Five-year biomarker progression variability for Alzheimer's disease dementia prediction: Can a complex instrumental activities of daily living marker fill in the gaps?

Ioannis Tarnanas; Anthoula Tsolaki; Mark Wiederhold; Brenda Wiederhold; Magda Tsolaki

doi:10.1016/j.dadm.2015.10.005

Five-year biomarker progression variability for Alzheimer's disease dementia prediction: Can a complex instrumental activities of daily living marker fill in the gaps?

Alzheimers Dement (Amst). 2015 Nov 14;1(4):521-32. doi: 10.1016/j.dadm.2015.10.005. eCollection 2015 Dec.

Authors

Ioannis Tarnanas¹, Anthoula Tsolaki², Mark Wiederhold³, Brenda Wiederhold⁴, Magda Tsolaki²

Affiliations

¹ Health-IS Lab, Department of Management, Technology and Economics, ETH Zurich, Zurich, Switzerland; Piaget Research Foundation, Nürnberg, Germany.
² 3rd Department of Neurology, Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece.
³ Division of Cognitive and Restorative Neurology, Virtual Reality Medical Center, San Diego, CA, USA.
⁴ Virtual Reality Medical Institute, Clos Chapelle aux Champs, Brussels, Belgium.

Abstract

Introduction: Biomarker progressions explain higher variability in cognitive decline than baseline values alone. This study examines progressions of established biomarkers along with a novel marker in a longitudinal cognitive decline.

Methods: A total of 215 subjects were used with a diagnosis of normal, mild cognitive impairment (MCI) or Alzheimer's disease (AD) at baseline. We calculated standardized biomarker progression rates and used them as predictors of outcome within 5 years.

Results: Early cognitive declines were more strongly explained by fluorodeoxyglucose-positron emission tomography, precuneus and medial temporal cortical thickness, and the complex instrumental activities of daily living (iADL) marker progressions. Using Cox proportional hazards model, we found that these progressions were a significant risk factor for conversion from both MCI to AD (adjusted hazard ratio 1.45; 95% confidence interval 1.20-1.93; P = 1.23 × 10(-5)) and cognitively normal to MCI (adjusted hazard ratio 1.76; 95% confidence interval 1.32-2.34; P = 1.55 × 10(-5)).

Discussion: Compared with standard biological biomarkers, complex functional iADL markers could also provide predictive information for cognitive decline during the presymptomatic stage. This has important implications for clinical trials focusing on prevention in asymptomatic individuals.

Keywords: Alzheimer's disease; Biomarker; Biomarker progressions; Cognitive declines; Computerized cognitive assessment; Diagnostics; Early detection; MCI; MRI; PET; Rate of progression.