Dataset Information

Effect of age, ethnicity, sex, cognitive status and APOE genotype on amyloid load and the threshold for amyloid positivity.

ABSTRACT: The threshold for amyloid positivity by visual assessment on PET has been validated by comparison to amyloid load measured histopathologically and biochemically at post mortem. As such, it is now feasible to use qualitative visual assessment of amyloid positivity as an in-vivo gold standard to determine those factors which can modify the quantitative threshold for amyloid positivity. We calculated quantitative amyloid load, measured as Standardized Uptake Value Ratios (SUVRs) using [18-F]florbetaben PET scans, for 159 Hispanic and non-Hispanic participants, who had been classified clinically as Cognitively Normal (CN), Mild Cognitive Impairment (MCI) or Dementia (DEM). PET scans were visually rated as amyloid positive (A+) or negative (A-), and these judgments were used as the gold standard with which to determine (using ROC analyses) the SUVR threshold for amyloid positivity considering factors such as age, ethnicity (Hispanic versus non-Hispanic), gender, cognitive status, and apolipoprotein E ?4 carrier status. Visually rated scans were A+ for 11% of CN, 39.0% of MCI and 70% of DEM participants. The optimal SUVR threshold for A+ among all participants was 1.42 (sensitivity?=?94%; specificity?=?92.5%), but this quantitative threshold was higher among E4 carriers (SUVR?=?1.52) than non-carriers (SUVR?=?1.31). While mean SUVRs did not differ between Hispanic and non-Hispanic participants;, a statistically significant interaction term indicated that the effect of E4 carrier status on amyloid load was greater among non-Hispanics than Hispanics. Visual assessment, as the gold standard for A+, facilitates determination of the effects of various factors on quantitative thresholds for amyloid positivity. A continuous relationship was found between amyloid load and global cognitive scores, suggesting that any calculated threshold for the whole group, or a subgroup, is artefactual and that the lowest calculated threshold may be optimal for the purposes of early diagnosis and intervention.

SUBMITTER: Duara R

PROVIDER: S-EPMC6447735 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Effect of age, ethnicity, sex, cognitive status and APOE genotype on amyloid load and the threshold for amyloid positivity.

Duara R R Loewenstein D A DA Lizarraga G G Adjouadi M M Barker W W WW Greig-Custo M T MT Rosselli M M Penate A A Shea Y F YF Behar R R Ollarves A A Robayo C C Hanson K K Marsiske M M Burke S S Ertekin-Taner N N Vaillancourt D D De Santi S S Golde T T St DeKosky D

NeuroImage. Clinical 20190327

The threshold for amyloid positivity by visual assessment on PET has been validated by comparison to amyloid load measured histopathologically and biochemically at post mortem. As such, it is now feasible to use qualitative visual assessment of amyloid positivity as an in-vivo gold standard to determine those factors which can modify the quantitative threshold for amyloid positivity. We calculated quantitative amyloid load, measured as Standardized Uptake Value Ratios (SUVRs) using [18-F]florbet ...[more]

PMID: 30991618

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Project description:BackgroundStage 1 of the National Institute on Aging-Alzheimer's Association's proposed Alzheimer's disease continuum is defined as amyloid-β (Aβ) positive but cognitively normal. Identifying at-risk individuals before Aβ reaches pathological levels could have great benefits for early intervention. Although Aβ levels become abnormal long before severe cognitive impairments appear, increasing evidence suggests that subtle cognitive changes may begin early, potentially before Aβ surpasses the threshold for abnormality. We examined whether baseline cognitive performance would predict progression from normal to abnormal levels of Aβ.MethodsWe examined the association of baseline cognitive composites (Preclinical Alzheimer Cognitive Composite, Alzheimer's Disease Neuroimaging Initiative (ADNI) memory factor composite) with progression to Aβ positivity in 292 nondemented, Aβ-negative ADNI participants. Additional analyses included continuous cerebrospinal fluid biomarker levels to examine the effects of subthreshold pathology.ResultsForty participants progressed to Aβ positivity during follow-up. Poorer baseline performance on both cognitive measures was significantly associated with increased odds of progression. More abnormal levels of baseline cerebrospinal fluid phosphorylated tau and subthreshold Aβ were associated with increased odds of progression to Aβ positivity. Nevertheless, baseline ADNI memory factor composite performance predicted progression even after controlling for baseline biomarker levels and APOE genotype (Preclinical Alzheimer Cognitive Composite was trend level). Survival analyses were largely consistent: controlling for baseline biomarker levels, baseline Preclinical Alzheimer Cognitive Composite still significantly predicted progression time to Aβ positivity (ADNI memory factor composite was trend level).ConclusionsThe possibility of intervening before Aβ reaches pathological levels is of obvious benefit. Low-cost, noninvasive cognitive measures can be informative for determining who is likely to progress to Aβ positivity, even after accounting for baseline subthreshold biomarker levels.

Project description:The importance of early interventions in Alzheimer's disease (AD) emphasizes the need to accurately and efficiently identify at-risk individuals. Although many dementia prediction models have been developed, there are fewer studies focusing on detection of brain pathology. We developed a model for identification of amyloid-PET positivity using data on demographics, vascular factors, cognition, APOE genotype, and structural MRI, including regional brain volumes, cortical thickness and a visual medial temporal lobe atrophy (MTA) rating. We also analyzed the relative importance of different factors when added to the overall model. The model used baseline data from the Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) exploratory PET sub-study. Participants were at risk for dementia, but without dementia or cognitive impairment. Their mean age was 71 years. Participants underwent a brain 3T MRI and PiB-PET imaging. PiB images were visually determined as positive or negative. Cognition was measured using a modified version of the Neuropsychological Test Battery. Body mass index (BMI) and hypertension were used as cardiovascular risk factors in the model. Demographic factors included age, gender and years of education. The model was built using the Disease State Index (DSI) machine learning algorithm. Of the 48 participants, 20 (42%) were rated as A? positive. Compared with the A? negative group, the A? positive group had a higher proportion of APOE ?4 carriers (53 vs. 14%), lower executive functioning, lower brain volumes, and higher visual MTA rating. AUC [95% CI] for the complete model was 0.78 [0.65-0.91]. MRI was the most effective factor, especially brain volumes and visual MTA rating but not cortical thickness. APOE was nearly as effective as MRI in improving detection of amyloid positivity. The model with the best performance (AUC 0.82 [0.71-0.93]) was achieved by combining APOE and MRI. Our findings suggest that combining demographic data, vascular risk factors, cognitive performance, APOE genotype, and brain MRI measures can help identify A? positivity. Detecting amyloid positivity could reduce invasive and costly assessments during the screening process in clinical trials.

Dataset Information

Effect of age, ethnicity, sex, cognitive status and APOE genotype on amyloid load and the threshold for amyloid positivity.

Publications

Effect of age, ethnicity, sex, cognitive status and APOE genotype on amyloid load and the threshold for amyloid positivity.

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