scholarly journals East Asian-specific novel loci associated with late-onset Alzheimer’s disease: the GARD cohort Genome-wide study

2020 ◽  
Author(s):  
Sarang Kang ◽  
Tamil Iniyan Gunasekaran ◽  
Kyu Yeong Choi ◽  
Jang Jae Lee ◽  
Sungho Won ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Large Scale ◽  
Genetic Factors ◽  
Late Onset ◽  
East Asian ◽  
Genetic Heritability ◽  
Genome Wide ◽  
Japanese Sample ◽  
Genomic Studies

ABSTRACTThe high genetic heritability of Alzheimer’s disease has contributed to the multi-directional and large-scale genomic studies to discover genetic factors, and so far many massive studies have been reported. However, the majority of genetic factors have been identified through European races, and relatively few studies using East Asians to discover genetic factors. In this study, East Asian specific loci is first reported through GWAS using GARD cohorts, which have been intensively recruited and managed by a single institution. ApoE-stratified GWAS with the AD cases and matched controls (n=2,291) in the Korean cohort and validation analysis using a Japanese sample (n=1,956) replicated six previously reported loci (genes) including ApoE and suggested two novel susceptible loci in LRIG1 and CACNA1A gene. This study demonstrates that discovery of AD-associated variants can be accomplished in ethnic groups of a more homogeneous genetic background using samples comprising fewer subjects.

scholarly journals Potential Novel Genes for Late-Onset Alzheimer’s Disease in East-Asian Descent Identified by APOE-Stratified Genome-Wide Association Study

2021 ◽  
pp. 1-10
Author(s):  
Sarang Kang ◽  
Jungsoo Gim ◽  
Jiwoon Lee ◽  
Tamil Iniyan Gunasekaran ◽  
Kyu Yeong Choi ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Association Study ◽  
Genome Wide Association Study ◽  
Late Onset ◽  
East Asian ◽  
Genome Wide Association ◽  
Japanese Cohort ◽  
Genome Wide ◽  
A Genome

The present study reports two novel genome-wide significant loci for late-onset Alzheimer’s disease (LOAD) identified from APOE ε4 non-carrier subjects of East Asian origin. A genome-wide association study of Alzheimer’s disease was performed in 2,291 Korean seniors in the discovery phase, from the Gwangju Alzheimer’ and Related Dementias (GARD) cohort study. The study was replicated in a Japanese cohort of 1,956 subjects that suggested two novel susceptible SNPs in two genes: LRIG1 and CACNA1A. This study demonstrates that the discovery of AD-associated variants is feasible in non-European ethnic groups using samples comprising fewer subjects from the more homogeneous genetic background.

scholarly journals Genetic effect estimates in case-control studies when a continuous variable is omitted from the model

2019 ◽  
Author(s):  
Ying Sheng ◽  
Chiung-Yu Huang ◽  
Siarhei Lobach ◽  
Lydia Zablotska ◽  
Iryna Lobach ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Large Scale ◽  
False Positive Rate ◽  
Continuous Variable ◽  
Genetic Effects ◽  
Data Availability ◽  
Conditional Density ◽  
Link Type ◽  
Genome Wide

ABSTRACTLarge-scale genome-wide analyses scans provide massive volumes of genetic variants on large number of cases and controls that can be used to estimate the genetic effects. Yet, the sets of non-genetic variables available in publicly available databases are often brief. It is known that omitting a continuous variable from a logistic regression model can result in biased estimates of odds ratios (OR) (e.g., Gail et al (1984), Neuhaus et al (1993), Hauck et al (1991), Zeger et al (1988)). We are interested to assess what information is needed to recover the bias in the OR estimate of genotype due to omitting a continuous variable in settings when the actual values of the omitted variable are not available. We derive two estimating procedures that can recover the degree of bias based on a conditional density of the omitted variable or knowing the distribution of the omitted variable. Importantly, our derivations show that omitting a continuous variable can result in either under- or over-estimation of the genetic effects. We performed extensive simulation studies to examine bias, variability, false positive rate, and power in the model that omits a continuous variable. We show the application to two genome-wide studies of Alzheimer’s disease.Data Availability StatementThe data that support the findings of this study are openly available in the Database of Genotypes and Phenotypes at [https://www.ncbi.nlm.nih.gov/projects/gap/cgibin/study.cgi?study_id=phs000372.v1.p1], reference number [phs000372.v1.p1] and at the Alzheimer’s Disease Neuroimaging Initiative http://adni.loni.usc.edu/.

scholarly journals Genes, pathways and risk prediction in Alzheimer’s disease

2019 ◽  
Author(s):  
John Hardy ◽  
Valentina Escott-Price
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Late Onset ◽  
Membrane Damage ◽  
Disease Process ◽  
Complete Understanding ◽  
Induced Membrane ◽  
Genome Wide ◽  
Key Factor ◽  
Risk Of Disease

Abstract The failure of recent clinical trials in Alzheimer's disease has highlighted the need for the development of a more complete understanding of the pathogenesis of the disorder and also a belief that therapies may only work if given very early in the disease process before overt symptoms occur. The rare, early onset forms of the disease are all caused by mutations which make amyloid deposition a more likely event. Here we discuss the recent data showing that, in contrast, much of the risk of late onset disease is encoded by loci involved in lipid metabolism and/or encoded by microglia. We discuss these finding and suggest that amyloid induced membrane damage may be a key factor in disease and also review the evidence that genome wide genetic analysis can substantially help in the prediction of those individuals at high risk of disease in the general population.

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 ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Genetic Variants ◽  
Genetic Variant ◽  
Case Control Study ◽  
Late Onset ◽  
Common Genetic Variant ◽  
Genome Wide ◽  
Control Study

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.

scholarly journals Genetic underpinnings in Alzheimer’s disease – a review

2017 ◽  
Vol 29 (1) ◽  
pp. 21-38 ◽  
Author(s):  
Ahmed A. Moustafa ◽  
Mubashir Hassan ◽  
Doaa H. Hewedi ◽  
Iman Hewedi ◽  
Julia K. Garami ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Late Onset ◽  
Genetic Research ◽  
Twin Studies ◽  
Pedigree Analysis ◽  
Protein Signaling ◽  
Genetic Components ◽  
Genome Wide ◽  
Pharmacological Targets

AbstractIn this review, we discuss the genetic etiologies of Alzheimer’s disease (AD). Furthermore, we review genetic links to protein signaling pathways as novel pharmacological targets to treat AD. Moreover, we also discuss the clumps of AD-m ediated genes according to their single nucleotide polymorphism mutations. Rigorous data mining approaches justified the significant role of genes in AD prevalence. Pedigree analysis and twin studies suggest that genetic components are part of the etiology, rather than only being risk factors for AD. The first autosomal dominant mutation in the amyloid precursor protein (APP) gene was described in 1991. Later, AD was also associated with mutated early-onset (presenilin 1/2,PSEN1/2andAPP) and late-onset (apolipoprotein E,ApoE) genes. Genome-wide association and linkage analysis studies with identified multiple genomic areas have implications for the treatment of AD. We conclude this review with future directions and clinical implications of genetic research in AD.

scholarly journals Predicting late-onset Alzheimer’s disease from genomic data using deep neural networks

2019 ◽  
Author(s):  
Javier de Velasco Oriol ◽  
Edgar E. Vallejo ◽  
Karol Estrada ◽  
Keyword(s):  
Alzheimer’S Disease ◽  
Neural Networks ◽  
Alzheimer's Disease ◽  
Genetic Variants ◽  
Deep Neural Networks ◽  
Late Onset ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Clinical Markers ◽  
Genome Wide

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.

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