scholarly journals Genome-wide analysis of genetic predisposition to Alzheimer’s disease and related sex-disparities

2018 ◽  
Author(s):  
Alireza Nazarian ◽  
Anatoliy I. Yashin ◽  
Alexander M. Kulminski
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Genetic Architecture ◽  
Genetic Basis ◽  
The United States ◽  
Genome Wide Association ◽  
Polygenic Inheritance ◽  
Genome Wide ◽  
Sex Disparities ◽  
Males And Females

AbstractBackgroundAlzheimer’s disease (AD) is the most common cause of dementia in the elderly and the sixth leading cause of death in the United States. AD is mainly considered a complex disorder with polygenic inheritance. Despite discovering many susceptibility loci, a major proportion of AD genetic variance remains to be explained.MethodsWe investigated the genetic architecture of AD in four publicly available independent datasets through genome-wide association, transcriptome-wide association, and gene-based analyses. To explore differences in the genetic basis of AD between males and females, analyses were performed on three samples in each dataset: males and females combined, only males, or only females.ResultsOur genome-wide association analyses corroborated the associations of several previously detected AD loci and revealed novel significant associations of 54 single-nucleotide polymorphisms (SNPs) at a p-value of < 5E-06. In addition, 23 genes located outside the chromosome 19q13 region showed suggestive associations with AD at a false discovery rate of 0.05 in transcriptome-wide association and gene-based analyses. Most of the newly detected AD-associated SNPs and genes were sex specific, indicating sex disparities in the genetic basis of AD.ConclusionsOur findings, particularly the newly discovered sex-specific genetic contributors, provide novel insight into the genetic architecture of AD and can advance our understanding of its pathogenesis.

scholarly journals Prediction of Alzheimer's disease using multi-variants from a Chinese genome-wide association study

Brain ◽  
2020 ◽  
Author(s):  
Longfei Jia ◽  
Fangyu Li ◽  
Cuibai Wei ◽  
Min Zhu ◽  
Qiumin Qu ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Association Study ◽  
Predictive Models ◽  
Genome Wide Association Study ◽  
Disease Onset ◽  
Genome Wide Association ◽  
Nucleotide Polymorphisms ◽  
Risk Variants ◽  
Genome Wide

Abstract Previous genome-wide association studies have identified dozens of susceptibility loci for sporadic Alzheimer’s disease, but few of these loci have been validated in longitudinal cohorts. Establishing predictive models of Alzheimer’s disease based on these novel variants is clinically important for verifying whether they have pathological functions and provide a useful tool for screening of disease risk. In the current study, we performed a two-stage genome-wide association study of 3913 patients with Alzheimer’s disease and 7593 controls and identified four novel variants (rs3777215, rs6859823, rs234434, and rs2255835; Pcombined = 3.07 × 10−19, 2.49 × 10−23, 1.35 × 10−67, and 4.81 × 10−9, respectively) as well as nine variants in the apolipoprotein E region with genome-wide significance (P &lt; 5.0 × 10−8). Literature mining suggested that these novel single nucleotide polymorphisms are related to amyloid precursor protein transport and metabolism, antioxidation, and neurogenesis. Based on their possible roles in the development of Alzheimer’s disease, we used different combinations of these variants and the apolipoprotein E status and successively built 11 predictive models. The predictive models include relatively few single nucleotide polymorphisms useful for clinical practice, in which the maximum number was 13 and the minimum was only four. These predictive models were all significant and their peak of area under the curve reached 0.73 both in the first and second stages. Finally, these models were validated using a separate longitudinal cohort of 5474 individuals. The results showed that individuals carrying risk variants included in the models had a shorter latency and higher incidence of Alzheimer’s disease, suggesting that our models can predict Alzheimer’s disease onset in a population with genetic susceptibility. The effectiveness of the models for predicting Alzheimer’s disease onset confirmed the contributions of these identified variants to disease pathogenesis. In conclusion, this is the first study to validate genome-wide association study-based predictive models for evaluating the risk of Alzheimer’s disease onset in a large Chinese population. The clinical application of these models will be beneficial for individuals harbouring these risk variants, and particularly for young individuals seeking genetic consultation.

Genome-Wide Association Study of Brain Alzheimer’s Disease-Related Metabolic Decline as Measured by [18F] FDG-PET Imaging

2020 ◽  
Vol 77 (1) ◽  
pp. 401-409
Author(s):  
Rong-Ze Wang ◽  
Yu-Xiang Yang ◽  
Hong-Qi Li ◽  
Xue-Ning Shen ◽  
Shi-Dong Chen ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Association Study ◽  
Fdg Pet ◽  
Genome Wide Association Study ◽  
Genetic Model ◽  
Genome Wide Association ◽  
Angular Gyrus ◽  
Genome Wide ◽  
18F Fdg

Background: Hypometabolism detected by fluorodeoxyglucose F18 positron emission tomography ([18F] FDG PET) is an early neuropathologic changes in Alzheimer’s disease (AD) and provides important pathologic staging information. Objective: This study aimed to discover genetic interactions that regulate longitudinal glucose metabolic decline in AD-related brain regions. Methods: A total of 586 non-Hispanic white individuals from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) 1/GO/2 cohorts that met all quality control criteria were included in this study. Genome-wide association study of glucose metabolic decline in regions of interest (ROIs) was performed with linear regression under the additive genetic model. Results: We identified two novel variants that had a strong association with longitudinal metabolic decline in different ROI. Rs4819351-A in gene 1-acylglycerol-3-phosphate O-acyltransferase 3 (AGPAT3) demonstrated reduced metabolic decline in right temporal gyrus (p = 3.97×10–8, β= –0.016), while rs13387360-T in gene LOC101928196 demonstrated reduced metabolic decline in left angular gyrus (p = 1.69×10–8, β= –0.027). Conclusion: Our results suggest two genome-wide significant SNPs (rs4819351, rs13387360) in AGPAT3 and LOC101928196 as protective loci that modulate glucose metabolic decline. These two genes should be further investigated as potential therapeutic target for neurodegeneration diseases.

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