scholarly journals Genetic predisposition, Aβ misfolding in blood plasma, and Alzheimer’s disease

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hannah Stocker ◽  
Andreas Nabers ◽  
Laura Perna ◽  
Tobias Möllers ◽  
Dan Rujescu ◽  
...  

AbstractAlzheimer’s disease is highly heritable and characterized by amyloid plaques and tau tangles in the brain. The aim of this study was to investigate the association between genetic predisposition, Aβ misfolding in blood plasma, a unique marker of Alzheimer associated neuropathological changes, and Alzheimer’s disease occurrence within 14 years. Within a German community-based cohort, two polygenic risk scores (clinical Alzheimer’s disease and Aβ42 based) were calculated, APOE genotype was determined, and Aβ misfolding in blood plasma was measured by immuno-infrared sensor in 59 participants diagnosed with Alzheimer’s disease during 14 years of follow-up and 581 participants without dementia diagnosis. Associations between each genetic marker and Aβ misfolding were assessed through logistic regression and the ability of each genetic marker and Aβ misfolding to predict Alzheimer’s disease was determined. The Alzheimer’s disease polygenic risk score and APOE ε4 presence were associated to Aβ misfolding (odds ratio, 95% confidence interval: per standard deviation increase of score: 1.25, 1.03–1.51; APOE ε4 presence: 1.61, 1.04–2.49). No association was evident for the Aβ polygenic risk score. All genetic markers were predictive of Alzheimer’s disease diagnosis albeit much less so than Aβ misfolding (areas under the curve: Aβ polygenic risk score: 0.55; AD polygenic risk score: 0.59; APOE ε4: 0.63; Aβ misfolding: 0.84). Clinical Alzheimer’s genetic risk was associated to early pathological changes (Aβ misfolding) measured in blood, however, predicted Alzheimer’s disease less accurately than Aβ misfolding itself. Genetic predisposition may provide information regarding disease initiation, while Aβ misfolding could be important in clinical risk prediction.

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 ◽  
...  

2021 ◽  
Author(s):  
Daniel J. Panyard ◽  
Yuetiva K. Deming ◽  
Burcu F. Darst ◽  
Carol A. Van Hulle ◽  
Kaj Blennow ◽  
...  

AbstractAlthough our understanding of Alzheimer’s disease (AD) has greatly improved in recent years, the root cause remains unclear, making it difficult to find effective diagnosis and treatment options. Our understanding of the pathophysiology underlying AD has benefited from genomic analyses, including those that leverage polygenic risk score (PRS) models of disease. In many aspects of genomic research the use of functional annotation has been able to improve the power of genomic models. Here, we leveraged genomic functional annotations to build tissue-specific PRS models for 13 tissues and applied the scores to two longitudinal cohort studies of AD. The PRS model that was most predictive of AD diagnosis relative to cognitively unimpaired participants was the liver tissue score: n = 1,116; odds ratio (OR) (95% confidence interval [CI]) = 2.19 (1.70-2.82) per standard deviation (SD) increase in PRS; P = 1.46 × 10−9. After removing the APOE locus from the PRS models, the liver score was the only PRS to remain statistically significantly associated with AD diagnosis after multiple testing correction, although the effect was weaker: OR (95% CI) = 1.55 (1.19-2.02) per SD increase in PRS; P = 0.0012. In follow-up analysis, the liver PRS was statistically significantly associated with levels of amyloid (P = 3.53 × 10−6) and tau (P = 1.45 × 10−5) in the cerebrospinal fluid (CSF) (when the APOE locus was included) and nominally associated with CSF soluble TREM2 levels (P = 0.042) (when the APOE locus was excluded). These findings provide further evidence of the role of the liver-functional genome in AD and the benefits of incorporating functional annotation into genomic research.


2021 ◽  
Vol 17 (S5) ◽  
Author(s):  
Tingting Hou ◽  
Keke Liu ◽  
Cuicui Liu ◽  
Lin Cong ◽  
Yongxiang Wang ◽  
...  

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