Callosal thickness profiles for prognosticating conversion from mild cognitive impairment to Alzheimer's disease: A classification approach

Plasma Transthyretin as a Predictor of Amnestic Mild Cognitive Impairment Conversion to Dementia

Amnestic mild cognitive impairment (MCI) is a prodromal stage of dementia, with a higher incidence of these patients progressing to Alzheimer’s disease (AD) than normal aging people. A biomarker for the early detection and prediction for this progression is important. We recruited MCI subjects in three teaching hospitals and conducted longitudinal follow-up for 5 years at one-year intervals. Cognitively healthy controls were recruited for comparisom at baseline. Plasma transthyretin (TTR) levels were measured by ELISA. Survival analysis with time to AD conversion as an outcome variable was calculated with the multivariable Cox proportional hazards models using TTR as a continuous variable with adjustment for other covariates and bootstrapping resampling analysis. In total, 184 MCI subjects and 40 sex- and age-matched controls were recruited at baseline. At baseline, MCI patients had higher TTR levels compared with the control group. During the longitudinal follow-ups, 135 MCI patients (73.4%) completed follow-up at least once. The TTR level was an independent predictor for MCI conversion to AD when using TTR as a continuous variable (p = 0.023, 95% CI 1.001–1.007). In addition, in MCI converters, the TTR level at the point when they converted to AD was significantly lower than that at baseline (328.6 ± 66.5 vs. 381.9 ± 77.6 ug/ml, p < 0.001). Our study demonstrates the temporal relationship between the plasma TTR level and the conversion from MCI to AD.

Callosal thickness profiles for prognosticating conversion from mild cognitive impairment to Alzheimer's disease: A classification approach

INTRODUCTION

Alzheimer's disease (AD) is the most common form of dementia. Finding biomarkers to prognosticate transition from mild cognitive impairment (MCI) to AD is important to clinical medicine. Promising imaging biomarkers of AD conversion identified so far include atrophy of the cerebral cortex and subcortical gray matter nuclei.

METHODS

This study introduces thickness and bending angle of the corpus callosum as a putative white matter marker of MCI to AD conversion. The corpus callosum is computationally less demanding to segment automatically compared to more complicated structures and a subject can be processed in a few minutes. We aimed to demonstrate that callosal shape and thickness measures provide a simple, effective, and accurate prognostication tool in ADNI dataset. Using longitudinal datasets, we classified MCI subjects based on conversion to AD assessed via cognitive testing. We evaluated the classification accuracy of callosal shape features in comparison with the existing "gold standard" cortical thickness and subcortical gray matter volume measures.

RESULTS

The callosal thickness measures were less accurate in classifying conversion status by cognitive scores compared to gray matter measures for AD.

CONCLUSIONS

While this paper presented a negative result, this method may be more suitable for a disease of the white matter.