NIH, National Cancer Institute, Division of Cancer Treatment and Diagnosis (DCTD) NIH - National Institutes of Health National Cancer Institute DCTD - Division of Cancer Treatment and Diagnosis

Comparison of Data Normalization Strategies for Array-Based MicroRNA Profiling Experiments and Identification and Validation of Circulating MicroRNAs as Endogenous Controls in Hypertension.

Author(s): Chekka LMS, Langaee T, Johnson JA

Publication: Front Genet, 2022, Vol. 13, Page 836636

PubMed ID: 35432462 PubMed Review Paper? No

Purpose of Paper

The purpose of this paper was to compare different normalization strategies for plasma microRNA (miRNA, miR) expression profiles using real-time PCR arrays.

Conclusion of Paper

Of the 754 miRNAs profiled, 346 were detected in plasma from one or more patients, but only 81 were detected in ≥50% of specimens and thus included in the analysis.  Each of the five normalization strategies evaluated reduced data variability of the 81 miRNAs analyzed; the largest decreases observed were after quantile normalization, followed by global mean normalization. Variability of the 13 miRNAs expressed in specimens from all patients was lowest when data was normalized to the mean of the same 13 miRNAs (MCR) followed by quantile normalization.  miR-223-3p, miR-19b, miR-126-5p, and miR-106a were identified as the most stable using RefFinder and when data was normalized to the global mean. However, when validated using a second cohort of specimens from African Americans, miR-19b and miR-106a were not detected in all plasma samples.  

Studies

  1. Study Purpose

    The purpose of this study was to compare different normalization strategies for plasma miRNA expression profiles using real-time PCR arrays. This study used EDTA plasma from 36 European women with untreated hypertension that had been stored long-term at -80°C; further details of blood collection, processing and storage were not provided. Stable miRNA were validated using the plasma from 50 African Americans with hypertension (further details not provided). RNA was extracted from plasma using the MagMAX mirVana Total RNA Isolation Kit and reverse transcribed using the TaqMan reverse transcription kit and Megaplex Primer Pools A and B. cDNA was pre-amplified using TaqMan PreAmp Master Mix and Megaplex PreAmp Primer Pools A and B. Levels of 754 miRNA were quantified by real-time PCR using the TaqMan OpenArray Human MicroRNA Panel. miRNA that did not amplify in ≥50% of specimens were excluded from further analysis. A Cq value of 40 was assigned for miRNA that did not amplify. miRNA expression was normalized to: (1) the global mean, (2) the mean of expressed miRNA, omitting missing values (mean centering, unimputed), (3) the mean of the subset of miRNA expressed in all specimens (mean centering restricted, MCR), (4) Quantile, and (5) endogenous controls (miR-223-3p) identified using RefFinder.  

    Summary of Findings:

    Of the 754 miRNAs profiled, 346 were detected in specimens from one or more patients, but only 81 miRNAs were detected in ≥50% of specimens and thus included in further analysis.  Each of the five normalization strategies evaluated reduced the data variability of the 81 miRNAs analyzed with the largest decreases observed after quantile normalization followed by global mean normalization. Normalization using only the 13 miRNAs expressed in all specimens (MCR) performed similarly to normalization to miR-223. The variability of the 13 miRNAs expressed in all specimens was lowest when data was normalized by the MCR method, followed by quantile normalization.  miR-223-3p, miR-19b, miR-126-5p, and miR-106a exhibited the least variability after normalization to the global mean.  These four miRNAs were also identified as the most stable miRNAs using RefFinder based on the Delta CT, BestKeeper, Normfinder and geNorm results. However, when validated using a second cohort of specimens from African Americans, miR-19b and miR-106a were not detected in all samples.  miR-223-3p and miR-126-5p were identified as the most stable based miRNAs of those evaluated based on the Delta CT, BestKeeper, Normfinder and geNorm results in the validation cohort, and thus were chosen for subsequent use.

    Biospecimens
    Preservative Types
    • Frozen
    Diagnoses:
    • Hypertension
    Platform:
    AnalyteTechnology Platform
    RNA Real-time qRT-PCR
    RNA Low density array
    Pre-analytical Factors:
    ClassificationPre-analytical FactorValue(s)
    Low density array Specific Data handling Normalized to global mean
    Normalized to mean of expressed miRNA omitting missing values (mean centering unimputed)
    Normalized to the mean of subset of miRNA expressed in all specimens (mean centering restricted, MCR)
    Quantile normalized
    Normalized to endogenous controls (miR-223-3p) identified using Reffinder
    Preaquisition Patient race African American
    European

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