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Integrative Proteomics-Metabolomics Strategy for Pathological Mechanism of Vascular Depression Mouse Model
Hongxia Zhao1, Hongli Du2, Min Liu3
1School of Pharmacy, Second Military Medical University , Shanghai 200433, China.
Insights
Vascular depression (VD) research is advanced by a new study integrating proteomics and metabolomics in mice. This approach identifies key protein and metabolite changes, offering novel targets for understanding and treating VD.
Area of Science:
- Neuroscience
- Biochemistry
- Genomics
Background:
- Vascular depression (VD) is a growing subtype of depression linked to vascular issues.
- The underlying mechanisms and basic research for VD remain inadequately understood.
- Existing research lacks comprehensive molecular insights into VD pathogenesis.
Purpose of the Study:
- To establish a protein-metabolite regulatory network in a murine VD model.
- To elucidate the comprehensive impact of VD on organismal systems.
- To identify potential therapeutic targets and biomarkers for VD.
Main Methods:
- Combined LC-MS-based proteomics and metabolomics analyses.
- Utilized isobaric tags for relative and absolute quantification (iTRAQ) for protein analysis.
- Constructed a protein-to-metabolite regulatory network using Ingenuity Pathway Analysis.
- Validated key molecular changes using LC-MS/MS and Western blotting.
Main Results:
- Identified 44 differential metabolites and 304 differential proteins in the hippocampus of VD mice.
- Revealed dysregulation in neuroplasticity, neurotransmitter transport, neuronal cell proliferation/apoptosis, and amino acid, lipid, and energy metabolism.
- Established a validated protein-metabolite regulatory network.
Conclusions:
- The study provides a comprehensive molecular framework for understanding VD.
- Identified proteins and metabolites offer targeted directions for future VD mechanism research.
- The integrative proteomics and metabolomics strategy serves as a precise and credible approach for VD research and biomarker screening.
Abstract:
Vascular depression (VD), a subtype of depression, is caused by vascular diseases or cerebrovascular risk factors. Recently, the proportion of VD patients has increased significantly, which severely affects their quality of life. However, the current pathogenesis of VD has not yet been fully understood, and the basic research is not adequate. In this study, on the basis of the combination of LC-MS-based proteomics and metabolomics, we aimed to establish a protein metabolism regulatory network in a murine VD model to elucidate a more comprehensive impact of VD on organisms. We detected 44 metabolites and 304 proteins with different levels in the hippocampus samples from VD mice using a combination of metabolomic and proteomics analyses with an isobaric tags for relative and absolute quantification (iTRAQ) method. We constructed a protein-to-metabolic regulatory network by correlating and integrating the differential metabolites and proteins using ingenuity pathway analysis. Then we quantitatively validated the levels of the bimolecules shown in the bioinformatics analysis using LC-MS/MS and Western blotting. Validation results suggested changes in the regulation of neuroplasticity, transport of neurotransmitters, neuronal cell proliferation and apoptosis, and disorders of amino acids, lipids and energy metabolism. These proteins and metabolites involved in these dis-regulated pathways will provide a more targeted and credible direction to study the mechanism of VD. Therefore, this paper presents an approach and strategy that was applied in integrative proteomics and metabolomics for research and screening potential targets and biomarkers of VD, which could be more precise and credible in a field lacking adequate basic research.
