Abstract P122: Plasma Circulating microRNAs as Potential Biomarkers in Chronic Kidney Disease
Bibliographic record
Abstract
Background: Chronic kidney disease (CKD) is a global health burden with a worldwide prevalence of 13.4% for stage 5 and 10.6% for stage 3-5. There is an epidemiological association between hypertension (HTN) and CKD. The prevalence of high blood pressure (BP) has been reported to be over 85% in stage 3 and over 90% in stage 4-5 CKD patients. Circulating cell-free small non-coding RNAs called microRNA (miRNA) have been shown to associate with different pathologies including cancer and cardiovascular disease, and accordingly possesses potential to serve as biomarkers with clinical application. We aimed to identify differentially expressed (DE) miRNAs that may be related to CKD. Methods and Results: Normotensive, HTN (systolic BP > 135 mmHg or diastolic BP of 85-115 mmHg with BPtru) and CKD (estimated glomerular filtration rate (eGFR) < 60mL/min/m 2 ) subjects (n=15-16 per group) were studied. Platelet-free plasma was isolated by a 2-step centrifugation (1000xg followed by 10,000xg) from 6 ml total blood. Plasma miRNAs were extracted using the QIAamp Circulating Nucleic Acid Kit. The quantity and quality of RNA were assessed using an Agilent 2100 Bioanalyzer. cDNA libraries were prepared using the TruSeq Small RNA Library Prep Kit, and sequenced with the HiSeq 2500 platform. FastQC was used for quality control. Sequences were mapped by STAR to the hg38 genome and annotated by miRDeep2. DE miRNAs were identified using EdgeR, which found 6 up-regulated and 3 down-regulated miRNAs uniquely associated with the HTN group, 2 up-regulated and 12 down-regulated miRNAs uniquely associated with the CKD group and 3 down-regulated miRNAs in both groups ( P <0.01 & q<0.1). Two down-regulated miRNAs in the HTN group, miR-26a-5p (r=-0.33, P <0.05) and miR-151a-5p (r=-0.33, P <0.05), were correlated with SBP. One up-regulated miRNA in CKD group, let-7g-5p (r=0.31, P <0.05), was correlated with eGFR. Conclusions and Perspectives: DE platelet-free plasma miRNAs were identified in HTN and CKD patients. Some miRNAs may have the potential to serve as biomarkers in CKD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".