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Integrated multi‑omics analysis of liver metabolic dysregulation in ACE2 knockout mice

  • Authors:
    • Shuai Xiao
    • Jinxiu Guo
    • Bo Yu
    • Shiyuan Zhao
    • Yicun Shang
    • Ni Li
    • Jiyao Cui
    • Fangqiang Song
    • Pei Jiang
  • View Affiliations / Copyright

    Affiliations: Department of Intensive Care Medicine, The Affiliated Tengzhou Central People's Hospital of Xuzhou Medical University, Tengzhou, Shandong 277500, P.R. China, Institute of Translational Pharmacy, Jining Medical Research Academy, Jining, Shandong 272000, P.R. China
    Copyright: © Xiao et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Article Number: 134
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    Published online on: July 3, 2025
       https://doi.org/10.3892/ijmm.2025.5575
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Abstract

The present study systematically investigated the impact of angiotensin‑converting enzyme 2‑knockout (ACE2KO) on hepatic metabolic homeostasis and its molecular mechanisms using integrated transcriptomic, proteomic and metabolomic profiling. ACE2KO exacerbated hepatic lipid accumulation, as evidenced by elevated total cholesterol and triglyceride levels, while disrupting the renin‑angiotensin system equilibrium via increased angiotensin II levels and reduced angiotensin‑(1‑7) levels. Histopathological analysis revealed hepatocyte edema, vacuolar degeneration and inflammatory infiltration in the ACE2KO mice. Multi‑omics integration revealed systemic metabolic dysregulation. Transcriptomics identified 1,004 differentially expressed genes, including lipid metabolism regulators (Scd1 and Fabp1) and circadian rhythm modulators (Arntl and Cry1), proteomics identified 191 differentially expressed proteins associated with interferon signaling activation (Oas1a and Rsad2) and lipid synthesis suppression (Scd1 and Fasn), and metabolomics highlighted 193 differentially expressed metabolites indicative of bile acid dysregulation, glutathione redox imbalance and amino acid metabolism anomalies. Cross‑omics analysis indicated that ACE2 is a key regulator of metabolic homeostasis. Its absence causes systematic metabolic disorders, including lipid metabolism disorder, amino acid metabolic imbalance and detoxification dysfunction. These findings comprehensively delineated the multifaceted role of ACE2 in hepatic metabolic homeostasis, and provided mechanistic insights into and therapeutic targets for ACE2‑associated liver diseases.
View Figures

Figure 1

Hepatic injury, metabolic
dysregulation and renin-angiotensin system pathway imbalance in
ACE2KO mice. (A) Loss of ACE2 protein expression (western
blotting). (B) Reduced ACE2 mRNA levels (reverse
transcription-quantitative PCR). (C) Histopathological alterations
(hematoxylin and eosin staining). The green arrow indicates
hydropic degeneration with cytoplasmic pallor and rarefaction. The
blue arrow shows sporadic vacuolar degeneration with microvesicular
cytoplasmic inclusions. The purple arrow points to focal
lymphocytic infiltrates. The orange arrow denotes mild sinusoidal
stasis. Scale bar, 50 µm. (D) Increased hepatic total
cholesterol levels in ACE2KO vs. CK mice. (E) Increased hepatic
triglyceride levels in ACE2KO vs. CK mice. (F) Decreased
Ang-(1-7) levels. (G) Elevated AngII levels.
ACE2, angiotensin-converting enzyme 2; Ang-(1-7),
angiotensin-(1-7); AngII, angiotensin II; CK, control;
KO, knockout.

Figure 2

ACE2KO induces hepatic transcriptomic
alterations in mice. (A) Heatmap of DEGs in the ACE2KO group vs. CK
group. (B) Volcano plot of DEGs in the ACE2KO group vs. CK group
(red, upregulated; blue, downregulated). (C) GO enrichment analysis
of DEGs between the ACE2KO and CK (total) groups (top 30 terms).
(D) Hierarchical clustering of GO level 2 categories. (E) Top 20
enriched KEGG pathways. (F) Regulatory network between TFs and
target DEGs (Sankey diagram). Statistical thresholds: DEGs, q-value
<0.05; and GO/KEGG terms, P<0.05). ACE2,
angiotensin-converting enzyme 2; CK, control; DEG, differentially
expressed gene; FC, fold change; GO, Gene Ontology; KEGG, Kyoto
Encyclopedia of Genes and Genomes; KO, knockout; PPAR, peroxisome
proliferator-activated receptor; Sig, significance; CellP.,
cellular processes; GenlP., general processes; HumaD., human
diseases; Metab, metabolism; OrgaS., organismal systems; TF,
transcription factor.

Figure 3

ACE2KO induces hepatic proteomic
alterations in mice. (A) Volcano plot of DEPs in the ACE2KO group
vs. CK group (red, upregulated; blue, downregulated). (B) Heatmap
of DEPs in the ACE2KO group vs. CK group. The scale of -2 to 2
indicates standardized data values, with red indicating high
expression (near 2) and blue indicating low expression (near-2).
(C) GO enrichment analysis of DEPs between the ACE2KO and CK
(total) groups (top 30 terms). (D) KEGG enrichment analysis. From
the outside inward: The first circle shows enriched
classifications, with the outer circle as a coordinate ruler for
protein counts; different colors represent various classifications.
The second circle displays protein counts within each
classification and the corresponding P-values, with longer bars and
redder color indicating higher counts and smaller P-values. The
third circle indicates the ratio of upregulated (light red) to
downregulated (light blue) proteins with specific values provided.
The fourth circle represents the rich factor for each
classification (foreground proteins divided by background
proteins), with each grid on the background auxiliary line
representing 0.2. (E) Protein-protein interaction network of DEPs,
where nodes represent DEPs. Red nodes indicate upregulation, blue
nodes indicate downregulation and the node size reflects
connectivity, with larger nodes indicating higher connectivity.
Statistical thresholds: DEPs, P<0.05; and GO/KEGG terms,
P<0.05. ACE2, angiotensin-converting enzyme 2; CK, control; DEP,
differentially expressed protein; FC, fold change; GO, Gene
Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; KO,
knockout; Sig, significance.

Figure 4

ACE2KO disrupts hepatic metabolomic
profiles in mice. (A) OPLS-DA plot illustrating sample clustering
and group separation. (B) Permutation plot validating the OPLS-DA
model. (C) Volcano plot of DEMs in the ACE2KO group vs. CK group.
(D) Heatmap of DEMs in the ACE2KO group vs. CK group. The scale of
-2 to 2 indicates standardized data values, with red meaning high
expression (near 2) and blue meaning low expression (near -2). (E)
Correlation analysis of DEMs. Red circles denote positive
correlation (values closer to 1 indicate stronger correlations),
blue circles represent negative correlation (values closer to -1
indicate stronger correlations) and the area of the circles is
proportional to the absolute value of the correlation coefficient.
(F) Top 20 enriched Kyoto Encyclopedia of Genes and Genomes
metabolic pathways. P-values reflect the significance of enrichment
within metabolic pathways. The red line represents a P-value
threshold of 0.01, and the blue line represents a P-value threshold
of 0.05. Statistical thresholds: DEMs, VIP >1 and P<0.05; and
pathways, P<0.05. ACE2, angiotensin-converting enzyme 2; CK,
control; DEM, differentially expressed metabolite; FC, fold change;
KO, knockout; OPLS-DA, orthogonal partial least
squares-discriminant analysis; PPAR, peroxisome
proliferator-activated receptor; Sig, significance; VIP, variable
importance in projection.

Figure 5

Multi-omics integration identifies
key biomarkers and pathway crosstalk in ACE2KO mice. (A) MixOmics
analysis of multi-omics data. The R package mixOmics was utilized
for integrated analysis of multi-omics data to illustrate the
correlation and discriminative capacity of different omics data on
their first principal components. The lower triangle shows the
Pearson correlation coefficients between the first principal
components of each pair of omics data, while the upper triangle
presents scatter plots of ACE2KO (blue) and CK (orange) groups on
the first principal component of each omics type, visually
reflecting the role of different omics in distinguishing between
the two groups. (B) Bar chart of the top 30 biomarkers
distinguishing the ACE2KO and CK groups. (C) Correlation
coefficient distribution plot, where the x-axis represents the
correlation coefficient, and the y-axis indicates the number of
coefficients within the corresponding bins. (D) Venn diagram
depicting the differential pathways mapped to genes, proteins and
metabolites. (E) Bar chart of common pathways mapped by
differentially expressed genes, proteins and metabolites, with the
x-axis representing pathways and the y-axis reflecting pathway
enrichment P-values. (F) Distribution diagram of associated
elements, where the x-axis represents pathway IDs and the y-axis
indicates the number of corresponding interaction pathways. ACE2,
angiotensin-converting enzyme 2; CK, control; KO, knockout; PPAR,
peroxisome proliferator-activated receptor.

Figure 6

KEGG Markup Language interaction
network. (A) Level 1 major pathway interaction network. This
network represents the classification of pathways into high-level
biological processes, highlighting global interaction patterns
among broad functional categories. (B) Level 2 subclass pathway
interaction network. This network further categorizes pathways into
specialized functional subclasses, delineating pathway coordination
within specific biological mechanisms or disease-related modules.
Node labels represent pathway names, node sizes indicate
connectivity (degree of interaction) and node colors correspond to
the KEGG classification levels. ACE2, angiotensin-converting enzyme
2; CK, control; KEGG, Kyoto Encyclopedia of Genes and Genomes; KO,
knockout; PPAR, peroxisome proliferator-activated receptor.
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Copy and paste a formatted citation
Spandidos Publications style
Xiao S, Guo J, Yu B, Zhao S, Shang Y, Li N, Cui J, Song F and Jiang P: Integrated multi‑omics analysis of liver metabolic dysregulation in ACE2 knockout mice. Int J Mol Med 56: 134, 2025.
APA
Xiao, S., Guo, J., Yu, B., Zhao, S., Shang, Y., Li, N. ... Jiang, P. (2025). Integrated multi‑omics analysis of liver metabolic dysregulation in ACE2 knockout mice. International Journal of Molecular Medicine, 56, 134. https://doi.org/10.3892/ijmm.2025.5575
MLA
Xiao, S., Guo, J., Yu, B., Zhao, S., Shang, Y., Li, N., Cui, J., Song, F., Jiang, P."Integrated multi‑omics analysis of liver metabolic dysregulation in ACE2 knockout mice". International Journal of Molecular Medicine 56.3 (2025): 134.
Chicago
Xiao, S., Guo, J., Yu, B., Zhao, S., Shang, Y., Li, N., Cui, J., Song, F., Jiang, P."Integrated multi‑omics analysis of liver metabolic dysregulation in ACE2 knockout mice". International Journal of Molecular Medicine 56, no. 3 (2025): 134. https://doi.org/10.3892/ijmm.2025.5575
Copy and paste a formatted citation
x
Spandidos Publications style
Xiao S, Guo J, Yu B, Zhao S, Shang Y, Li N, Cui J, Song F and Jiang P: Integrated multi‑omics analysis of liver metabolic dysregulation in ACE2 knockout mice. Int J Mol Med 56: 134, 2025.
APA
Xiao, S., Guo, J., Yu, B., Zhao, S., Shang, Y., Li, N. ... Jiang, P. (2025). Integrated multi‑omics analysis of liver metabolic dysregulation in ACE2 knockout mice. International Journal of Molecular Medicine, 56, 134. https://doi.org/10.3892/ijmm.2025.5575
MLA
Xiao, S., Guo, J., Yu, B., Zhao, S., Shang, Y., Li, N., Cui, J., Song, F., Jiang, P."Integrated multi‑omics analysis of liver metabolic dysregulation in ACE2 knockout mice". International Journal of Molecular Medicine 56.3 (2025): 134.
Chicago
Xiao, S., Guo, J., Yu, B., Zhao, S., Shang, Y., Li, N., Cui, J., Song, F., Jiang, P."Integrated multi‑omics analysis of liver metabolic dysregulation in ACE2 knockout mice". International Journal of Molecular Medicine 56, no. 3 (2025): 134. https://doi.org/10.3892/ijmm.2025.5575
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