Prediction of fast decline in amyloid positive mild cognitive impairment patients using multimodal biomarkers

Hyemin Jang, Jongyun Park, Sookyoung Woo, Seonwoo Kim, Hee Jin Kim, D. L. Na, Samuel N. Lockhart, Yeshin Kim, Ko Woon Kim, Soo Hyun Cho, Seung Joo Kim, Jun Kyung Seong, Sang Won Seo

Research output: Contribution to journalArticle

Abstract

It may be possible to classify patients with Aβ positive (+) mild cognitive impairment (MCI) into fast and slow decliners according to their biomarker status. In this study, we aimed to develop a risk prediction model to predict fast decline in the Aβ+ MCI population using multimodal biomarkers. We included 186 Aβ+ MCI patients who underwent florbetapir PET, brain MRI, cerebrospinal fluid (CSF) analyses, and FDG PET at baseline. We defined conversion to dementia within 3 years (= fast decline) as the outcome. The associations of potential covariates (MCI stage, APOE4 genotype, corrected hippocampal volume (HV), FDG PET SUVR, AV45 PET SUVR, CSF Aβ, total tau (t-tau), and phosphorylated tau (p-tau)) with the outcome were tested and nomograms were constructed using logistic regression models in the training dataset (n=124, n of fast decliners=52). The model was internally validated with the testing dataset (n=62, n of fast decliners=22). The multivariable analysis (including CSF t-tau) showed that MCI stage (late MCI vs. early MCI; OR 15.88, 95% CI 4.59, 54.88), APOE4 (OR 5.65, 95% CI 1.52, 20.98), corrected HV*1000 (OR 0.22, 95% CI 0.09, 0.57), FDG SUVR*10 (OR 0.43, 95% CI 0.27, 0.71), and loge CSF t-tau (OR 6.20, 95% CI 1.48, 25.96) were associated with being fast decliners. In the second model including CSF p-tau instead of t-tau, the above associations remained the same, with a significant association between loge CSF p-tau (OR 4.53, 95% CI 1.26, 16.31) and fast decline. The constructed nomograms showed excellent predictive performance (90%) on validation with the testing dataset. Among Aβ+ MCI patients, our findings suggested that multimodal AD biomarkers are significantly associated with being classified as fast decliners. A nomogram incorporating these biomarkers might be useful in early treatment decisions or stratified enrollment of this population into clinical trials.

Original languageEnglish
Article number101941
JournalNeuroImage: Clinical
Volume24
DOIs
Publication statusPublished - 2019 Jan 1

Fingerprint

Amyloid
Biomarkers
Cerebrospinal Fluid
Nomograms
Pets
Logistic Models
Cognitive Dysfunction
Population
Dementia
Genotype
Clinical Trials
Brain
Datasets

Keywords

  • Alzheimer's disease
  • Amyloid
  • Conversion to dementia
  • Mild cognitive impairment
  • Multimodal biomarkers
  • Nomogram

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Neurology
  • Clinical Neurology
  • Cognitive Neuroscience

Cite this

Prediction of fast decline in amyloid positive mild cognitive impairment patients using multimodal biomarkers. / Jang, Hyemin; Park, Jongyun; Woo, Sookyoung; Kim, Seonwoo; Kim, Hee Jin; Na, D. L.; Lockhart, Samuel N.; Kim, Yeshin; Kim, Ko Woon; Cho, Soo Hyun; Kim, Seung Joo; Seong, Jun Kyung; Seo, Sang Won.

In: NeuroImage: Clinical, Vol. 24, 101941, 01.01.2019.

Research output: Contribution to journalArticle

Jang, H, Park, J, Woo, S, Kim, S, Kim, HJ, Na, DL, Lockhart, SN, Kim, Y, Kim, KW, Cho, SH, Kim, SJ, Seong, JK & Seo, SW 2019, 'Prediction of fast decline in amyloid positive mild cognitive impairment patients using multimodal biomarkers', NeuroImage: Clinical, vol. 24, 101941. https://doi.org/10.1016/j.nicl.2019.101941
Jang, Hyemin ; Park, Jongyun ; Woo, Sookyoung ; Kim, Seonwoo ; Kim, Hee Jin ; Na, D. L. ; Lockhart, Samuel N. ; Kim, Yeshin ; Kim, Ko Woon ; Cho, Soo Hyun ; Kim, Seung Joo ; Seong, Jun Kyung ; Seo, Sang Won. / Prediction of fast decline in amyloid positive mild cognitive impairment patients using multimodal biomarkers. In: NeuroImage: Clinical. 2019 ; Vol. 24.
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