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Clinical Research

Perirenal fat: a neglected fat depot shaping heterogeneity of obesity along with hepatic fat

International Journal of Obesity (2025)Cite this article

Subjects

Abstract

Objective

Obesity is a heterogeneous condition that leads to diverse cardiovascular and metabolic outcomes. This study aimed to identify the primary visceral fats contributing to metabolically unhealthy obesity and to investigate the characteristics of fat distribution associated with different obesity-related complications.

Methods

A retrospective analysis was conducted on fat-selective magnetic resonance images (MRI) from 319 individuals with a BMI ≥24 kg/m². Participants were categorized into four groups: solely obesity, T2DM, hypertension, and dyslipidemia, to examine differences in the distribution of hepatic, pancreatic, preperitoneal, mesenteric, and perirenal fat (PrFT). Correlation analyses were performed to elucidate relationships between visceral fat deposits and obesity-related characteristics. Logistic regression identified key fat deposition sites associated with common obesity-related complications. Additionally, the limitations of single-site fat measurements in capturing the heterogeneity of obesity were examined.

Results

PrFT exhibited the strongest correlation with blood pressure (r = 0.225 ~ 0.306, all p < 0.001) among all visceral fats, and the hypertensive individuals with obesity presented the highest PrFT. Hepatic fat showed the highest association with glucose metabolism (r = 0.188 ~ 0.407 all p < 0.01), as evidenced by higher hepatic fat content in the T2DM group compared to other groups. Risk of metabolic syndrome increased by 3.06-fold (95% CI:1.35–6.93, p = 0.007) and 6.79-fold (95% CI:2.45–18.83, p < 0.001) with moderate and severe fatty steatosis compared to those without hepatic steatosis. A 2.24-fold (95% CI:1.27–3.97, p = 0.006) increase in metabolic syndrome likelihood was observed for each 1 cm increment in PrFT.

Conclusions

Besides hepatic fat, perirenal fat is also a key determinant for metabolic syndrome. Patients with various metabolic abnormalities present distinct patterns of visceral fat distribution, which could be simply profiled by perirenal and hepatic fat quantification.

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Fig. 1
Fig. 2: Fat distribution in patients with different obesity-related complications.
Fig. 3: Correlation between MRI fat parameters with metabolic characteristics shown in heatmap.
Fig. 4: Prevalence rates of obesity-related abnormalities analyzed by single fat stratification.

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Data availability

The datasets generated and analyzed during the current study are available from the corresponding authors on reasonable request.

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Acknowledgements

The authors sincerely acknowledge the invaluable collaboration and support provided by all the members of the “3+N” multidisciplinary weight loss program, Medical Center for Comprehensive Weight Control, the Third Affiliated Hospital of Sun Yat-Sen University. The authors also wish to thank all subjects who participated in this study.

Funding

This study was funded by National Natural Science Foundation of China (Grant 82270886, Grant 82302222), Guangdong Basic and Applied Basic Research Foundation (Grant 2023A1515220121), Sci-Tech Research Development Program of Guangzhou City (202201020589) and Clinical Research 5010 Program (Grant 2023006), Fundamental Research Funds for the Central Universities, Sun Yat-sen University.

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Author notes

  1. These authors contributed equally: Yixin Chen, Ting Zhang.

Authors and Affiliations

  1. Department of Endocrinology and Metabolism, Guangdong Provincial Key Laboratory of Diabetology & Guangzhou Municipal Key Laboratory of Mechanistic and Translational Obesity Research, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China

    Yixin Chen, Baoding Qin, Yi Yang, Yuchan Wang, Zijian Mo, Mengyin Cai, Guojun Shi, Yanhua Zhu & Yanming Chen

  2. Department of Medical Ultrasound, Guangdong Provincial Key Laboratory of Diabetology & Guangzhou Municipal Key Laboratory of Mechanistic and Translational Obesity Research, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China

    Ting Zhang & Jie Zeng

  3. Department of Cardiology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China

    Lin Wu

  4. Department of Radiology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China

    Ruomi Guo

  5. Department of Clinical Immunology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China

    Yanming Chen

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  1. Yixin Chen
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Contributions

Jie Zeng, Yixin Chen and Ting Zhang designed this study and drafted the manuscript. Yixin Chen, Ruomi Guo, Baoding Qin, Yang Yi conducted MRI and statistical analyses. Ruomi Guo offered technical support in MRI sequences. Wu Lin, Yuchan Wang, and Zijian Mo were responsible for the curation of clinical data, and the acquisition of consent from study subjects. Mengyin Cai and Guojun Shi were responsible for result verification. Yanming Chen, Jie Zeng, and Yanhua Zhu initiated this study, edited the manuscript, and supervised this research.

Corresponding authors

Correspondence to Yanhua Zhu, Jie Zeng or Yanming Chen.

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Competing interests

The authors declare no competing interests.

Ethical approval

The study protocols were approved by the ethics committee of the Third Affiliated Hospital of Sun Yat-sen University (Ethical approval number: II2023-075-02). All methods were performed in accordance with the relevant guidelines and regulations. Written informed consent was obtained from each participant.

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Chen, Y., Zhang, T., Qin, B. et al. Perirenal fat: a neglected fat depot shaping heterogeneity of obesity along with hepatic fat. Int J Obes (2025). https://doi.org/10.1038/s41366-025-01874-7

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