Plasma Cell-Free RNA as Noninvasive Biomarker for Parkinson's Disease

Abstract

Parkinson disease (PD) is the most common neurodegenerative disorder, after Alzheimer disease (AD). Many attempts have been made to find a good biomarker, including alpha-synuclein protein levels in the cerebrospinal fluid (CSF). Cellfree nucleic acids-based diagnostic tests have revolutionized prenatal screening. They have also been investigated in cancer and fetal development among other traits, including neurodegenerative diseases. We have successfully developed a preliminary predictive model for AD using cell-free plasma RNA sequencing (cfRNASeq) and machine learning techniques. We used an exploratory dataset (10 AD cases and 10 controls) to train a predictive model.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2022
Accession Number
AD1199727

Entities

People

  • Laura Ibanez

Organizations

  • Washington University in St. Louis

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Alzheimer Disease
  • Biomedical Research
  • Data Analysis
  • Data Mining
  • Dementia
  • Diseases
  • Genetics
  • Machine Learning
  • Medical Personnel
  • Movement Disorders
  • Neural Networks
  • Neurodegeneration
  • Neurodegenerative Diseases
  • Nucleic Acids
  • Parkinson'S Disease
  • Predictive Modeling
  • Ribonucleic Acids

Fields of Study

  • Biology

Readers

  • Analytical Chemistry
  • Neurodegenerative Parkinson's Disease and Rickettsial Disease handbook, including the data level of dopamine, BC, neurons, and PD.
  • Oncology

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks
  • Biotechnology