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The Potential Role of Pyrroloquinoline Quinone to Regulate Thyroid Function and Gut Microbiota Composition of Graves’ Disease in Mice

Xiaoyan Liu

Xiaoyan Liu

Department of Nuclear Medicine, Shanghai Tenth Hospital, School of Clinical Medicine of Nanjing Medical UniversityShanghai, People’s Republic of China
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Liu, Xiaoyan
, 
Wen Jiang

Wen Jiang

Department of Nuclear Medicine, Shanghai Tenth People’s Hospital, Tongji University School of MedicineShanghai, People’s Republic of China
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Jiang, Wen
, 
Ganghua Lu

Ganghua Lu

Department of Nuclear Medicine, Shanghai Tenth People’s Hospital, Tongji University School of MedicineShanghai, People’s Republic of China
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Lu, Ganghua
, 
Tingting Qiao

Tingting Qiao

Department of Nuclear Medicine, Shanghai Tenth People’s Hospital, Tongji University School of MedicineShanghai, People’s Republic of China
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Qiao, Tingting
, 
Dingwei Gao

Dingwei Gao

Department of Nuclear Medicine, Shanghai Tenth People’s Hospital, Tongji University School of MedicineShanghai, People’s Republic of China
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Gao, Dingwei
, 
Mengyu Zhang

Mengyu Zhang

Department of Nuclear Medicine, Shanghai Tenth People’s Hospital, Tongji University School of MedicineShanghai, People’s Republic of China
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Zhang, Mengyu
, 
Haidong Cai

Haidong Cai

Department of Nuclear Medicine, Shanghai Tenth People’s Hospital, Tongji University School of MedicineShanghai, People’s Republic of China
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Cai, Haidong
, 
Li Chai

Li Chai

Department of Nuclear Medicine, Shanghai Tenth People’s Hospital, Tongji University School of MedicineShanghai, People’s Republic of China
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Chai, Li
, 
Wanwan Yi

Wanwan Yi

Department of Nuclear Medicine, Shanghai Tenth People’s Hospital, Tongji University School of MedicineShanghai, People’s Republic of China
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Yi, Wanwan
 and 
Zhongwei Lv

Zhongwei Lv

  • Department of Nuclear Medicine, Shanghai Tenth Hospital, School of Clinical Medicine of Nanjing Medical UniversityShanghai, People’s Republic of China
  • Department of Nuclear Medicine, Shanghai Tenth People’s Hospital, Tongji University School of MedicineShanghai, People’s Republic of China
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Lv, Zhongwei
  
Dec 16, 2023
The Potential Role of Pyrroloquinoline Quinone to Regulate Thyroid Function and Gut Microbiota Composition of Graves’ Disease in Mice's Cover Image
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Article Category: ORIGINAL PAPER
Published Online: Dec 16, 2023
Page range: 443 - 460
Received: Aug 02, 2023
Accepted: Oct 27, 2023
DOI: https://doi.org/10.33073/pjm-2023-042
Keywords
© 2023 Xiaoyan Liu et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Fig. 1.

PQQ supplement modulates thyroid function and ameliorates thyroid injury. A) The concentrations of T4 and B) TRAb levels were determined inserum samples using Mouse ELISA Kit, C) the representative pictures of H&E staining of thyroids (200 × magnification with 100 μm of scale). Data were represented as mean ± SEM, *p < 0.05, **p < 0.01, ***p < 0.001 between groups. Con – control group, GD – Graves’ disease group, GD + PQQ/low – GD mice treated with 20 mg PQQ/kg BW/day, GD + PQQ/mid – GD mice treated with 40 mg PQQ/kg BW/day, GD + PQQ/high – GD mice treated with 60 mg PQQ/kg BW/day, GD + MMI – GD mice treated with 2.5 mg MMI/kg/BW/day, PQQ – pyrroloquinoline quinone, MMI – methimazole
PQQ supplement modulates thyroid function and ameliorates thyroid injury. A) The concentrations of T4 and B) TRAb levels were determined inserum samples using Mouse ELISA Kit, C) the representative pictures of H&E staining of thyroids (200 × magnification with 100 μm of scale). Data were represented as mean ± SEM, *p < 0.05, **p < 0.01, ***p < 0.001 between groups. Con – control group, GD – Graves’ disease group, GD + PQQ/low – GD mice treated with 20 mg PQQ/kg BW/day, GD + PQQ/mid – GD mice treated with 40 mg PQQ/kg BW/day, GD + PQQ/high – GD mice treated with 60 mg PQQ/kg BW/day, GD + MMI – GD mice treated with 2.5 mg MMI/kg/BW/day, PQQ – pyrroloquinoline quinone, MMI – methimazole

Fig. 2.

PQQ supplement decreases inflammation and oxidative stress response and alleviates small intestine epithelial injury. Relative expression of mRNA in colons of A) IL6, TNFα, B) Nrf2, HO1 was detected by PCR, C) the representative pictures of the hematoxylin and eosin (H&E) staining of colons (200 × magnification with 100 μm of scale). Data are represented as mean ± SEM, *p < 0.05, **p < 0.01, ***p < 0.001 between groups
PQQ supplement decreases inflammation and oxidative stress response and alleviates small intestine epithelial injury. Relative expression of mRNA in colons of A) IL6, TNFα, B) Nrf2, HO1 was detected by PCR, C) the representative pictures of the hematoxylin and eosin (H&E) staining of colons (200 × magnification with 100 μm of scale). Data are represented as mean ± SEM, *p < 0.05, **p < 0.01, ***p < 0.001 between groups

Fig. 3.

Oral gavage of PQQ restores the diversity of gut microbiota in the GD group. A) Rank-abundance curves of the gut microbiota at the OTU level, B) rarefaction curves (SOBs index) of the gut microbiota at the OTU level. Comparison of a diversity in C) Sobs, D) Ace, E) Chao indices in Con, GD and PQQ/mid groups at the OTU level. Analysis of β diversity using F) PCA, G) PCoA based on bray_curtis, H) binary_jaccard and I) unweighted_unifrac distance and J) NMDS on the genus level. **p < 0.01; ***p < 0.001. OTUs – operational taxonomic units, PCA – principal component analysis, PCoA – principal coordinate analysis, NMDS – non-metric multidimensional scaling
Oral gavage of PQQ restores the diversity of gut microbiota in the GD group. A) Rank-abundance curves of the gut microbiota at the OTU level, B) rarefaction curves (SOBs index) of the gut microbiota at the OTU level. Comparison of a diversity in C) Sobs, D) Ace, E) Chao indices in Con, GD and PQQ/mid groups at the OTU level. Analysis of β diversity using F) PCA, G) PCoA based on bray_curtis, H) binary_jaccard and I) unweighted_unifrac distance and J) NMDS on the genus level. **p < 0.01; ***p < 0.001. OTUs – operational taxonomic units, PCA – principal component analysis, PCoA – principal coordinate analysis, NMDS – non-metric multidimensional scaling
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Fig. 4.

PQQ alters the composition and abundance of intestine flora in the GD group. A) The species Venn diagram at the genus level. Overlapping parts in the figure indicate common species. On the genus level, percent of community abundance unique to B) the Con group, C) GD group and E) PQQ group. D) Percent of community abundance shared by 3 groups.
PQQ alters the composition and abundance of intestine flora in the GD group. A) The species Venn diagram at the genus level. Overlapping parts in the figure indicate common species. On the genus level, percent of community abundance unique to B) the Con group, C) GD group and E) PQQ group. D) Percent of community abundance shared by 3 groups.

Fig. 4.

PQQ alters the composition and abundance of intestine flora in the GD group. F) Percent of community abundance of 3 groups on the Phylum level. G) Percent of community abundance of 3 groups on the Genus level. On the genus level, percent of community abundance in H) the Con group, I) GD group and J) PQQ group.
PQQ alters the composition and abundance of intestine flora in the GD group. F) Percent of community abundance of 3 groups on the Phylum level. G) Percent of community abundance of 3 groups on the Genus level. On the genus level, percent of community abundance in H) the Con group, I) GD group and J) PQQ group.
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Fig. 4.

PQQ alters the composition and abundance of intestine flora in the GD group. I) GD group and J) PQQ group. K) The heatmap on the abundance of top 30 genera among 3 groups. L) The Circos analysis of the abundance association between the sample and the top 10 genera.
PQQ alters the composition and abundance of intestine flora in the GD group. I) GD group and J) PQQ group. K) The heatmap on the abundance of top 30 genera among 3 groups. L) The Circos analysis of the abundance association between the sample and the top 10 genera.

Fig. 5.

Spearman correlation analysis and PICRUSt prediction under PQQ supplement in the GD group. A) Kruskal-Wallis H test validated the differential distributed genera and C) the abundance of Lactobacillus among all 3 groups. B) LEfSe analysis showed that the relative abundance of 14 genera was significantly different among all groups (LDA score > 3.0 or < –3.0, p < 0.05). LEfSe – linear discriminant analysis effect size, LDA – linear discriminant analysis, KEGG – Kyoto Encyclopedia of Genes and Genomes, COG – Clusters of Orthologous Groups, RDA – redundancy analysis
Spearman correlation analysis and PICRUSt prediction under PQQ supplement in the GD group. A) Kruskal-Wallis H test validated the differential distributed genera and C) the abundance of Lactobacillus among all 3 groups. B) LEfSe analysis showed that the relative abundance of 14 genera was significantly different among all groups (LDA score > 3.0 or < –3.0, p < 0.05). LEfSe – linear discriminant analysis effect size, LDA – linear discriminant analysis, KEGG – Kyoto Encyclopedia of Genes and Genomes, COG – Clusters of Orthologous Groups, RDA – redundancy analysis

Fig. 5.

Spearman correlation analysis and PICRUSt prediction under PQQ supplement in the GD group. D) The Heatmap of KEGG pathway, and E) the COG functional abundance box distribution based on the PICRUSt prediction among 3 groups. LEfSe – linear discriminant analysis effect size, LDA – linear discriminant analysis, KEGG – Kyoto Encyclopedia of Genes and Genomes, COG – Clusters of Orthologous Groups, RDA – redundancy analysis
Spearman correlation analysis and PICRUSt prediction under PQQ supplement in the GD group. D) The Heatmap of KEGG pathway, and E) the COG functional abundance box distribution based on the PICRUSt prediction among 3 groups. LEfSe – linear discriminant analysis effect size, LDA – linear discriminant analysis, KEGG – Kyoto Encyclopedia of Genes and Genomes, COG – Clusters of Orthologous Groups, RDA – redundancy analysis
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Fig. 5.

Spearman correlation analysis and PICRUSt prediction under PQQ supplement in the GD group. D) The Heatmap of KEGG pathway, and E) the COG functional abundance box distribution based on the PICRUSt prediction among 3 groups. F) RDA results of gut microbiota and environmental factors (T4, TRAB, IL6, TNFα, Nrf2 and HO1) of mice in 3 groups. G) Network Diagram based on the Collinearity Analysis in 3 groups. LEfSe – linear discriminant analysis effect size, LDA – linear discriminant analysis, KEGG – Kyoto Encyclopedia of Genes and Genomes, COG – Clusters of Orthologous Groups, RDA – redundancy analysis
Spearman correlation analysis and PICRUSt prediction under PQQ supplement in the GD group. D) The Heatmap of KEGG pathway, and E) the COG functional abundance box distribution based on the PICRUSt prediction among 3 groups. F) RDA results of gut microbiota and environmental factors (T4, TRAB, IL6, TNFα, Nrf2 and HO1) of mice in 3 groups. G) Network Diagram based on the Collinearity Analysis in 3 groups. LEfSe – linear discriminant analysis effect size, LDA – linear discriminant analysis, KEGG – Kyoto Encyclopedia of Genes and Genomes, COG – Clusters of Orthologous Groups, RDA – redundancy analysis

Fig. 5.

Spearman correlation analysis and PICRUSt prediction under PQQ supplement in the GD group. H) Spearman Correlation Analysis between samples and top 50 genera. LEfSe – linear discriminant analysis effect size, LDA – linear discriminant analysis, KEGG – Kyoto Encyclopedia of Genes and Genomes, COG – Clusters of Orthologous Groups, RDA – redundancy analysis
Spearman correlation analysis and PICRUSt prediction under PQQ supplement in the GD group. H) Spearman Correlation Analysis between samples and top 50 genera. LEfSe – linear discriminant analysis effect size, LDA – linear discriminant analysis, KEGG – Kyoto Encyclopedia of Genes and Genomes, COG – Clusters of Orthologous Groups, RDA – redundancy analysis
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