Evidence map›Paper›PMID 28802700›Full record

ArticleDiabetes research and clinical practice2017

Salivary extracellular RNA biomarkers for insulin resistance detection in hispanics.

Yong Zhang, Jie Sun, Feng Li, Tristan R Grogan, Jose L Vergara, QingXian Luan, Moon-Soo Park, David Chia, David Elashoff, Kaumudi J Joshipura and 1 more

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Diabetes research and clinical practice, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.2field-weighted citation impact, top 45% 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

5 citing papers in PubMed, 11 citations in OpenAlex.

  1. Liquid Biopsy: A Game Changer for Type 2 Diabetes.International journal of molecular sciences · 2024
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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

11 authors at 5 institutions in 4 countries.

Yong ZhangFirst Clinical Division, Peking University School and Hospital of Stomatology, Beijing, China; School of Dentistry, University of California Los Angeles, Los Angeles, CA, USA.
Jie SunSchool of Medicine, Shenzhen University, Shenzhen, China; School of Dentistry, University of California Los Angeles, Los Angeles, CA, USA.
Feng LiSchool of Dentistry, University of California Los Angeles, Los Angeles, CA, USA.
Tristan R GroganDepartment of Biostatistics and Medicine, School of Public Health, University of California Los Angeles, Los Angeles, CA, USA.
Jose L VergaraCenter for Clinical Research and Health Promotion University of Puerto Rico School of Dental Medicine, San Juan, Puerto Rico.
QingXian LuanDepartment of Periodontology, Peking University School and Hospital of Stomatology, Beijing, China.
Moon-Soo ParkDepartment of Oral Medicine and Diagnosis, Oral Science Institute, College of Dentistry, Gangneung-Wonju National University, Gangneung, Republic of Korea; School of Dentistry, University of California Los Angeles, Los Angeles, CA, USA.
David ChiaDepartment of Pathology, University of California Los Angeles, Los Angeles, CA, USA.
David ElashoffDepartment of Biostatistics and Medicine, School of Public Health, University of California Los Angeles, Los Angeles, CA, USA.
Kaumudi J JoshipuraCenter for Clinical Research and Health Promotion University of Puerto Rico School of Dental Medicine, San Juan, Puerto Rico; Department of Epidemiology, T.H. Chan School of Public Health, Harvard University, Boston, MA, USA. Electronic address: kaumudi.joshipura@upr.edu.
David T W WongSchool of Dentistry, University of California Los Angeles, Los Angeles, CA, USA. Electronic address: dtww@ucla.edu.
University of California, Los Angeles · USGangneung–Wonju National University · KRHarvard University · USKing University · USPeking University · CN

Funding

TECHNOLOGIES AND RESOURCES FOR CORE LABORATORIESU54MD007587 · NIMHD · UNIVERSITY OF PUERTO RICO MED SCIENCES · PI LUCIANO, CARLOS A., NOBOA, CARIAMARIE · 2012 to 2018
$23.2M
TRCLU54RR026139 · NCRR · UNIVERSITY OF PUERTO RICO MED SCIENCES · PI FRONTERA, WALTER R. · 2010 to 2011
$8.4M
Periodontitis and pre-clinical diabetesR01DE020111 · NIDCR · UNIVERSITY OF PUERTO RICO MED SCIENCES · PI JOSHIPURA, KAUMUDI J, PEREZ, CYNTHIA MADELINE · 2010 to 2015
$3.1M
Molecular Determinants of Oral Tongue Cancer MetastasisR01CA139596 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI WONG, DAVID T, ZHOU, XIAOFENG · 2008 to 2012
$1.7M
Clinical Utility of Salivary ExRNA Biomarkers for Gastric Cancer DetectionUH2TR000923 · NCATS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI WONG, DAVID T · 2013 to 2014
$996k
NCATS NIH HHS UH2 TR000923NCI NIH HHS R01 CA139596NCRR NIH HHS U54 RR026139NIDCR NIH HHS R01 DE020111NIMHD NIH HHS U54 MD007587
6 · The paper itself

Abstract

aimsInsulin resistance (IR) detection is challenging and no test is currently used in clinical practice. We developed salivary biomarkers that could be used for IR detection.

methodsWe collected saliva from 186 healthy and 276 pre-diabetic participants, divided them into high and low IR groups based on a HOMA cutoff of 2.5. We profiled extracellular transcriptome by microarray in saliva supernatant from 23 high IR and 15 low IR participants, and pre-validated the top ten extracellular mRNA (exRNA) markers in a new cohort of 40 high and 40 low IR participants. A prediction panel was then built and validated in an independent cohort of 149 high and 195 low IR participants.

resultsTranscriptomic analyses identified 42 exRNA candidates differentially present in saliva of high and low IR participants. From the top ten candidates, six were individually validated (PRKCB, S100A12, IL1R2, CAMP, VPS4B, CAP1) (p<0.01) and yielded AUC values ranging from 0.66 to 0.76. Body mass index (BMI) was significant higher in high compared to low IR group with AUC of 0.66, and showed no correlation with any of candidate biomarkers. The combination of four exRNA markers (IL1R2, VPS4B, CAP1, LUZP6) with BMI achieved excellent results in the prediction panel building dataset (AUC=0.79, sensitivity=79%, specificity=64%). The prediction model was validated in an independent cohort (AUC=0.82, sensitivity=63%, specificity=92%).

conclusionsA panel of four salivary exRNA biomarkers (IL1R2, VPS4B, CAP1, LUZP6) and BMI was validated that can distinguish high and low IR participants, overall and in subgroups of healthy and pre-diabetic participants.

Indexed as

AdultAgedBiomarkersFemaleHispanic or LatinoHumansInsulin ResistanceLongitudinal StudiesMaleMiddle AgedSalivaBiomarkersExtracellular RNAInsulin resistanceSalivary biomarker

Identifiers

PMID28802700
PMCPMC5741087
OpenAlexW2738478468

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.