Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 Dec 2;71(12):1157-1163.
doi: 10.1507/endocrj.EJ24-0256. Epub 2024 Sep 14.

Dysregulation of c-Jun (JUN) and FBJ murine osteosarcoma viral oncogene homolog B (FOSB) in obese people and their predictive values for metabolic syndrome

Affiliations

Dysregulation of c-Jun (JUN) and FBJ murine osteosarcoma viral oncogene homolog B (FOSB) in obese people and their predictive values for metabolic syndrome

Chenxi Yang et al. Endocr J. .

Abstract

The incidences of metabolic syndrome (MetS), denoting insulin resistance-associated various metabolic disorders, are increasing. This study aimed to identify new biomarkers for predicting MetS and provide a novel diagnostic approach. Herein, the expression profiles of c-Jun (JUN) and FBJ murine osteosarcoma viral oncogene homolog B (FOSB) in individuals with obesity and patients with MetS from the Gene Expression Omnibus database. Quantitative reverse transcription polymerase chain reaction (RT-qPCR) was used to evaluate the messenger RNA levels of JUN and FOSB in the peripheral blood of healthy volunteers (lean and obese) and patients with MetS (lean and obese), along with that in the adipose tissue and peripheral blood of obese mouse model. Furthermore, receiver operating characteristic (ROC) curve and logistic regression analyses were performed to determine the diagnostic value of JUN and FOSB in MetS. The expression profiles and RT-qPCR results showed that JUN and FOSB were highly expressed in individuals with obesity, obese mouse models, and patients with MetS. The ROC analysis results showed an area under the curve values of 0.872 and 0.879 for JUN, 0.802 and 0.962 for FOSB, and 0.946 and 0.979 for JUN-FOSB in the lean group and the group with obesity, respectively, in predicting MetS. Logistic regression analysis showed that the p-values of both JUN and FOSB as MetS-affecting factors were <0.05. Altogether, the findings of this study indicate that both JUN and FOSB, abnormally expressed in individuals with obesity, are good biomarkers of MetS.

Keywords: Diagnosis; FBJ murine osteosarcoma viral oncogene homolog B (FOSB); Metabolic syndrome; Obesity; c-Jun (JUN).

PubMed Disclaimer

Conflict of interest statement

None of the authors have any potential conflicts of interest associated with this research.

Figures

Fig. 1
Fig. 1. JUN and FOSB contribute to the development of obesity. (A) The Venn diagram of the genes that were highly expressed in individuals with obesity (GSE235696) and patients with metabolic syndrome (GSE98895). (B and C) The expression profiles of JUN and FOSB in lean and individuals with obesity from the GSE235696 dataset. (D and E) Relative mRNA levels of JUN and FOSB in the peripheral blood derived from lean and individuals with obesity. (F and G) Relative mRNA levels of JUN and FOSB in the visceral adipose tissue and peripheral blood of healthy and obese mice. ***p < 0.001.
Fig. 2
Fig. 2. High expression of JUN and FOSB in patients with MetS. (A and B) The expression maps of JUN and FOSB in healthy individuals and patients with MetS from the GSE98895 dataset. (C and D) Relative mRNA levels of JUN and FOSB in the peripheral blood of lean and individuals with obesity without or with MetS. ***p < 0.001.
Fig. 3
Fig. 3. JUN and FOSB are valuable biomarkers of MetS. The ROC curves of JUN and FOSB levels for MetS prediction in (A) lean individuals and (B) individuals with obesity.

Similar articles

References

    1. Seravalle G, Grassi G (2017) Obesity and hypertension. Pharmacol Res 122: 1–7. - PubMed
    1. Ortega FB, Lavie CJ, Blair SN (2016) Obesity and cardiovascular disease. Circ Res 118: 1752–1770. - PubMed
    1. Koliaki C, Liatis S, Kokkinos A (2019) Obesity and cardiovascular disease: revisiting an old relationship. Metabolism 92: 98–107. - PubMed
    1. Snyder S, Turner GA, Turner A (2014) Obesity-related kidney disease. Prim Care 41: 875–893. - PubMed
    1. Craig JR, Jenkins TG, Carrell DT, Hotaling JM (2017) Obesity, male infertility, and the sperm epigenome. Fertil Steril 107: 848–859. - PubMed

MeSH terms