Evidence map›Paper›PMID 29259803›Full record

ArticleObesity science & practice2017

Preliminary evidence supports circulating microRNAs as prognostic biomarkers for type 2 diabetes.

E Flowers, A M Kanaya, Y Fukuoka, I E Allen, B Cooper, B E Aouizerat

Abstract read
In one paragraph

Article in Obesity science & practice, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

21 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  17. MicroRNA-423 may regulate diabetic vasculopathy.Clinical and experimental medicine · 2019
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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

6 authors.

E FlowersDepartment of Physiological Nursing University of California San Francisco CA USA.ORCID 0000-0002-7054-7533
A M KanayaDepartment of Medicine University of California San Francisco CA USA.
Y FukuokaDepartment of Physiological Nursing University of California San Francisco CA USA.
I E AllenDepartment of Epidemiology and Biostatistics University of California San Francisco CA USA.
B CooperUniversity of California San Francisco CA USA.
B E AouizeratNew York University New York NY USA.

Funding

Clinical and Transtional Science InstituteKL2TR000143 · NCATS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GRANDIS, JENNIFER RUBIN · 2012 to 2015
$11.9M
Restorative Yoga for Therapy of the Metabolic Syndrome (RHYTHMS) studyR01AT004569 · NCCIH · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KANAYA, ALKA M. · 2009 to 2012
$2.1M
Applying Virtual Social Networking to Diabetes Prevention For Filipino AmericansR34DK102100 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI BENDER, MELINDA SARMIENTO, FUKUOKA, YOSHIMI · 2014 to 2015
$474k
NCATS NIH HHS KL2 TR000143NCCIH NIH HHS R01 AT004569NIDDK NIH HHS R34 DK102100
6 · The paper itself

Abstract

Background: Circulating microRNAs are emerging as potential prognostic biomarkers for the development of type 2 diabetes. However, microRNAs are also associated with complications from impaired glucose metabolism (e.g. endothelial cell function). Prior studies have not evaluated for associations between trajectories of circulating microRNAs with trajectories of fasting blood glucose over time and the responses to behavioral interventions to reduce risk. This study performed longitudinal assessment of microRNAs and fasting blood glucose and identified relationships between microRNAs and behavioral risk reduction interventions. Methods: MicroRNAs (n = 353) were measured in subsets (n = 10, n = 8) of participants from previously completed clinical trials that studied behavioral risk reduction interventions. Fasting blood glucose trajectories were associated with changes in 45 microRNAs over 12 months. Results: Following a 3-month physical activity and dietary intervention compared with baseline, 13 microRNAs were differentially expressed. Seven microRNAs (i.e. miR-106b, miR-20b, miR-363, miR-486, miR-532, miR-92a and miR-93) were commonly identified between the two analyses. Conclusions: Further studies are needed to determine which microRNAs are prognostic biomarkers of risk for type 2 diabetes versus consequences of impaired glucose metabolism. Additional future directions of this research are to differentiate whether microRNAs are prognostic and/or diagnostic biomarkers for risk for type 2 diabetes and predictive biomarkers of responses to risk reduction interventions.

Indexed as

biomarkerdiabetesfasting blood glucosemicroRNA

Identifiers

PMID29259803
PMCPMC5729496

What OpenQuestion holds

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Registered trials

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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.