raffaele Ferrari1, Jorge H Moreno, Abu T Minhajuddin, Sid E O'Bryant, Joan S Reisch, Robert C Barber, Parastoo Momeni.   

Abstract

Two recent genome-wide association studies (GWAS) for late onset Alzheimer's disease (LOAD) revealed 3 new genes: clusterin (CLU), phosphatidylinositol binding clathrin assembly protein (PICALM), and complement receptor 1 (CR1). In order to evaluate association with these genome-wide association study-identified genes and to isolate the variants contributing to the pathogenesis of LOAD, we genotyped the top single nucleotide polymorphisms (SNPs), rs11136000 (CLU), rs3818361 (CR1), and rs3851179 (PICALM), and sequenced the entire coding regions of these genes in our cohort of 342 LOAD patients and 277 control subjects. We confirmed the association of rs3851179 (PICALM) (p = 7.4 × 10(-3)) with the disease status. Through sequencing we identified 18 variants in CLU, 3 of which were found exclusively in patients; 8 variants (out of 65) in CR1 gene were only found in patients and the 16 variants identified in PICALM gene were present in both patients and controls. In silico analysis of the variants in PICALM did not predict any damaging effect on the protein. The haplotype analysis of the variants in each gene predicted a common haplotype when the 3 single nucleotide polymorphisms rs11136000 (CLU), rs3818361 (CR1), and rs3851179 (PICALM), respectively, were included. For each gene the haplotype structure and size differed between patients and controls. In conclusion, we confirmed association of CLU, CR1, and PICALM genes with the disease status in our cohort through identification of a number of disease-specific variants among patients through the sequencing of the coding region of these genes. Published by Elsevier Inc.

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Year:  2012        PMID: 22402018     DOI: 10.1016/j.neurobiolaging.2012.01.110

Source DB:  PubMed          Journal:  Neurobiol Aging        ISSN: 0197-4580            Impact factor:   4.673


  17 in total

Review 1.  Impact of late-onset Alzheimer's genetic risk factors on beta-amyloid endocytic production.

Authors:  Cláudia Guimas Almeida; Farzaneh Sadat Mirfakhar; Catarina Perdigão; Tatiana Burrinha
Journal:  Cell Mol Life Sci       Date:  2018-04-27       Impact factor: 9.261

2.  Validating GWAS-Identified Risk Loci for Alzheimer's Disease in Han Chinese Populations.

Authors:  Hui-Zhen Wang; Rui Bi; Qiu-Xiang Hu; Qun Xiang; Chen Zhang; Deng-Feng Zhang; Wen Zhang; Xiaohong Ma; Wanjun Guo; Wei Deng; Liansheng Zhao; Peiyan Ni; Mingli Li; Yiru Fang; Tao Li; Yong-Gang Yao
Journal:  Mol Neurobiol       Date:  2014-12-03       Impact factor: 5.590

3.  Late-onset Alzheimer's risk variants in memory decline, incident mild cognitive impairment, and Alzheimer's disease.

Authors:  Minerva M Carrasquillo; Julia E Crook; Otto Pedraza; Colleen S Thomas; V Shane Pankratz; Mariet Allen; Thuy Nguyen; Kimberly G Malphrus; Li Ma; Gina D Bisceglio; Rosebud O Roberts; John A Lucas; Glenn E Smith; Robert J Ivnik; Mary M Machulda; Neill R Graff-Radford; Ronald C Petersen; Steven G Younkin; Nilüfer Ertekin-Taner
Journal:  Neurobiol Aging       Date:  2014-08-04       Impact factor: 4.673

Review 4.  The Role of PICALM in Alzheimer's Disease.

Authors:  Wei Xu; Lan Tan; Jin-Tai Yu
Journal:  Mol Neurobiol       Date:  2014-09-04       Impact factor: 5.590

5.  Association of MTHFR and PICALM polymorphisms with Alzheimer's disease.

Authors:  Luciano Belcavello; Daniela Camporez; Leila D Almeida; Renato L Morelato; Maria C P Batitucci; Flavia de Paula
Journal:  Mol Biol Rep       Date:  2014-10-31       Impact factor: 2.316

6.  rs3851179 Polymorphism at 5' to the PICALM Gene is Associated with Alzheimer and Parkinson Diseases in Brazilian Population.

Authors:  Cíntia Barros Santos-Rebouças; Andressa Pereira Gonçalves; Jussara Mendonça Dos Santos; Bianca Barbosa Abdala; Luciana Branco Motta; Jerson Laks; Margarete Borges de Borges; Ana Lúcia Zuma de Rosso; João Santos Pereira; Denise Hack Nicaretta; Márcia Mattos Gonçalves Pimentel
Journal:  Neuromolecular Med       Date:  2017-05-31       Impact factor: 3.843

7.  Effect of CR1 Genetic Variants on Cerebrospinal Fluid and Neuroimaging Biomarkers in Healthy, Mild Cognitive Impairment and Alzheimer's Disease Cohorts.

Authors:  Xi-Chen Zhu; Hui-Fu Wang; Teng Jiang; Huan Lu; Meng-Shan Tan; Chen-Chen Tan; Lin Tan; Lan Tan; Jin-Tai Yu
Journal:  Mol Neurobiol       Date:  2016-01-07       Impact factor: 5.590

8.  Whole-exome sequencing and imaging genetics identify functional variants for rate of change in hippocampal volume in mild cognitive impairment.

Authors:  K Nho; J J Corneveaux; S Kim; H Lin; S L Risacher; L Shen; S Swaminathan; V K Ramanan; Y Liu; T Foroud; M H Inlow; A L Siniard; R A Reiman; P S Aisen; R C Petersen; R C Green; C R Jack; M W Weiner; C T Baldwin; K Lunetta; L A Farrer; S J Furney; S Lovestone; A Simmons; P Mecocci; B Vellas; M Tsolaki; I Kloszewska; H Soininen; B C McDonald; M R Farlow; B Ghetti; M J Huentelman; A J Saykin
Journal:  Mol Psychiatry       Date:  2013-04-23       Impact factor: 15.992

9.  A Network of Genetic Effects on Non-Demented Cognitive Aging: Alzheimer's Genetic Risk (CLU + CR1 + PICALM) Intensifies Cognitive Aging Genetic Risk (COMT + BDNF) Selectively for APOEɛ4 Carriers.

Authors:  Shraddha Sapkota; Roger A Dixon
Journal:  J Alzheimers Dis       Date:  2018       Impact factor: 4.472

10.  Association between clusterin concentration and dementia: a systematic review and meta-analysis.

Authors:  Caiping Yang; Hai Wang; Chaojiu Li; Huiyan Niu; Shunkui Luo; Xingzhi Guo
Journal:  Metab Brain Dis       Date:  2018-10-05       Impact factor: 3.584

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