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. 2017 Oct:132:85-94.
doi: 10.1016/j.diabres.2017.07.008. Epub 2017 Jul 19.

Salivary extracellular RNA biomarkers for insulin resistance detection in hispanics

Yong Zhang  1 , Jie Sun  2 , Feng Li  3 , Tristan R Grogan  4 , Jose L Vergara  5 , QingXian Luan  6 , Moon-Soo Park  7 , David Chia  8 , David Elashoff  4 , Kaumudi J Joshipura  9 , David T W Wong  10
Affiliations

Salivary extracellular RNA biomarkers for insulin resistance detection in hispanics

Yong Zhang et al. Diabetes Res Clin Pract. 2017 Oct.

Abstract

Aims: Insulin 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.

Methods: We 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.

Results: Transcriptomic 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%).

Conclusions: A 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.

Keywords: Extracellular RNA; Insulin resistance; Salivary biomarker.

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Conflict of interest statement

Conflicts of interest statement: David T.W Wong is co-founder of RNAmeTRIX Inc., a molecular diagnostic company. He holds equity in RNAmeTRIX, and serves as a company Director and Scientific Advisor. The University of California also holds equity in RNAmeTRIX. Intellectual property that David Wong invented and which was patented by the University of California has been licensed to RNAmeTRIX. Additionally, he is a consultant to PeriRx. All other authors have nothing to disclose.

Figures

Figure 1
Figure 1
Panel A shows the mean (±SE) salivary levels of ten candidate markers in individual exRNA marker validation set, six of them (PRKCB, S100A12, IL1R2, CAMP, VPS4B, CAP1) showed significant difference between high IR and low IR groups. Panel B and C show levels of six candidate markers used in prediction panel building (B) and validation of the prediction model (C). In Panel A, B, and C, a single asterisk denotes P<.05 for the between-group comparison; double asterisks denote P<.01.
Figure 2
Figure 2
ROC curves for final prediction panel for IR in: A) non-diabetic and pre-diabetic; B) non-diabetics; C) pre-diabetics
See this image and copyright information in PMC

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