Open AccessTaming the Huntington’s Disease Proteome: What Have We Learned?
Author(s) -
Connor Seeley,
Kimberly B. Kegel-Gleason
Publication year - 2021
Publication title -
journal of huntington's disease
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.081
H-Index - 24
eISSN - 1879-6400
pISSN - 1879-6397
DOI - 10.3233/jhd-200465
Subject(s) - huntingtin , proteome , computational biology , identification (biology) , huntington's disease , proteomics , data science , perspective (graphical) , computer science , disease , field (mathematics) , bioinformatics , biology , neuroscience , medicine , artificial intelligence , genetics , pathology , botany , mathematics , gene , pure mathematics
Mass spectrometry (MS) is a physical technique used to identify specific chemicals and molecules by precise analysis of their mass and charge; this technology has been adapted for biological sciences applications. Investigators have used MS to identify differential expressions of proteins in Huntington’s disease (HD), to discover Huntingtin (HTT) interacting proteins and to analyze HTT proteoforms. Using systems biology and computational approaches, data from MS screens have been leveraged to find differentially expressed pathways. This review summarizes the data from most of the MS studies done in the HD field in the last 20 years and compares it to the protein data reported before the use of MS technology. The MS results validate early findings in the field such as differential expression of PDE10a and DARPP-32 and identify new changes. We offer a perspective on the MS approach in HD, particularly for identification of disease pathways, the challenges in interpreting data across different studies, and its application to protein studies moving forward.