Introduction Identification of blood-based metabolic changes might provide early and easy-to-obtain biomarkers. Methods We included 127 Alzheimer's disease (AD) patients and 121 control subjects with cerebrospinal fluid biomarker-confirmed diagnosis (cutoff tau/amyloid β peptide 42: 0.52). Mass spectrometry platforms determined the concentrations of 53 amine compounds, 22 organic acid compounds, 120 lipid compounds, and 40 oxidative stress compounds. Multiple signatures were assessed: differential expression (nested linear models), classification (logistic regression), and regulatory (network extraction). Results Twenty-six metabolites were differentially expressed. Metabolites improved the classification performance of clinical variables f...
<div><p>Accumulating evidence links numerous abnormalities in cerebral metabolism with the progressi...
Alzheimer's Disease (AD) currently affects more than 5 million Americans, with numbers expected to g...
Introduction: Machine learning (ML) may harbor the potential to capture the metabolic complexity in ...
Introduction Identification of blood-based metabolic changes might provide early and easy-to-obtain ...
INTRODUCTION: The Alzheimer's Disease Research Summits of 2012 and 2015 incorporated experts from ac...
BACKGROUND:The metabolic basis of Alzheimer disease (AD) is poorly understood, and the relationships...
A specific, sensitive and essentially non-invasive assay to diagnose and monitor Alzheimer's disease...
Alzheimer’s disease (AD) has proven remarkably refractory to proposed and approved therapies, none o...
Alzheimer's disease (AD) is determined by various pathophysiological mechanisms starting 10-25 years...
Accumulating evidence links numerous abnormalities in cerebral metabolism with the progression of Al...
We believe this is the first study to investigate associations between blood metabolites and neocort...
<div><p>Background</p><p>The metabolic basis of Alzheimer disease (AD) is poorly understood, and the...
An easily accessible and non-invasive biomarker for the early detection of Alzheimer's disease (AD) ...
Accumulating evidence links numerous abnormalities in cerebral metabolism with the progression of Al...
Alzheimer’s disease (AD) is the leading cause of dementia, but the pathogenetic factors are not yet ...
<div><p>Accumulating evidence links numerous abnormalities in cerebral metabolism with the progressi...
Alzheimer's Disease (AD) currently affects more than 5 million Americans, with numbers expected to g...
Introduction: Machine learning (ML) may harbor the potential to capture the metabolic complexity in ...
Introduction Identification of blood-based metabolic changes might provide early and easy-to-obtain ...
INTRODUCTION: The Alzheimer's Disease Research Summits of 2012 and 2015 incorporated experts from ac...
BACKGROUND:The metabolic basis of Alzheimer disease (AD) is poorly understood, and the relationships...
A specific, sensitive and essentially non-invasive assay to diagnose and monitor Alzheimer's disease...
Alzheimer’s disease (AD) has proven remarkably refractory to proposed and approved therapies, none o...
Alzheimer's disease (AD) is determined by various pathophysiological mechanisms starting 10-25 years...
Accumulating evidence links numerous abnormalities in cerebral metabolism with the progression of Al...
We believe this is the first study to investigate associations between blood metabolites and neocort...
<div><p>Background</p><p>The metabolic basis of Alzheimer disease (AD) is poorly understood, and the...
An easily accessible and non-invasive biomarker for the early detection of Alzheimer's disease (AD) ...
Accumulating evidence links numerous abnormalities in cerebral metabolism with the progression of Al...
Alzheimer’s disease (AD) is the leading cause of dementia, but the pathogenetic factors are not yet ...
<div><p>Accumulating evidence links numerous abnormalities in cerebral metabolism with the progressi...
Alzheimer's Disease (AD) currently affects more than 5 million Americans, with numbers expected to g...
Introduction: Machine learning (ML) may harbor the potential to capture the metabolic complexity in ...