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Mining for Protein Aberrations in Parkinson’s Disease Using Large-Scale Protein Databases

Study Rationale: Deficient clearance of misfolded alpha-synuclein aggregates contributes to the pathology of Parkinson’s disease (PD). But broader disturbances in proteostasis—the balanced production, folding, and removal of cellular proteins—could also be taking place. Cells under stress may make mistakes when synthesizing proteins, incorporating incorrect amino acids or producing proteins that are longer or shorter than they should be. The resulting aberrant proteins can remain undetected by standard analytical methods, in which algorithms search sample databases only to determine whether proteins are present or absent, not whether they deviate from the expected sequence.

Hypothesis: We hypothesize that anomalous and aberrant proteins in people with PD await discovery. This untapped trove of protein forms will provide a signature of the changes in proteostasis associated with PD.

Study Design: In this project, we will apply new methods to analyse the rich, existing proteome data sets from blood cells, blood plasma and cerebrospinal fluid collected from people with PD. Using newly generated databases that contain recognition sequences derived from the genetic data of people with PD, we will catalogue the anomalous proteins that result from amino acid substitutions, the use of alternative start sites during protein production and atypical protein modifications.

Impact on Diagnosis/Treatment of Parkinson’s Disease: Obtaining the signatures of protein aberrancies may be useful in diagnosing PD and screening individuals for clinical trials. Because this study also includes data from people with other movement disorders, we may find a signature that will distinguish these symptomatically overlapping groups, potentially facilitating more rapid and accurate diagnoses.

Next Steps for Development: If successful, the results of this study could be implemented immediately in a clinical trial setting, because the signatures will be detectable directly via standard methods such as mass spectrometry without the need for antibody development.

Trial Phase: The signatures would be useful in all phases of clinical trials.


Researchers

  • Eleanor Therese Coffey, PhD

    Turku Finland


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