Xuemei Zhao

Title : A machine learning approach to identify a circulating microRNA signature for Alzheimer disease

Abstract:

Accurate diagnosis of Alzheimer’s disease (AD) involving less invasive molecular procedures, and at reasonable cost is an unmet medical need.  From the Oxford Project to Investigate Memory and Ageing (OPTIMA) study, a cohort of serum samples was profiled by a multiplex microRNA (miRNA) reverse transcription quantitative PCR analysis.  Clinical diagnosis of a subset of AD and the controls was confirmed by post-mortem (PM) histologic examination of brain tissue.  In a machine learning approach, a 12-miRNA signature for AD identification was constructed.  Using a subset of AD and control subjects with PM confirmed diagnosis status, a separate 12-miRNA signature was constructed demonstrating improved accuracy.  The miRNA signature appears to be a promising blood test to diagnose AD.

Biography:

Xuemei is currently a Senior Principal Scientist in the Translational Molecular Biomarkers Department at Merck & Co., Inc. in Kenilworth, NJ.  She received her Ph.D. in Chemistry from Columbia University and performed her postdoctoral research at Cold Spring Harbor Laboratory.  Afterwards, Xuemei joined the Proteomics Department in Molecular Profiling at Merck in 2004.  She led the biochemistry group focusing on sample preparation for LC-MS based proteomics profiling for biomarker discovery and new target identification.  In 2012, Xuemei transitioned to clinical biomarker development.  Currently, she leads the immunoassay group to develop, validate, and deploy immunoassay-based biomarkers in all phases of clinical development and all therapeutic areas at Merck & Co., Inc.