scholarly journals Continuous and risk‐score‐based predictors of ATN Alzheimer's disease status among cognitively healthy individuals: Findings from the EPAD‐LCS study

2020 ◽  
Vol 16 (S5) ◽  
Author(s):  
Catherine M Calvin ◽  
Casper de Boer ◽  
Vanessa Raymont ◽  
John Gallacher ◽  
Ivan G Koychev ◽  
...  
2015 ◽  
Vol 11 (7S_Part_19) ◽  
pp. P872-P872 ◽  
Author(s):  
Valentina Escott-Price ◽  
Rebecca Sims ◽  
Denise Harold ◽  
Maria Vronskaya ◽  
Peter Holmans ◽  
...  

Author(s):  
Ruocheng Dong ◽  
Burcu F. Darst ◽  
Yuetiva Deming ◽  
Yue Ma ◽  
Qiongshi Lu ◽  
...  

2021 ◽  
Vol 18 ◽  
Author(s):  
Yuanyuan Wei ◽  
Nianwei Huang ◽  
Yong Liu ◽  
Xi Zhang ◽  
Silun Wang ◽  
...  

Background: Early detection of Alzheimer’s disease (AD) and its early stage, the mild cognitive impairment (MCI), has important scientific, clinical and social significance. Magnetic resonance imaging (MRI) based statistical shape analysis provides an opportunity to detect regional structural abnormalities of brain structures caused by AD and MCI. Objective: In this work, we aimed to employ a well-established statistical shape analysis pipeline, in the framework of large deformation diffeomorphic metric mapping, to identify and quantify the regional shape abnormalities of the bilateral hippocampus and amygdala at different prodromal stages of AD, using three Chinese MRI datasets collected from different domestic hospitals. Methods: We analyzed the region-specific shape abnormalities at different stages of the neuropathology of AD by comparing the localized shape characteristics of the bilateral hippocampi and amygdalas between healthy controls and two disease groups (MCI and AD). In addition to group comparison analyses, we also investigated the association between the shape characteristics and the Mini Mental State Examination (MMSE) of each structure of interest in the disease group (MCI and AD combined) as well as the discriminative power of different morphometric biomarkers. Results: We found the strongest disease pathology (regional atrophy) at the subiculum and CA1 subregions of the hippocampus and the basolateral, basomedial as well as centromedial subregions of the amygdala. Furthermore, the shape characteristics of the hippocampal and amygdalar subregions exhibiting the strongest AD related atrophy were found to have the most significant positive associations with the MMSE. Employing the shape deformation marker of the hippocampus or the amygdala for automated MCI or AD detection yielded a significant accuracy boost over the corresponding volume measurement. Conclusion: Our results suggested that the amygdalar and hippocampal morphometrics, especially those of shape morphometrics, can be used as auxiliary indicators for monitoring the disease status of an AD patient.


2017 ◽  
Vol 114 (38) ◽  
pp. E7929-E7938 ◽  
Author(s):  
Maria Paraskevaidi ◽  
Camilo L. M. Morais ◽  
Kássio M. G. Lima ◽  
Julie S. Snowden ◽  
Jennifer A. Saxon ◽  
...  

The progressive aging of the world’s population makes a higher prevalence of neurodegenerative diseases inevitable. The necessity for an accurate, but at the same time, inexpensive and minimally invasive, diagnostic test is urgently required, not only to confirm the presence of the disease but also to discriminate between different types of dementia to provide the appropriate management and treatment. In this study, attenuated total reflection FTIR (ATR-FTIR) spectroscopy combined with chemometric techniques were used to analyze blood plasma samples from our cohort. Blood samples are easily collected by conventional venepuncture, permitting repeated measurements from the same individuals to monitor their progression throughout the years or evaluate any tested drugs. We included 549 individuals: 347 with various neurodegenerative diseases and 202 age-matched healthy individuals. Alzheimer’s disease (AD;n= 164) was identified with 70% sensitivity and specificity, which after the incorporation of apolipoprotein ε4 genotype (APOEε4) information, increased to 86% when individuals carried one or two alleles of ε4, and to 72% sensitivity and 77% specificity when individuals did not carry ε4 alleles. Early AD cases (n= 14) were identified with 80% sensitivity and 74% specificity. Segregation of AD from dementia with Lewy bodies (DLB;n= 34) was achieved with 90% sensitivity and specificity. Other neurodegenerative diseases, such as frontotemporal dementia (FTD;n= 30), Parkinson’s disease (PD;n= 32), and progressive supranuclear palsy (PSP;n= 31), were included in our cohort for diagnostic purposes. Our method allows for both rapid and robust diagnosis of neurodegeneration and segregation between different dementias.


2019 ◽  
Vol 10 ◽  
Author(s):  
Tao Wang ◽  
Zhifa Han ◽  
Yu Yang ◽  
Rui Tian ◽  
Wenyang Zhou ◽  
...  

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 ◽  
...  

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