Capturing the Kidney Transcriptome by Urinary Extracellular Vesicles—From Pre-Analytical Obstacles to Biomarker Research

Author:

Barreiro Karina12,Dwivedi Om Prakash1,Rannikko Antti34,Holthöfer Harry15,Tuomi Tiinamaija1678,Groop Per-Henrik791011,Puhka Maija12ORCID

Affiliation:

1. Institute for Molecular Medicine Finland FIMM, HiLIFE, University of Helsinki, 00290 Helsinki, Finland

2. Institute for Molecular Medicine Finland FIMM, EV and HiPREP Core, University of Helsinki, 00290 Helsinki, Finland

3. Research Program in Systems Oncology, Faculty of Medicine, University of Helsinki, 00290 Helsinki, Finland

4. Department of Urology, University of Helsinki, Helsinki University Hospital, 00290 Helsinki, Finland

5. III Department of Medicine, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany

6. Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, 214 28 Malmö, Sweden

7. Folkhälsan Institute of Genetics, Folkhälsan Research Center, 00290 Helsinki, Finland

8. Endocrinology, Abdominal Centre, Helsinki University Hospital, 00029 Helsinki, Finland

9. Department of Nephrology, University of Helsinki, Helsinki University Hospital, 00290 Helsinki, Finland

10. Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, 00290 Helsinki, Finland

11. Department of Diabetes, Central Clinical School, Monash University, Melbourne, VIC 3800, Australia

Abstract

Urinary extracellular vesicles (uEV) hold non-invasive RNA biomarkers for genitourinary tract diseases. However, missing knowledge about reference genes and effects of preanalytical choices hinder biomarker studies. We aimed to assess how preanalytical variables (urine storage temperature, isolation workflow) affect diabetic kidney disease (DKD)—linked miRNAs or kidney—linked miRNAs and mRNAs (kidney-RNAs) in uEV isolates and to discover stable reference mRNAs across diverse uEV datasets. We studied nine raw and normalized sequencing datasets including healthy controls and individuals with prostate cancer or type 1 diabetes with or without albuminuria. We focused on kidney-RNAs reviewing literature for DKD-linked miRNAs from kidney tissue, cell culture and uEV/urine experiments. RNAs were analyzed by expression heatmaps, hierarchical clustering and selecting stable mRNAs with normalized counts (>200) and minimal coefficient of variation. Kidney-RNAs were decreased after urine storage at −20 °C vs. −80 °C. Isolation workflows captured kidney-RNAs with different efficiencies. Ultracentrifugation captured DKD -linked miRNAs that separated healthy and diabetic macroalbuminuria groups. Eleven mRNAs were stably expressed across the datasets. Hence, pre-analytical choices had variable effects on kidney-RNAs—analyzing kidney-RNAs complemented global correlation, which could fade differences in some relevant RNAs. Replicating prior DKD-marker results and discovery of candidate reference mRNAs encourages further uEV biomarker studies.

Funder

Innovative Medicines Initiative 2 Joint Undertaking

European Union’s Horizon 2020 research and innovation programme and EFPIA and JDRF

University of Helsinki

Publisher

MDPI AG

Subject

Genetics (clinical),Genetics

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