Longitudinal profiling of urinary extracellular vesicle RNA reveals physiological variability and stable reference genes in healthy individuals

Urinary extracellular vesicles (uEVs) have emerged as promising non-invasive molecular carriers for biomarker discovery, yet the physiological variability and tissue-associated characteristics of uEV RNA cargo in healthy individuals remain poorly defined. This knowledge gap limits the interpretation, normalization, and clinical translation of uEV-based transcriptomic studies. Here, we performed a longitudinal RNA-sequencing analysis of uEVs from 12 healthy donors, of whom six contributed complete longitudinal sample sets, to establish a molecular reference framework for physiological uEV transcriptomes. We systematically characterized inter- and intra-individual variation in uEV RNA cargo and found substantial transcriptomic heterogeneity despite relatively stable extracellular vesicle secretion levels over time. A conserved set of highly expressed genes was significantly enriched in ribosomal function and oxidative phosphorylation, indicating their role in fundamental cellular maintenance. Importantly, we identified 12 protein-coding genes that showed consistently low expression variance both across individuals and within individuals over time. Cross-dataset analyses using independent external and pan-cancer datasets further supported their potential utility as candidate reference transcripts for uEV RNA studies. Computational tissue deconvolution inferred predominant kidney- and bladder-associated transcriptomic signatures, while cell-type enrichment analysis showed relatively high enrichment scores for smooth muscle cells and mesenchymal stem cells. Together, this study defines the physiological landscape of healthy uEV transcriptomes, delineates key sources of biological variation, and provides candidate reference transcripts and tissue-associated molecular profiles to support the standardization and translational application of uEV-based molecular biomarker research.

Authors

Institutions

Publication Details

Journal
Molecular Medicine
Published
2026-09-04
DOI
https://doi.org/10.1186/s10020-026-01633-y
Primary Topic
Extracellular vesicles in disease
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

Longitudinal profiling of urinary extracellular vesicle RNA reveals physiological variability and stable reference genes in healthy individuals

Xiaochun Shu, Jiaoyuan Li, Qiankun Wang, Xiong Wang et al.
Molecular Medicine
Extracellular vesicles in disease
article

Longitudinal profiling of urinary extracellular vesicle RNA reveals physiological variability and stable reference genes in healthy individuals

Xiaochun Shu, Jiaoyuan Li, Qiankun Wang, Xiong Wang, Yi Wang, Lingyan Deng, Tongxin Yin, Huihao Ren, Hui Hu, Liming Cheng, Xu Wang, Xiao Xiao, Yuting Feng, Weiyun Zhang
article en

Abstract

Urinary extracellular vesicles (uEVs) have emerged as promising non-invasive molecular carriers for biomarker discovery, yet the physiological variability and tissue-associated characteristics of uEV RNA cargo in healthy individuals remain poorly defined. This knowledge gap limits the interpretation, normalization, and clinical translation of uEV-based transcriptomic studies. Here, we performed a longitudinal RNA-sequencing analysis of uEVs from 12 healthy donors, of whom six contributed complete longitudinal sample sets, to establish a molecular reference framework for physiological uEV transcriptomes. We systematically characterized inter- and intra-individual variation in uEV RNA cargo and found substantial transcriptomic heterogeneity despite relatively stable extracellular vesicle secretion levels over time. A conserved set of highly expressed genes was significantly enriched in ribosomal function and oxidative phosphorylation, indicating their role in fundamental cellular maintenance. Importantly, we identified 12 protein-coding genes that showed consistently low expression variance both across individuals and within individuals over time. Cross-dataset analyses using independent external and pan-cancer datasets further supported their potential utility as candidate reference transcripts for uEV RNA studies. Computational tissue deconvolution inferred predominant kidney- and bladder-associated transcriptomic signatures, while cell-type enrichment analysis showed relatively high enrichment scores for smooth muscle cells and mesenchymal stem cells. Together, this study defines the physiological landscape of healthy uEV transcriptomes, delineates key sources of biological variation, and provides candidate reference transcripts and tissue-associated molecular profiles to support the standardization and translational application of uEV-based molecular biomarker research.

Molecular Medicine
Renji Hospital (CN), Shanghai Cancer Institute (CN), State Key Laboratory of Oncogene and Related Genes (CN), Tongji Hospital (CN), Huazhong University of Science and Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 18%
Extracellular vesicles in disease
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.