Evidence map›Paper›PMID 30430409›Full record

ArticleMolecular neurobiology2019

Analytics of Cerebrospinal Fluid MicroRNA Quantitative PCR Studies.

Theresa A Lusardi, Jack T Wiedrick, Molly Malone, Jay I Phillips, Ursula S Sandau, Babett Lind, Joseph F Quinn, Jodi A Lapidus, Julie A Saugstad

Open access · greenAbstract read
In one paragraph

Article in Molecular neurobiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.1field-weighted citation impact, top 56% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 1 institution in 1 country.

Theresa A LusardiCancer Early Detection Advanced Research Center, Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA.
Jack T WiedrickBiostatistics & Design Program, Oregon Health & Science University, Portland, OR, USA.
Molly MaloneDepartment of Anesthesiology & Perioperative Medicine, Oregon Health & Science University, Portland, OR, USA.
Jay I PhillipsDepartment of Anesthesiology & Perioperative Medicine, Oregon Health & Science University, Portland, OR, USA.
Ursula S SandauDepartment of Anesthesiology & Perioperative Medicine, Oregon Health & Science University, Portland, OR, USA.
Babett LindDepartment of Neurology, Layton Aging and Alzheimer's Center, Oregon Health & Science University, Portland, OR, USA.
Joseph F QuinnDepartment of Neurology, Layton Aging and Alzheimer's Center, Oregon Health & Science University, Portland, OR, USA.
Jodi A LapidusBiostatistics & Design Program, Oregon Health & Science University, Portland, OR, USA.
Julie A SaugstadDepartment of Anesthesiology & Perioperative Medicine, Oregon Health & Science University, Portland, OR, USA. saugstad@ohsu.edu.ORCID http://orcid.org/0000-0002-2996-9611
Oregon Health & Science University · US

Funding

Oregon Clinical and Translational Research Institute - The National COVID Cohort Collaborative (N3C)UL1TR002369 · NCATS · OREGON HEALTH & SCIENCE UNIVERSITY · PI Cynthia D Morris, Christopher G. Slatore · 2017 to 2026
$78.4M
Oregon Clinical and Translational Research InstituteUL1TR000128 · NCATS · OREGON HEALTH & SCIENCE UNIVERSITY · PI ELLISON, DAVID H · 2012 to 2015
$28.7M
Outreach, Recruitment and Education CoreP30AG008017 · NIA · OREGON HEALTH & SCIENCE UNIVERSITY · PI KAYE, JEFFREY A · 1990 to 2019
$27.7M
Optimization and Normalization Studies for Individual CSF SamplesUH3TR000903 · NCATS · OREGON HEALTH & SCIENCE UNIVERSITY · PI QUINN, JOSEPH F, SAUGSTAD, JULIE ANNE · 2015 to 2016
$1.2M
Optimization and Normalization Studies for CSF as a BiomarkerUH2TR000903 · NCATS · OREGON HEALTH & SCIENCE UNIVERSITY · PI QUINN, JOSEPH F, SAUGSTAD, JULIE ANNE · 2013 to 2014
$793k
NCATS NIH HHS Oregon Clinical & Translational Research Institute UL1TR000128NCATS NIH HHS UH2 TR000903NCATS NIH HHS UH2/UH3TR000903NCATS NIH HHS UH3 TR000903NCATS NIH HHS UL1 TR000128NCATS NIH HHS UL1 TR002369NIA NIH HHS P30 AG008017NIA NIH HHS P30AG008017
6 · The paper itself

Abstract

MicroRNAs (miRNAs) are small non-coding RNAs that regulate post-transcriptional gene expression. Recent studies have shown that human disease states correlate with measurable differences in the level of circulating miRNAs relative to healthy controls. Thus, there is great interest in developing clinical miRNA assays as diagnostic or prognostic biomarkers for diseases, and as surrogate measures for therapeutic outcomes. Our studies have focused on miRNAs in human cerebral spinal fluid (CSF) as biomarkers for central nervous system (CNS) diseases. Our objective here was to examine factors that may affect the outcome of quantitative PCR (qPCR) studies on CSF miRNAs, in order to guide planning and interpretation of future CSF miRNA TaqMan® low-density array (TLDA) studies. We obtained CSF from neurologically normal (control) donors and used TLDAs to measure miRNA expression. We examined sources of error in the TLDA outcomes due to (1) nonspecific amplification of products in total RNA, (2) variations in RNA isolations performed on different days, (3) miRNA primer probe efficiency, and (4) variations in individual TLDA cards. We also examined the utility of card-to-card TLDA corrections and use of an unchanged "reference standard" to remove batch processing effects in large-scale studies.

Indexed as

BiomarkersCentral Nervous System DiseasesCerebrospinal FluidHumansMicroRNAsReal-Time Polymerase Chain ReactionBiomarkersMicroRNAsAnalyticsCerebrospinal fluidmicroRNAQuantitative PCRTaqMan low-density array

Identifiers

PMID30430409
PMCPMC6527498
OpenAlexW2901421885

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.