ACE2 pathway regulates thermogenesis and energy metabolism

  1. Xi Cao
  2. Tingting Shi
  3. Chuanhai Zhang
  4. Wanzhu Jin
  5. Lini Song
  6. Yichen Zhang
  7. Jingyi Liu
  8. Fangyuan Yang
  9. Charles N Rotimi
  10. Aimin Xu
  11. Jinkui Yang  Is a corresponding author
  1. Capital Medical University, China
  2. University of Texas Meical Center at Dallas, United States
  3. Chinese Academy of Sciences, China
  4. National Institutes of Health, United States
  5. University of Hong Kong, Hong Kong

Abstract

Identification of key regulators of energy homeostasis holds important therapeutic promise for metabolic disorders, such as obesity and diabetes. ACE2 cleaves angiotensin II (Ang II) to generate Ang-(1-7) which acts mainly through the Mas1 receptor. Here, we identify ACE2 pathway as a critical regulator in the maintenance of thermogenesis and energy expenditure. We found that ACE2 is highly expressed in brown adipose tissue (BAT) and that cold stimulation increases ACE2 and Ang-(1-7) levels in BAT and serum. Ace2 knockout mice (Ace2-/y) and Mas1 knockout mice (Mas1-/-) displayed impaired thermogenesis. Mice transplanted with brown adipose tissue from Mas1-/- display metabolic abnormalities consistent with those seen in the Ace2 and Mas1 knockout mice. In contrast, impaired thermogenesis of Leprdb/db obese diabetic mice and high-fat diet-induced obese mice were ameliorated by overexpression of Ace2 or continuous infusion of Ang-(1-7). Activation of ACE2 pathway was associated with improvement of metabolic parameters, including blood glucose, lipids and energy expenditure in multiple animal models. Consistently, ACE2 pathway remarkably enhanced the browning of white adipose tissue. Mechanistically, we showed that ACE2 pathway activated Akt/FoxO1 and PKA pathway, leading to induction of UCP1 and activation of mitochondrial function. Our data propose that adaptive thermogenesis requires regulation of ACE2 pathway and highlight novel potential therapeutic targets for the treatment of metabolic disorders.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting file.

Article and author information

Author details

  1. Xi Cao

    Beijing Diabetes Institute, Beijing Key Laboratory of Diabetes Research and Care, Beijing Tongren Hospital, Capital Medical University, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  2. Tingting Shi

    Beijing Diabetes Institute, Beijing Key Laboratory of Diabetes Research and Care, Beijing Tongren Hospital, Capital Medical University, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  3. Chuanhai Zhang

    Department of Physiology, University of Texas Meical Center at Dallas, Dallas, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7644-2436
  4. Wanzhu Jin

    Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  5. Lini Song

    Beijing Diabetes Institute, Beijing Key Laboratory of Diabetes Research and Care, Beijing Tongren Hospital, Capital Medical University, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  6. Yichen Zhang

    Beijing Diabetes Institute, Beijing Key Laboratory of Diabetes Research and Care, Beijing Tongren Hospital, Capital Medical University, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  7. Jingyi Liu

    Beijing Diabetes Institute, Beijing Key Laboratory of Diabetes Research and Care, Beijing Tongren Hospital, Capital Medical University, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  8. Fangyuan Yang

    Beijing Diabetes Institute, Beijing Key Laboratory of Diabetes Research and Care, Beijing Tongren Hospital, Capital Medical University, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  9. Charles N Rotimi

    National Human Genome Research Institute, National Institutes of Health, Bethesda, United States
    Competing interests
    The authors declare that no competing interests exist.
  10. Aimin Xu

    Department of Medicine, University of Hong Kong, Hong Kong, Hong Kong
    Competing interests
    The authors declare that no competing interests exist.
  11. Jinkui Yang

    Beijing Diabetes Institute, Beijing Key Laboratory of Diabetes Research and Care, Beijing Tongren Hospital, Capital Medical University, Beijing, China
    For correspondence
    jkyang@ccmu.edu.cn
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5430-2149

Funding

National Natural Science Foundation of China (81930019,81561128015)

  • Jinkui Yang

National Natural Science Foundation of China (81670774,82070850)

  • Xi Cao

Beijing natural science foundation (7162047)

  • Xi Cao

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Animal experimentation: All animal protocols used in this study were reviewed and approved by the Ethics Committee of Animal Research at Beijing Tongren Hospital, Capital Medical University (#2017-0107).

Reviewing Editor

  1. Nicola Napoli, Campus Bio-Medico University of Rome, Italy

Publication history

  1. Received: July 16, 2021
  2. Preprint posted: August 10, 2021 (view preprint)
  3. Accepted: January 9, 2022
  4. Accepted Manuscript published: January 11, 2022 (version 1)
  5. Version of Record published: January 20, 2022 (version 2)
  6. Version of Record updated: January 25, 2022 (version 3)
  7. Version of Record updated: March 22, 2022 (version 4)

Copyright

This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

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  1. Xi Cao
  2. Tingting Shi
  3. Chuanhai Zhang
  4. Wanzhu Jin
  5. Lini Song
  6. Yichen Zhang
  7. Jingyi Liu
  8. Fangyuan Yang
  9. Charles N Rotimi
  10. Aimin Xu
  11. Jinkui Yang
(2022)
ACE2 pathway regulates thermogenesis and energy metabolism
eLife 11:e72266.
https://doi.org/10.7554/eLife.72266

Further reading

    1. Medicine
    2. Neuroscience
    Guido I Guberman et al.
    Research Article

    Background: The heterogeneity of white matter damage and symptoms in concussion has been identified as a major obstacle to therapeutic innovation. In contrast, most diffusion MRI (dMRI) studies on concussion have traditionally relied on group-comparison approaches that average out heterogeneity. To leverage, rather than average out, concussion heterogeneity, we combined dMRI and multivariate statistics to characterize multi-tract multi-symptom relationships.

    Methods: Using cross-sectional data from 306 previously-concussed children aged 9-10 from the Adolescent Brain Cognitive Development Study, we built connectomes weighted by classical and emerging diffusion measures. These measures were combined into two informative indices, the first representing microstructural complexity, the second representing axonal density. We deployed pattern-learning algorithms to jointly decompose these connectivity features and 19 symptom measures.

    Results: Early multi-tract multi-symptom pairs explained the most covariance and represented broad symptom categories, such as a general problems pair, or a pair representing all cognitive symptoms, and implicated more distributed networks of white matter tracts. Further pairs represented more specific symptom combinations, such as a pair representing attention problems exclusively, and were associated with more localized white matter abnormalities. Symptom representation was not systematically related to tract representation across pairs. Sleep problems were implicated across most pairs, but were related to different connections across these pairs. Expression of multi-tract features was not driven by sociodemographic and injury-related variables, as well as by clinical subgroups defined by the presence of ADHD. Analyses performed on a replication dataset showed consistent results.

    Conclusions: Using a double-multivariate approach, we identified clinically-informative, cross-demographic multi-tract multi-symptom relationships. These results suggest that rather than clear one-to-one symptom-connectivity disturbances, concussions may be characterized by subtypes of symptom/connectivity relationships. The symptom/connectivity relationships identified in multi-tract multi-symptom pairs were not apparent in single-tract/single-symptom analyses. Future studies aiming to better understand connectivity/symptom relationships should take into account multi-tract multi-symptom heterogeneity.

    Funding: financial support for this work from a Vanier Canada Graduate Scholarship from the Canadian Institutes of Health Research (GIG), an Ontario Graduate Scholarship (SS), a Restracomp Research Fellowship provided by the Hospital for Sick Children (SS), an Institutional Research Chair in Neuroinformatics (MD), as well as a Natural Sciences and Engineering Research Council CREATE grant (MD).