Cognitive gene risk profile for the prediction of cognitive decline in presymptomatic Alzheimer’s disease

Document Type

Journal Article

Publication Title

Personalized Medicine in Psychiatry

School

School of Medical and Health Sciences

RAS ID

27302

Comments

Porter, T., Villemagne, V. L., Savage, G., Milicic, L., Ying Lim, Y., Maruff, P., . . . Laws, S. M. (2018). Cognitive gene risk profile for the prediction of cognitive decline in presymptomatic Alzheimer's disease. Personalized Medicine in Psychiatry, 7, 14-20. doi:10.1016/j.pmip.2018.03.001

Abstract

Introduction

In cognitively normal (CN) older adults, high levels of Aβ-amyloid are associated with significant decline in cognition, especially episodic memory. Several genes have previously been associated with cognition, including APOE, KIBRA, KLOTHO, BDNF, COMT, SPON1 and CSMD1. While some of this variation has been attributed to some of these genes individually, the combined effects of these genes on rates of cognitive decline, particularly in preclinical Alzheimer’s Disease remain largely unknown.

Methods

To elucidate if risk alleles within these genes can be suitably combined to predict cognitive decline 127 CN older adults with elevated PET-ascertained Aβ-amyloid were included in a decision tree analysis to define a “Cognitive Gene Risk Profile” for decline in a verbal episodic memory composite.

Results

The episodic memory-derived Cognitive Gene Risk Profile defined four groups: APOE ε4+ Risk, ε4+ Resilient, ε4− Risk, ε4− Resilient, with the ε4+ Risk group declining significantly faster than all other groups (ε4+ Resilient, p = 0.0008; ε4− Risk, p = 0.025; ε4− Resilient, p = 0.0006). The ε4+ Risk group also declined significantly faster than all other groups on Global, Clinical Progression and Pre-Alzheimer’s cognitive composites.

Discussion

The defined Cognitive Gene Risk Profile has potential utility in participant selection/stratification for preclinical AD trials that incorporate Aβ-amyloid and where decline in cognition is essential to determine therapeutic effectiveness.

DOI

10.1016/j.pmip.2018.03.001

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