Development of a rapid and simple Xeno Nucleic Acid (XNA) sensor-based microRNA detection platform for Parkinson’s disease diagnostics
6 affiliations
- 1XENOHELIX Co. Ltd
- 2Department of Neurology, Yonsei University College of Medicine
- 3Department of Systems Biology, Institute of Life Science and Biotechnology, Yonsei University
- 4Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine
- 5Department of Neurology, National Taiwan University Hospital
- 6Institute of Biotechnology, National Taiwan University
Abstract
Current biomarkers for Parkinson’s disease (PD) diagnosis, including imaging tracers, α-synuclein seeding assays, proteomic markers, and metabolomic signatures, are often limited by invasiveness, cost, scalability, or insufficient reproducibility. Circulating microRNAs (miRNAs) are attractive minimally invasive biomarkers because they are mechanistically linked to disease-associated pathways and remain stable in biofluids. However, the clinical translation of miRNA biomarkers has been hindered by multistep workflows and analytical variability arising from adapter ligation, reverse transcription, amplification drift, and cross-platform inconsistency in qRT-PCR, sequencing, and hybridization-based assays. To address these limitations, we developed XENO-Q, a rapid three-step platform that enables bias-minimized miRNA quantification through target-selective synthesis, in which only sensor-confirmed miRNAs are converted into amplifiable chimera products. XENO-Q enables linear quantification across several orders of magnitude with femtomolar sensitivity and high reproducibility while maintaining compatibility with qRT-PCR, ddPCR, and nanopore sequencing workflows. As a demonstration of clinical applicability, XENO-Q identified a two-marker circulating miRNA signature that accurately distinguished PD from other neurodegenerative conditions. These findings establish XENO-Q as a scalable and clinically translatable framework for next-generation miRNA diagnostics beyond Parkinson’s disease. Graphical abstract
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BibTeX
@article{byun2026development,
title = {{Development of a rapid and simple Xeno Nucleic Acid (XNA) sensor-based microRNA detection platform for Parkinson’s disease diagnostics}},
author = {Mi Young Byun and Moon Young Ryu and Seok Jong Chung and Bora Lee and Jong Ryeol Oh and Jin Kyu Woo and Jin Young Shin and Min Kyun Han and Oh Young Bang and Yun Joong Kim and Ming-Che Kuo and Hsiang-Hsuan Lin-Wang and Ruey-Meei Wu and Shau-Ping Lin and Seok Keun Cho and Phil Hyu Lee and Seong Wook Yang},
journal = {Journal of Nanobiotechnology},
year = {2026},
month = jun,
doi = {10.1186/s12951-026-04707-5},
url = {https://doi.org/10.1186/s12951-026-04707-5},
note = {CC BY},
}
RIS
TY - JOUR
TI - Development of a rapid and simple Xeno Nucleic Acid (XNA) sensor-based microRNA detection platform for Parkinson’s disease diagnostics
AU - Mi Young Byun
AU - Moon Young Ryu
AU - Seok Jong Chung
AU - Bora Lee
AU - Jong Ryeol Oh
AU - Jin Kyu Woo
AU - Jin Young Shin
AU - Min Kyun Han
AU - Oh Young Bang
AU - Yun Joong Kim
AU - Ming-Che Kuo
AU - Hsiang-Hsuan Lin-Wang
AU - Ruey-Meei Wu
AU - Shau-Ping Lin
AU - Seok Keun Cho
AU - Phil Hyu Lee
AU - Seong Wook Yang
PY - 2026
DA - 2026/06/01
JO - Journal of Nanobiotechnology
DO - 10.1186/s12951-026-04707-5
UR - https://doi.org/10.1186/s12951-026-04707-5
AB - Current biomarkers for Parkinson’s disease (PD) diagnosis, including imaging tracers, α-synuclein seeding assays, proteomic markers, and metabolomic signatures, are often limited by invasiveness, cost, scalability, or insufficient reproducibility. Circulating microRNAs (miRNAs) are attractive minimally invasive biomarkers because they are mechanistically linked to disease-associated pathways and remain stable in biofluids. However, the clinical translation of miRNA biomarkers has been hindered by multistep workflows and analytical variability arising from adapter ligation, reverse transcription, amplification drift, and cross-platform inconsistency in qRT-PCR, sequencing, and hybridization-based assays. To address these limitations, we developed XENO-Q, a rapid three-step platform that enables bias-minimized miRNA quantification through target-selective synthesis, in which only sensor-confirmed miRNAs are converted into amplifiable chimera products. XENO-Q enables linear quantification across several orders of magnitude with femtomolar sensitivity and high reproducibility while maintaining compatibility with qRT-PCR, ddPCR, and nanopore sequencing workflows. As a demonstration of clinical applicability, XENO-Q identified a two-marker circulating miRNA signature that accurately distinguished PD from other neurodegenerative conditions. These findings establish XENO-Q as a scalable and clinically translatable framework for next-generation miRNA diagnostics beyond Parkinson’s disease. Graphical abstract
SN - 1477-3155
ER -