Whole Genome Sequencing in Parkinson's disease

Abstract

The NIA aimed to generate deep genome sequence of 3050 Parkinsons disease (PD) cases and 700 matched controls and to aggregate data for control genomes. All genomes were to be joint called to harmonize data. These data would be used within NIA to identify and fine map PD linked risk loci. The cumulative genetic data was to be used to identify putative risk variants which could then be tested for biological consequences. The data was to be distributed and made available through NIH databases. These goals have been achieved. More than 5,000 PD genomes were sequenced, and harmonized with genomic data from other series, from control cohorts, and from other diseases. These data have been made available through the LONI website (for PPMI samples) and through the Accelerating Medicines Partnership PD portal (now ~10,000 genomes). These data have been used as a part of an effort to more than double the known risk loci for PD (90 loci) and to attribute biological consequences to these loci. In addition, this work has contributed to the increased precision of disease predictive modeling using machine learning.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2021
Accession Number
AD1138264

Entities

People

  • Andrew Singleton

Organizations

  • National Institute on Aging

Tags

Communities of Interest

  • Autonomy
  • C4I
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Brain
  • Cells
  • Chemistry
  • Genetics
  • Health Services
  • Information Science
  • Machine Learning
  • Medical Personnel
  • Neurodegeneration
  • Neurons
  • Parkinson'S Disease
  • Stem Cells

Fields of Study

  • Biology

Readers

  • Molecular Genetics
  • Neural Network Machine Learning.
  • Neurodegenerative Parkinson's Disease and Rickettsial Disease handbook, including the data level of dopamine, BC, neurons, and PD.

Technology Areas

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