MicroRNA super-resolution imaging in blood for Alzheimer's disease

BMB Rep. 2023 Mar;56(2):190-195. doi: 10.5483/BMBRep.2022-0151.

Abstract

We propose a novel blood biomarker detection method that uses miRNA super-resolution imaging to enable the early diagnosis of Alzheimer's disease (AD). Here, we report a singlemolecule detection method for visualizing disease-specific miRNA in tissue from an AD mice model, and peripheral blood mononuclear cells (PBMCs) from AD patients. Using optimized Magnified Analysis of Proteome (MAPs), we confirmed that five miRNAs contribute to neurodegenerative disease in the brain hippocampi of 5XFAD and wild-type mice. We also assessed PBMCs isolated from the whole blood of AD patients and a healthy control group, and subsequently analyzed those samples using miRNA super-resolution imaging. We detected more miR-200a-3p expression in the cornu ammonis 1 and dentate gyrus regions of 3 month-old 5XFAD mice than in wild-type mice. Additionally, miRNA super-resolution imaging of blood provides AD diagnosis platform for studying miRNA regulation inside cells at the single molecule level. Our results present a potential liquid biopsy method that could improve the diagnosis of early stage AD and other diseases. [BMB Reports 2023; 56(3): 190-195].

Publication types

  • News

MeSH terms

  • Alzheimer Disease* / diagnostic imaging
  • Alzheimer Disease* / genetics
  • Animals
  • Hippocampus / diagnostic imaging
  • Hippocampus / metabolism
  • Leukocytes, Mononuclear / metabolism
  • Mice
  • MicroRNAs* / genetics
  • MicroRNAs* / metabolism
  • Neurodegenerative Diseases* / metabolism

Substances

  • MicroRNAs

Grants and funding

ACKNOWLEDGEMENTS This study was supported by a research grant from Gangnam Severance Hospital, Yonsei University College of Medicine. This study was supported by a faculty research grant from the Yonsei University College of Medicine for (6-2020-0109). This work was supported by the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare and Ministry of Science and ICT, Republic of Korea (grant number: HI17C1260 and HU20C0164). This research was supported by a National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (NRF-2020R1F1A1072307). This work was supported by the Basic Science Research Program through the NRF, funded by the Ministry of Education (NRF-2020R1A6A3A01097969).