A genetics‐based biomarker risk algorithm for predicting risk of Alzheimer's disease
Abstract
A straightforward, reproducible blood‐based test that predicts age‐dependent risk of Alzheimer's disease (AD) could be used as an enrichment tool for clinical development of therapies. This study evaluated the prognostic performance of a genetics‐based biomarker risk algorithm (GBRA) established on a combination of apolipoprotein E (APOE)/translocase of outer mitochondrial membrane 40 homolog (TOMM40) genotypes and age, then compare it to cerebrospinal fluid (CSF) biomarkers, neuroimaging, and neurocognitive tests using data from two independent AD cohorts.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jan 01, 2016
- Source ID
- 10.1016/j.trci.2015.12.002
Entities
People
- Allen D. Roses
- Ann M. Saunders
- Daniel K. Burns
- James R. Burke
- Kathleen A. Welsh‐bohmer
- Kathleen M. Hayden
- Michael W. Lutz
- Scott S. Sundseth
- The Alzheimer’s Disease Neuroimaging Initiative*
Organizations
- AbbVie
- BioClinica
- Biogen
- Canadian Institutes of Health Research
- Chiron Corporation
- Duke University
- Eli Lilly and Company
- GE HealthCare
- Laboratoires Servier
- Lundbeck
- National Institute of Biomedical Imaging and Bioengineering
- National Institute on Aging
- National Institutes of Health
- Norman Cousins Center for Psychoneuroimmunology
- Northern California Institute for Research and Education
- Pfizer
- Roche (United States)
- Takeda Pharmaceutical Company
- United States Department of Defense
- Wake Forest School of Medicine