Retinal alpha-synuclein accumulation correlates with retinal dysfunction and structural thinning in the A53T mouse model of Parkinson’s disease

Katie K.N. Tran, Vickie H.Y. Wong, Anh Hoang, David I. Finkelstein, Bang V. Bui, Christine T.O. Nguyen

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Abnormal alpha-synuclein (α-SYN) protein deposition has long been recognized as one of the pathological hallmarks of Parkinson’s disease’s (PD). This study considers the potential utility of PD retinal biomarkers by investigating retinal changes in a well characterized PD model of α-SYN overexpression and how these correspond to the presence of retinal α-SYN. Transgenic A53T homozygous (HOM) mice overexpressing human α-SYN and wildtype (WT) control littermates were assessed at 4, 6, and 14 months of age (male and female, n = 15–29 per group). In vivo retinal function (electroretinography, ERG) and structure (optical coherence tomography, OCT) were recorded, and retinal immunohistochemistry and western blot assays were performed to examine retinal α-SYN and tyrosine hydroxylase. Compared to WT controls, A53T mice exhibited reduced light-adapted (cone photoreceptor and bipolar cell amplitude, p < 0.0001) ERG responses and outer retinal thinning (outer plexiform layer, outer nuclear layer, p < 0.0001) which correlated with elevated levels of α-SYN. These retinal signatures provide a high throughput means to study α-SYN induced neurodegeneration and may be useful in vivo endpoints for PD drug discovery.

Original languageEnglish (US)
Article number1146979
JournalFrontiers in Neuroscience
Volume17
DOIs
StatePublished - 2023
Externally publishedYes

Keywords

  • A53T
  • Parkinson’s disease
  • alpha-synuclein
  • electroretinography
  • optical coherence tomography
  • retina

ASJC Scopus subject areas

  • General Neuroscience

Fingerprint

Dive into the research topics of 'Retinal alpha-synuclein accumulation correlates with retinal dysfunction and structural thinning in the A53T mouse model of Parkinson’s disease'. Together they form a unique fingerprint.

Cite this