scholarly journals Association of Polygenic Risk Score with Age at Onset and Cerebrospinal Fluid Biomarkers of Alzheimer’s Disease in a Chinese Cohort

2020 ◽  
Vol 36 (7) ◽  
pp. 696-704 ◽  
Author(s):  
Wei-Wei Li ◽  
Zhen Wang ◽  
Dong-Yu Fan ◽  
Ying-Ying Shen ◽  
Dong-Wan Chen ◽  
...  
2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Itziar de Rojas ◽  
Sonia Moreno-Grau ◽  
Niccolo Tesi ◽  
Benjamin Grenier-Boley ◽  
Victor Andrade ◽  
...  

AbstractGenetic discoveries of Alzheimer’s disease are the drivers of our understanding, and together with polygenetic risk stratification can contribute towards planning of feasible and efficient preventive and curative clinical trials. We first perform a large genetic association study by merging all available case-control datasets and by-proxy study results (discovery n = 409,435 and validation size n = 58,190). Here, we add six variants associated with Alzheimer’s disease risk (near APP, CHRNE, PRKD3/NDUFAF7, PLCG2 and two exonic variants in the SHARPIN gene). Assessment of the polygenic risk score and stratifying by APOE reveal a 4 to 5.5 years difference in median age at onset of Alzheimer’s disease patients in APOE ɛ4 carriers. Because of this study, the underlying mechanisms of APP can be studied to refine the amyloid cascade and the polygenic risk score provides a tool to select individuals at high risk of Alzheimer’s disease.


2015 ◽  
Vol 11 (7S_Part_19) ◽  
pp. P872-P872 ◽  
Author(s):  
Valentina Escott-Price ◽  
Rebecca Sims ◽  
Denise Harold ◽  
Maria Vronskaya ◽  
Peter Holmans ◽  
...  

2006 ◽  
Vol 14 (7S_Part_20) ◽  
pp. P1094-P1094
Author(s):  
Sultan Raja Chaudhury ◽  
Tulsi Patel ◽  
Abigail Fallows ◽  
Keeley J. Brookes ◽  
Tamar Guetta-Baranes ◽  
...  

Author(s):  
V. Escott-Price ◽  
A. Myers ◽  
M. Huentelman ◽  
M. Shoai ◽  
J. Hardy

The We and others have previously shown that polygenic risk score analysis (PRS) has considerable predictive utility for identifying those at high risk of developing Alzheimer’s disease (AD) with an area under the curve (AUC) of >0.8. However, by far the greatest determinant of this risk is the apolipoprotein E locus with the E4 allele alone giving an AUC of ~0.68 and the inclusion of the protective E2 allele increasing this to ~0.69 in a clinical cohort. An important question is to determine how good PRS is at predicting risk in those who do not carry the E4 allele (E3 homozygotes, E3E2 and E2E2) and in those who carry neither the E4 or E2 allele (i.e. E3 homozygotes). Previous studies have shown that PRS remains a significant predictor of AD risk in clinical cohorts after controlling for APOE ε4 carrier status. In this study we assess the accuracy of PRS prediction in a cohort of pathologically confirmed AD cases and controls. The exclusion of APOE4 carriers has surprisingly little effect on the PRS prediction accuracy (AUC ~0.83 [95% CI: 0.80-0.86]), and the accuracy remained higher than that in clinical cohorts with APOE included as a predictor. From a practical perspective this suggests that PRS analysis will have predictive utility even in E4 negative individuals and may be useful in clinical trial design.


2018 ◽  
Vol 24 (3) ◽  
pp. 421-430 ◽  
Author(s):  
Mark W. Logue ◽  
Matthew S. Panizzon ◽  
Jeremy A. Elman ◽  
Nathan A. Gillespie ◽  
Sean N. Hatton ◽  
...  

2017 ◽  
Vol 56 (1) ◽  
pp. 25-36 ◽  
Author(s):  
Angharad R. Morgan ◽  
Samuel Touchard ◽  
Caroline O’Hagan ◽  
Rebecca Sims ◽  
Elisa Majounie ◽  
...  

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