PROTEOMICS – Clinical Applications最新文献

Purpose: Chronic kidney disease (CKD) causes detrimental systemic effects, including inflammation or apoptosis, which lead to substantial morbidity and mortality. However, the causal effect of reduced kidney function on systemic proteomic signatures is incompletely understood.

Methods: We performed an integrated Mendelian randomization (MR) and observational analyses to identify the causal association between kidney function and plasma protein levels, based on 1815 plasma protein profiles in 50,407 UK Biobank participants and the CKDGen Phase 4 genome-wide association study (GWAS) meta-analysis for the genetic instruments of eGFR.

Results: The MR analysis revealed 383 plasma proteins causally associated with eGFR. Reduced kidney function was found to be causally associated with an increase in the plasma levels of 381 proteins, among which TNF and IGFBP4 were increased, while the level of two proteins, NPHS1 and SPOCK1, decreased. Apoptosis-related pathway was significantly enriched in the gene-set enrichment analysis. In network analysis, TNF was identified as a hub protein with multiple linkages to molecules included in the TNF-signaling pathways, involved in inflammation, fibrosis, and apoptosis.

Conclusions: In this proteo-genomic analysis, we identified 383 plasma proteins causally associated with eGFR, highlighting TNF-associated pathways as pathologically relevant processes in kidney disease progression, systemic inflammation, and organ fibrosis, warranting further investigation.

Purpose: Diabetes mellitus (DM) is a major cause of end-stage kidney disease (ESKD), with kidney transplantation being the preferred treatment. However, post-transplant diabetes mellitus (PTDM) increases mortality and graft loss. While PTDM and Type 2 diabetes mellitus (T2DM) share risk factors, their mechanisms differ, particularly in diabetic nephropathy (DN). This study aimed to investigate the molecular differences in PTDM by mapping the proteomes of proximal tubuli and serum in normoglycemic (NG), pre-transplant T2DM, and PTDM patients one year post-transplantation. Experimental Design Proteomic analysis was performed on microdissected proximal tubular cells and serum samples from kidney transplant recipients categorized as NG, pre-transplant T2DM, or PTDM at one year post-transplantation. Mass spectrometry was used to identify differentially expressed proteins. Data analyses were performed using gene ontology databases and pathway analysis.

Results: Proteomic analysis revealed key differences, including significant dysregulation of mitochondrial proteins and lipid metabolism pathways in PTDM patients compared to T2DM and NG groups. Additionally, we observed distinct serum patterns of cholesterol metabolism dysregulation in PTDM, highlighting a complex interplay between fatty acid metabolism, mitochondrial dysfunction and systemic lipid dysregulation that may drive renal injury in PTDM-related DN.

Conclusions and clinical relevance: This pilot study is the first to perform proteomic analysis on both microdissected tubular cells and serum from post-transplant PTDM, pre-transplant T2DM and NG transplant recipients. The proteomic differences between PTDM and T2DM could help to develop targeted therapies and early diagnostic markers, ultimately improving transplant outcomes and patient management. Further research is needed to validate these findings and explore their therapeutic potential.

Introduction: Percutaneous transluminal coronary angioplasty (PTCA) is an effective procedure to decrease the severity of stenotic coronary atherosclerotic lesions. However, its long-term success is limited by the formation of restenosis or neointima by increased proliferation of smooth muscle cells (SMCs) and synthesis of extracellular matrix. Polypeptide growth factors are potent SMC mitogens and are involved in SMC proliferation and extracellular matrix (ECM) synthesis. In this line, inhibition of de novo protein synthesis might be beneficial.

Methods: We examined the effects of different concentrations of translational inhibitor puromycin on SMC proliferation and apoptosis, in vitro. Further, we examined the effects of local administration of puromycin in a rabbit balloon injury model of the iliac artery.

Results: Injection of puromycin or its vehicle was performed with an infusion-balloon catheter directly into the vessel wall during angioplasty. PTA in the vehicle group resulted in neointima formation 3 weeks after the vascular intervention. In contrast, puromycin treatment resulted in a significant reduction of intima-media ratio. We observed decreased elastin and collagen III synthesis in puromycin-treated animals. With proteomics, we could demonstrate reduced protein expression of lamin, vimentin, alpha-1 antitrypsin, alpha-actin allowing puromycin treatment. In in vitro experiments, puromycin decreased SMCs proliferation (i.e., BrdU incorporation) following FCS stimulation.

Perspective: Based on the data from our animal experiments, aministration of puromycin directly into the vessel wall during angioplasty may be effective in preventing or reducing restenosis in humans.

Saliva is a child appropriate biofluid, but it has not previously been used to evaluate the systemic response to burn injury in children. The aim of this study was to investigate the salivary proteome of children with small area thermal skin burns relative to different burn characteristics (mechanism, time to re-epithelialization and risk of emotional distress). SWATH Mass Spectrometry was used to quantify the abundance of 742 proteins in the saliva of children with burns (n = 22) and healthy controls (n = 37). Eight proteins were differentially abundant in the saliva of children with burns compared to healthy children, and these were associated with immune processes, epidermal cell differentiation and transferrin receptor binding. Eleven proteins were differentially abundant in patients with burns of different mechanisms. Scald burns had an over-representation of immune/inflammatory response processes, and contact burns had an over-representation of cornification, intermediate filament assembly and cell death cellular processes. Four proteins were elevated in patients who were at high risk for emotional distress and 15 proteins were correlated with time to wound re-epithelialization. This pilot study proves that saliva can be used for paediatric biomarker discovery and can be used as a diagnostic and prognostic sample to investigate systemic changes in a paediatric burn cohort.

Purpose: Embryo-maternal signaling during the establishment of pregnancy in horses remains one of the biggest mysteries in large animal physiology. Early pregnancy loss represents a major source of economic loss to the breeding industry. This study aimed to investigate the systemic changes associated with early pregnancy by mapping the proteome of blood plasma at 14 days in pregnant and non-pregnant mares.

Experimental design: Plasma proteomes were analysed in commercially bred pregnant (n = 17) and non-pregnant (n = 17) Thoroughbred mares at 14 days after ovulation, using high-resolution mass spectrometry. Day 14 histotroph and yolk sac fluid were also profiled and datasets were integrated through pathway analysis.

Results: We identified 229 total protein IDs, with 12 increased and 10 decreased significantly in pregnant versus non-pregnant plasma. To gain functional insight, these data were aligned with proteomes of 14-day pregnant mare uterine fluid (n = 4; 1358 IDs) and conceptus fluid (soluble proteins within the yolk sac fluid; n = 4; 1152 IDs), and further interrogated using gene ontology databases and pathway analysis.

Conclusions and clinical relevance: These analyses identified consistent systemic changes in the mare's proteome that indicate a profound and specific immune response to early pregnancy, which appears to precede the systemic endocrine response to pregnancy. Integrated pathway analysis suggests that embryo-maternal interactions in early pregnancy may mimic elements of the virus-host interaction to modulate the maternal immune response. Transthyretin (TTR) and uteroglobin (SCGB1A1) were respectively down- and upregulated in plasma while also present in uterine fluid, and are proposed to be key proteins in early pregnancy establishment. These findings contribute significantly to our knowledge of early pregnancy in the mare and identify potential new avenues for developing clinical approaches to reduce early embryo loss.

Epithelial ovarian cancer (EOC) is the most lethal gynecologic malignancy which mainly consists of serous, mucinous, clear cell, and endometrioid subtypes. Due to the lack of classic symptoms at an early stage, EOC usually presented as advanced tumors with local and/or distant metastasis. Although a large portion of EOC was initially platinum-sensitive, most patients would acquire resistance to common chemotherapeutic agents. These aforementioned issues lead to a challenge for clinical treatments and unsatisfying outcomes. Previous studies have demonstrated the genetic features of EOC are hard to target and the alterations at DNA and RNA levels are not fully represented at the protein expression profiles which made it more complex. In recent years, a panel of studies attempted to explore the key proteins involved in the development and progression of EOC using high-throughput proteomic technologies. We herein summarized them to provide a full view of this topic. Trial Registration: ClinicalTrials.gov identifier: NCT046698990.

Purpose: Multiple Sclerosis is an inflammatory neurodegenerative disease characterised by blood-brain barrier dysfunction and leukocyte infiltration into the CNS. Platelets are best known for their contributions to haemostasis, however, upon activation, platelets release an abundance of soluble and vesicular-associated proteins, termed the platelet releasate (PR). This milieu contains numerous inflammatory and vasoactive proteins, that can attract leukocytes and alter endothelial permeability.

Experimental design: We aimed to characterise the PR of Relapsing-Remitting multiple sclerosis (RRMS) patients, previously characterized regarding thrombin generation dynamics compared to healthy controls. We carried out LFQ proteomic profiling of the PR from 15 RRMS and 19 aged-matched healthy controls.

Results: We identified 9 proteins increased and 16 proteins decreased in the PR of RRMS patients. Platelet/endothelial cell-adhesion molecule-1 (PECAM-1) was uniquely found in healthy control PR and circulating levels of PECAM-1 were significantly lower in RRMS patient samples. GO analysis revealed a strong link between altered proteins and extracellular vesicles (EVs). Small EV levels were significantly reduced in RRMS PR compared to healthy PR and showed a negative correlation with PECAM-1 levels in RRMS plasma.

Conclusions and clinical relevance: Our findings suggest that platelet reactivity may be linked to disease activity, even in periods of disease remission.

Determination of the changes in protein structure is crucial for a better understanding of their function and properties, which is highly important in identifying the causes of the disease, new drug development, and clinical applications. The Ramachandran plot, displaying the set of torsional angles, phi (Φ) and psi (Ψ), of the protein backbone, serves as a popular and convenient tool for secondary structure analysis and interpretation. However, identifying subtle changes in protein structure is often hindered in traditional Ramachandran plot, especially with the large amount of data generated by molecular dynamics (MD) simulations. In this paper, we proposed a useful and efficient tool, that is, differential Ramachandran plot (dRama), which enables to compare protein structures and extract the differences, providing a highly readable graphical representation. dRama is available at: https://github.com/MaksWolf44/dRama.

Purpose: Breast cancer is a significant threat to women's health. Precise prognosis prediction for breast cancer can help doctors implement more rational treatment strategies. Artificial intelligence can assist doctors in decision-making and enhance prediction accuracy.

Experimental design: In this paper, a deep learning model ECMHA-PP (Energy Constrained Multi-Head Self-Attention based Prognosis Prediction) is proposed to predict the prognosis of breast cancer. ECMHA-PP utilizes patients' clinical data and extracts features through a cross-position mix and a channel mix multi-layer perceptron. Then, it incorporates an energy-constrained multi-head self-attention layer to improve feature extraction capability. The source code of ECMHA-PP has been hosted on GitHub and is available at https://github.com/xiaoliu166370/ECMHA-PP.

Results: To evaluate our proposed method, prognostic prediction experiments were performed on the METABRIC dataset, yielding outstanding results with an average accuracy of 93.0% and an average area under the curve of 0.974. To further validate the model's performance, we conducted tests on another independent dataset, BRCA, achieving an accuracy of 87.6%.

Conclusions and clinical relevance: In comparison with other widely used advanced methods, ECMHA-PP demonstrated higher comprehensive performance, making it a reliable prognostic prediction model for breast cancer. Given its robust feature extraction and prediction capabilities.

Liquid chromatography, when used in conjunction with mass spectrometry (LC/MS), is a powerful tool for conducting accurate and reproducible investigations of numerous metabolites in natural products (NPs). LC/MS has gained prominence in metabolomic research due to its high throughput, the availability of multiple ionization techniques and its ability to provide comprehensive metabolite coverage. This unique method can significantly influence various scientific domains. This review offers a comprehensive overview of the current state of LC/MS-based metabolomics in the investigation of NPs. This review provides a thorough overview of the state of the art in LC/MS-based metabolomics for the investigation of NPs. It covers the principles of LC/MS, various aspects of LC/MS-based metabolomics such as sample preparation, LC modes, method development, ionization techniques and data pre-processing. Moreover, it presents the applications of LC/MS-based metabolomics in numerous fields of NPs research such as including biomarker discovery, the agricultural research, food analysis, the study of marine NPs and microbiological research. Additionally, this review discusses the challenges and limitations of LC/MS-based metabolomics, as well as emerging trends and developments in this field.