| Literature DB >> 29229927 |
María A Zuriaga1, José J Fuster1, Melissa G Farb2, Susan MacLauchlan1, Rosa Bretón-Romero2, Shakun Karki2, Donald T Hess3, Caroline M Apovian4, Naomi M Hamburg2, Noyan Gokce2, Kenneth Walsh5.
Abstract
The accumulation of visceral adiposity is strongly associated with systemic inflammation and increased cardiometabolic risk. WNT5A, a non-canonical WNT ligand, has been shown to promote adipose tissue inflammation and insulin resistance in animal studies. Among other non-canonical pathways, WNT5A activates planar cell polarity (PCP) signaling. The current study investigated the potential contribution of non-canonical WNT5A/PCP signaling to visceral adipose tissue (VAT) inflammation and associated metabolic dysfunction in individuals with obesity. VAT and subcutaneous adipose tissue (SAT) samples obtained from subjects undergoing bariatric surgery were analyzed by qRT-PCR for expression of WNT/PCP genes. In vitro experiments were conducted with preadipocytes isolated from VAT and SAT biopsies. The expression of 23 out of 33 PCP genes was enriched in VAT compared to SAT. Strong positive expression correlations of individual PCP genes were observed in VAT. WNT5A expression in VAT, but not in SAT, correlated with indexes of JNK signaling activity, IL6, waist-to-hip ratio and hsCRP. In vitro, WNT5A promoted the expression of IL6 in human preadipocytes. In conclusion, elevated non-canonical WNT5A signaling in VAT contributes to the exacerbated IL-6 production in this depot and the low-grade systemic inflammation typically associated with visceral adiposity.Entities:
Mesh:
Year: 2017 PMID: 29229927 PMCID: PMC5725530 DOI: 10.1038/s41598-017-17509-5
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Relative gene expression of WNT/PCP genes in VAT compared to SAT.
| Gene | Relative gene expression (visceral vs subcutaneous) | p value | |
|---|---|---|---|
| WNT ligands | WNT4 | 4.41 ± 0.73 | 1.8 × 10−5 |
| WNT5A | 14.72 ± 0.66 | 3.2 × 10−25 | |
| WNT9B | 1.62 ± 0.24 | 0.0362 | |
| WNT11 | 0.94 ± 0.07 | 0.3974 | |
| Transmembrane proteins (receptors, co-receptors) | ROR1 | 2.52 ± 0.19 | 2.7 × 10−11 |
| ROR2 | 33.39 ± 2.1 | 2.4 × 10−19 | |
| FZD1 | 2.50 ± 0.14 | 1.2 × 10−14 | |
| FZD2 | 2.13 ± 0.17 | 2.7 × 10−8 | |
| FZD3 | 2.44 ± 0.14 | 1.1 × 10−6 | |
| FZD4 | 0.69 ± 0.05 | 0.0025 | |
| FZD5 | 0.97 ± 0.07 | 0.6621 | |
| FZD6 | 1.00 ± 0.06 | 0.2090 | |
| FZD7 | 5.24 ± 0.31 | 1.4 × 10−18 | |
| FZD8 | 1.02 ± 0.06 | 0.9688 | |
| FZD9 | 0.89 ± 0.12 | 0.2588 | |
| FZD10 | 1.26 ± 0.24 | 0.1938 | |
| VANGL1 | 1.09 ± 0.07 | 0.5189 | |
| VANGL2 | 3.85 ± 0.31 | 1.2 × 10−13 | |
| CELSR1 | 3.37 ± 0.21 | 2.8 × 10−15 | |
| CELSR2 | 3.31 ± 0.40 | 5.9 × 10−10 | |
| CELSR3 | 1.6 ± 0.20 | 6.7 × 10−5 | |
| PTK7 | 9.06 ± 0.89 | 9.1 × 10−12 | |
| RYK | 1.18 ± 0.06 | 0.0260 | |
| Intracellular signaling mediators | DVL1 | 1.74 ± 0.12 | 1.65 × 10−11 |
| DVL2 | 1.36 ± 0.13 | 0.0016 | |
| DVL3 | 1.45 ± 0.08 | 9.8 × 10−7 | |
| ANKRD6 | 1.68 ± 0.12 | 1.9 × 10−8 | |
| INVS | 1.61 ± 0.08 | 5.83 × 10−10 | |
| SCRIB | 2.02 ± 0.07 | 1.87 × 10−17 | |
| PRICKLE1 | 2.60 ± 0.20 | 1.34 × 10−11 | |
| PRICKLE2 | 1.07 ± 0.05 | 0.3859 | |
| DAAM1 | 1.15 ± 0.07 | 0.0740 | |
| DAAM2 | 1.04 ± 0.07 | 0.6014 |
Transcript levels were evaluated by qRT-PCR. Data is expressed as Mean ± SEM.
Figure 1Overexpression of core PCP genes in visceral adipose tissue. (A) Schematic representation of main PCP signaling components. (B–I) Transcript levels of WNT5A (B), ROR co-receptors (C), FZD receptors (D) and main transmembrane and intracellular PCP signaling mediators (E–I) were evaluated in subcutaneous and visceral adipose tissue of subjects undergoing bariatric surgery by qRT-PCR analysis (**p < 0.001, ***p < 0.0001).
Figure 2WNT5A expression correlates with JNK signaling activity in VAT. (A,B) Relative levels of total (A) and phosphorylated JNK1/2 (B) in SAT and VAT were quantified by ELISA. (C,D) Pearson’s coefficients (r) were used to analyze the correlation between WNT5A transcript levels and pJNK/JNK protein ratios in visceral/omental (C) and subcutaneous (D) fat.
Figure 3WNT5A expression correlates with IL6 expression in VAT. (A,B) IL6 transcript and protein levels in SAT and VAT were evaluated by qRT-PCR (A) or ELISA (B). (C,D) Pearson’s correlation coefficients (r) were used to analyze the correlation between WNT5A and IL6 transcript levels in omental (C) and subcutaneous (D) fat were evaluated by qRT-PCR.
Figure 4WNT5A promotes IL6 production in human preadipocytes in vitro. (A) Baseline mRNA expression of WNT5A and IL6 was measured in visceral/omental and subcutaneous preadipocytes by qRT-PCR (n = 5). (B) Transcript levels of IL6 after treatment with recombinant WNT5A protein (1 µg/ml for 8 hours), assessed by qRT-PCR analysis. (C,D) Transcript levels of IL6 after treatment with with siRNA against WNT5A (C) or scrambled siRNA (D) as control. Data represented as percentage of WNT5A knock-down and percentage of change in IL6 mRNA levels.
Figure 5Positive correlation between WNT5A expression in VAT and markers of systemic inflammation and cardiometabolic risk under obesity conditions. Pearson’s coefficients (r) were used to analyze the correlation between WNT5A transcript levels and waist-to-hip ratio (A) and hsCRP (B).