A systems medicine approach reveals disordered immune system and lipid metabolism in multiple sclerosis patients

Pazhouhandeh, Mehrdad; Sahraian, Mohammd Ali; Siadat, Seyed Davar; Fateh, Abolfazl; Vaziri, Farzam; Tabrizi, Fatemeh Haji Abas; Ajorloo, Faezeh; Arshadi, Arash Keshavarzi; Fatemi, Elnaz; Gavgani, Somayeh Piri; Mahboudi, Fereidoun; Jamnani, Fatemeh Rahimi

doi:10.1111/cei.13087

Cited by 16 publications

(14 citation statements)

References 130 publications

(252 reference statements)

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“…Furthermore, we identified the DEGs related to lipid metabolism according to the enriched GO terms and signaling pathways. Among the 72 DEGs related to lipid metabolism, 19 genes were enriched in the PPAR signaling pathway with the classic mediation of lipid metabolism [ 21 , 22 ]. Among these 19 genes, the RNA-seq data showed that the APOA1 , ADIPOQ , FABP3 , FABP4 , FABP7 , HMGCS2 , LPL and RXRG genes were downregulated but the ACSL1 , FABP5 , PCK2 , PDPK1 , PPARG , SCD , SCD5 , and SLC27A6 genes were upregulated ( P < 0.05 or P < 0.01) in the DIMFPs, which had an important regulatory effect on lipid metabolism [ 14 , 21 – 35 ].…”

Section: Discussionmentioning

confidence: 99%

Identification of the molecular regulation of differences in lipid deposition in dedifferentiated preadipocytes from different chicken tissues

Luo

Liu

et al. 2021

BMC Genomics

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Background A body distribution with high intramuscular fat and low abdominal fat is the ideal goal for broiler breeding. Preadipocytes with different origins have differences in terms of metabolism and gene expression. The transcriptome analysis performed in this study of intramuscular preadipocytes (DIMFPs) and adipose tissue-derived preadipocytes (DAFPs) aimed to explore the characteristics of lipid deposition in different chicken preadipocytes by dedifferentiation in vitro. Results Compared with DAFPs, the total lipid content in DIMFPs was reduced (P < 0.05). Moreover, 72 DEGs related to lipid metabolism were screened, which were involved in adipocyte differentiation, fatty acid transport and fatty acid synthesis, lipid stabilization, and lipolysis. Among the 72 DEGs, 19 DEGs were enriched in the PPAR signaling pathway, indicating its main contribution to the regulation of the difference in lipid deposition between DAFPs and DIMFPs. Among these 19 genes, the representative APOA1, ADIPOQ, FABP3, FABP4, FABP7, HMGCS2, LPL and RXRG genes were downregulated, but the ACSL1, FABP5, PCK2, PDPK1, PPARG, SCD, SCD5, and SLC27A6 genes were upregulated (P < 0.05 or P < 0.01) in the DIMFPs. In addition, the well-known pathways affecting lipid metabolism (MAPK, TGF-beta and calcium) and the pathways related to cell communication were enriched, which may also contribute to the regulation of lipid deposition. Finally, the regulatory network for the difference in lipid deposition between chicken DAFPs and DIMFPs was proposed based on the above information. Conclusions Our data suggested a difference in lipid deposition between DIMFPs and DAFPs of chickens in vitro and proposed a molecular regulatory network for the difference in lipid deposition between chicken DAFPs and DIMFPs. The lipid content was significantly increased in DAFPs by the direct mediation of PPAR signaling pathways. These findings provide new insights into the regulation of tissue-specific fat deposition and the optimization of body fat distribution in broilers.

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Section: Discussionmentioning

confidence: 99%

Identification of the molecular regulation of differences in lipid deposition in dedifferentiated preadipocytes from different chicken tissues

Luo

Liu

et al. 2021

BMC Genomics

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show abstract

“…Furthermore, we identi ed the DEGs related to lipid metabolism according to the enriched GO terms and signaling pathways. Among the 72 DEGs related to lipid metabolism, 19 genes were enriched in the PPAR signaling pathway with the classic mediation on lipid metabolism [34,35], and the enriched genes included the representative ACSL1, APOA1, ADIPOQ, FABP3, FABP4, FABP5, FABP7, HMGCS2, LPL, PCK2, PDPK1, PPARG, RXRG, SCD, SCD5 and SLC27A6, etc., which had the important regulation on lipid metabolism [21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37]. Therfore, it was considered that these genes and PPAR signaling pathway had the important effects in vitro on regulating the difference of lipid deposition between DIMPs and DAFPs of chicken.…”

Section: Discussionmentioning

confidence: 99%

Identification of molecular regulation on difference of lipid deposition in dedifferentiated preadipocytes from different chicken tissues

Luo

Liu

et al. 2021

Preprint

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Background: The body distribution with high intramuscular fat and low abdominal fat is ideal goal for broiler breeding. Preadipocytes with different origins have differences in metabolism and gene expression. This transcriptome analysis of intramuscular preadipocytes (DIMPs) and adipose tissue-derived preadipocytes (DAFPs) is aim to explore the characteristics in lipid deposition of different chicken preadipocytes by dedifferentiation in vitro. Results: Compared to DAFPs, the total lipid content was decreased (P <0.05) in DIMFPs after two days with 100% confluence. Moreover, 72 DEGs related to lipid metabolism were screened, which are involved in the adipocyte differentiation, fatty acid transport and fatty acid synthesis, lipid stabilization, and lipolysis. Among the 72 DEGs, 19 DEGs were enriched in the PPAR signaling pathway, indicating a main contribution to the regulation of the difference of lipid deposition between DAFPs and DIMFPs. Among these 19 genes, the representative APOA1, ADIPOQ, FABP3, FABP4, FABP7, HMGCS2, LPL and RXRG genes were down-regulated, but ACSL1, FABP5, PCK2, PDPK1, PPARG, SCD, SCD5, SLC27A6 genes were up-regulated (P < 0.05 or P < 0.01) in the DIMFPs. In addition, the well-known pathways affecting lipid metabolism (MAPK-, TGF beta-, Calcium-, PPAR signaling pathway) and the pathways related to cell communication were enriched, which may also contribute to the regulation of lipid deposition. Finally, the regulatory network for the difference of lipid deposition between chicken DAFPs and DIMFPs were proposed based on the above information.Conclusions: Our data suggested the difference of lipid deposition between DIMPs and DAFPs of chicken in vitro, and proposed the molecular regulatory network for the difference of lipid deposition between chicken DAFPs and DIMFPs. The lipid content was significantly increased in DAFPs by the direct mediation of PPAR signaling pathways. These findings provide new insights into the regulation of tissue-specific fat deposition and optimizing body fat distribution in broilers.

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“…Speci cally, EPHA4 is the most abundant ephrin receptor, which interacted with almost all ephrin ligands, ranging from effects on in ammatory responses to axonal degeneration and regeneration in the central nervous system, especially in neurological functional recovery by regulating various processes, such as neuroin ammation, angiogenesis, neurogenesis, axonal reorganization and synaptic plasticity [20,30]. Although update to now, there is no available evidence proved the function of EPHA4 in the pathogenesis of SLE, EPHA4 as a possible in ammatory mediator may contribute to the immunopathological disease like multiple sclerosis and neuropsychiatric disorder in SLE [31][32][33][34][35][36]. Occasionally, in our study, we have found a signi cant decreased protein level of EPHA4 in the urine of JSLE patients, which may imply a potential role of EPHA4 in neurodevelopment of JSLE patients via PI3K-Akt signaling pathway.…”

Section: Discussionmentioning

confidence: 99%

Proteomic Analysis for Identification of Novel Urinary Biomarkers in Juvenile Systemic Lupus Erythematosus

Zhang¹,

Cai

Zhi

et al. 2020

Preprint

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Background: To identify new markers of juvenile systemic lupus erythematosus (JSLE) that facilitate patient stratification and prognosis is quite important. Therefore, our aim of the present study is to analyze alteration of protein expression and potential valuable biomarkers in juvenile systemic lupus erythematosus (JSLE) urine. Methods: Based on this aim, proteomics assay analyzed the changes of urinary proteins in study groups consisting of 9 healthy controls, 9 inactive JSLE and 10 active JSLE patients. And the correlationship between clinical characteristics of JSLE patients and new biomarkers discovered from proteomics assay was qualified.Results: We have identified a group of 105 differentially expressed proteins with ≥1.3 fold up-regulation or ≤0.77 fold down-regulation in JSLE patients. In gene ontology and functional enrichment analysis, we discovered these proteins were involved in several important biological processes such as acute phase inflammatory responses, complement activation, hemostasis, and immune system regulation. Interestingly, we found that Ephrin type-A receptor 4 (EPHA4) and Vitronectin (VTN) were significantly reduced in the urine of both inactive and active JSLE patients. Especially, the urinary VTN was also linear correlated with clinical characteristics of JSLE. Conclusion: In summary, this study provided a reliable proteomic reference profile for JSLE. Patients with active and inactive JSLE have differentially obvious metabolic proteins in the urine. VTN could be a specific diagnostic biomarker to distinguish inactive and active JSLE. These identified proteins as new biomarkers in this study can warrant some further exploiting in a larger prospective validation study.

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A systems medicine approach reveals disordered immune system and lipid metabolism in multiple sclerosis patients

Cited by 16 publications

References 130 publications

Identification of the molecular regulation of differences in lipid deposition in dedifferentiated preadipocytes from different chicken tissues

Identification of the molecular regulation of differences in lipid deposition in dedifferentiated preadipocytes from different chicken tissues

Identification of molecular regulation on difference of lipid deposition in dedifferentiated preadipocytes from different chicken tissues

Proteomic Analysis for Identification of Novel Urinary Biomarkers in Juvenile Systemic Lupus Erythematosus

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