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PubMed2025

Proteomic signature of dementia risk in type 2 diabetes.

INTRODUCTION: Type 2 diabetes (T2D) significantly increases dementia risk, yet the molecular mechanisms underlying this association remain unclear. OBJECTIVES: This study aimed to identify protein signatures that distinguish dementia risk in T2D patients, develop a proteomic prediction model, and elucidate biological pathways connecting T2D and dementia. METHODS: We analyzed 2,920 plasma proteins from 52,958 participants (including 3,292 with T2D) in the UK Biobank Pharma Proteomics Project with a median follow-up of 14.6 years. Cox regression models with interaction terms identified T2D-specific protein associations with dementia risk. Machine learning models were developed to predict dementia in T2D patients. Pathway analysis and weighted gene co-expression network analysis identified biological mechanisms linking T2D and dementia. RESULTS: We identified 471 proteins with significant interaction effects between T2D and dementia risk. In non-T2D individuals, elevated levels of neuronal pentraxin receptor (NPTXR, HR = 0.74, 95 %CI:0.66-0.83) and carbonic anhydrase 14 (CA14, HR = 0.67, 95 %CI:0.60-0.75) were exclusively associated with decreased dementia risk. Conversely, in T2D patients, elevated rho guanine nucleotide exchange factor 12 (ARHGEF12, HR = 1.45, 95 %CI:1.10-1.91) was specifically associated with increased dementia risk. A 51-protein model accurately predicted 15-year dementia risk in T2D patients (AUC = 0.835, C-index = 0.829), outperforming conventional clinical risk scores and maintaining high accuracy for Alzheimer's disease and vascular dementia. Pathway analysis revealed enrichment of IL6-JAK-STAT3 signaling in T2D-related dementia, while dysregulation of fatty acid metabolism was specific to T2D-associated Alzheimer's disease. CONCLUSIONS: This large-scale proteomic analysis identifies specific molecular signatures that differentiate dementia risk in diabetic and non-diabetic populations, with potential applications for early risk stratification and targeted interventions. The identified pathways provide novel insights into the pathophysiological processes connecting T2D and dementia and suggest potential therapeutic targets.

Humans↗

PubMed2026

Urban heat island and risk of rheumatoid arthritis: Insights from genetic predisposition and proteomics.

BACKGROUND: Urban heat island (UHI) exposure is an increasingly common consequence of urbanization and climate warming, but its association with rheumatoid arthritis (RA) risk remains unclear. OBJECTIVE: To investigate the association between UHI exposure and incident RA, and to further assess the roles of genetic susceptibility and plasma proteomic profiles in this association. METHODS: This study included 400,628 urban residents with UHI exposure data and free of RA at baseline. Cox proportional hazards models were used to evaluate the association between UHI exposure and incident RA. Polygenic risk scores were used to assess effect modification by genetic susceptibility. Proteomic analyses identified candidate proteins and enriched pathways underlying the association. Mendelian randomization, colocalization, and mediation analyses assessed causal relevance and mediation. RESULTS: Over a median follow-up of 14.05 years, 5397 incident RA cases were documented. Each standard-deviation increase in UHI exposure was associated with a 17% higher risk of RA. This association was more pronounced among older adults and individuals with lower socioeconomic status. An additive interaction was observed between UHI exposure and genetic risk for RA. Proteomic analyses suggested that this association may involve not only canonical immune-inflammatory pathways, but also hypoxia response and protein transport, with CD40, VCAM1, and SUGP1 emerging as potential molecular mediators. CONCLUSIONS: UHI exposure may be a modifiable environmental risk factor for RA and provide new insights into the biological mechanisms underlying this association.

Humans↗

PubMed2005

Proteomics analysis of human cerebrospinal fluid.

Cerebrospinal fluid (CSF) is secreted from several different central nervous system (CNS) structures, and any changes in the CSF composition will accurately reflect pathological processes. Proteomics offers a comprehensive bird's eye view to analyze CSF proteins at a systems level. This paper reviews the variety of analytical methods that have been used for proteomics analysis of CSF, including sample preparation, two-dimensional liquid and gel electrophoresis, mass spectrometry, bioinformatics, and non-gel methods. The differentially expressed CSF proteins that have been identified by proteomics methods are discussed.

Cerebrospinal Fluid Proteins↗

PubMed2005

Proteomics of bronchoalveolar lavage fluid.

Lung diseases are essentially multi-factorial diseases that require a global analysis, and thus, cannot be understood through the sole analysis of individual or small numbers of genes. Proteome analysis has rapidly developed in the post-genome era and is now widely accepted as the obligated complementary technology for genetic profiling. It has been shown to be a powerful tool for the study of human diseases and for identifying novel prognostic, diagnostic and therapeutic markers. During last years, proteomic approaches applied to lung diseases are centred on the analysis of proteins in samples, such as cell cultures, biopsies and physiological fluids like serum and, especially, bronchoalveolar lavage fluid (BALF). BALF is presently the most common way of sampling the components of the epithelial lining fluid (ELF) and the most faithful reflect of the protein composition of the pulmonary airways. This review focuses on the state of the investigations of BALF proteome and its powerful contribution both to a better knowledge of the lung structure at the molecular level and to the study of lung disorders at the clinical level.

Biomarkers↗

PubMed2006

Two-dimensional electrophoresis in proteome expression analysis.

Cell proteomes are complex, given they consist of several thousand proteins. Two-dimensional electrophoresis (2DE) is unique not only for its ability to simultaneously separate thousands of proteins but also for detecting post- and co-translational modifications, which cannot be predicted from genome sequences. This review will describe the protocols applied to prepare 2D gels properly, and analyse and summarise the major challenges for successful proteome analysis using 2DE, i.e. the ability to analyse very alkaline, hydrophobic and/or low or high M(r) proteins with high resolution and the ability to detect minor components. Challenges involving sample preparation and solubilisation prior to the first dimension IEF/IPG step will be studied in depth. Sample preparation is crucial in 2DE studies and greatly influences other stages of the technique. It is the aim of this review not only to describe the challenges and limitations of 2DE but also to suggest the avenues, the evolution, the potential and the future of 2DE in proteomics.

Electrophoresis, Gel, Two-Dimensional↗

PubMed2026

Integrated histone and proteome analyses reveal convergent and distinct hepatotoxic mechanisms of tenuazonic acid and deoxynivalenol.

Mycotoxins are widespread dietary contaminants whose health impacts are expected to intensify under climate change. Although their mechanisms of toxicity remain incompletely understood, epigenetic dysregulation has been increasingly implicated. Here, mass spectrometry-based multi-omics was used to profile histone post-translational modifications and proteome dynamics in HepG2 cells exposed to seven mycotoxin conditions. Time-resolved analyses identified tenuazonic acid as the dominant cellular disruptor, inducing alterations in H3K27 and H1 variants, and revealing a previously unrecognized oxidative modification of the H1.0 N-terminal methionine (H1.0N-term0AcM0Ox) that retains the protein's N-terminal acetylation. An Alternaria toxin mixture induced similar H1 responses, largely driven by tenuazonic acid, while deoxynivalenol produced convergent chromatin and proteomic alterations. Proteomic remodeling was characterized by increased protein translation, reduced mitochondrial complex IV expression, and impaired cholesterol biosynthesis, whereas sterigmatocystin activated DNA replication and repair pathways. Together, these findings demonstrate that mycotoxins disrupt chromatin organization, protein synthesis, and lipid metabolism, providing toxicological insight into hepatocellular dysfunction. These findings warrant further validation and mechanistic investigation in future hypothesis-driven studies of mycotoxin exposure.

Trichothecenes↗

PubMed2026

Role of omentin-1 in the global proteome of porcine pituitary cells: insights into proliferation- and apoptosis-related processes.

The anterior pituitary integrates endocrine regulation, cellular growth, and adaptive responses. Adipokines, secreted mainly by adipose tissue, act as hormonal signals linking metabolism, inflammation, appetite, and reproduction. They regulate hypothalamic-pituitary-ovarian axis by modulating hormone secretion and intracellular signaling. The presence of adipokine receptors in anterior pituitary suggests local metabolic-endocrine interactions. Omentin-1, predominantly expressed in visceral adipose tissue, participates in glucose metabolism and ovarian steroid regulation. Recent findings indicate that omentin-1 modulates tropic hormones, their receptors, and adipokine balance in anterior pituitary cells. We hypothesized that omentin-1 affects protein expression and signaling pathways involved in pituitary cell proliferation and apoptosis. This study examined its effects in anterior pituitary cells from Large White and Meishan pigs. Proteomic analysis identified 230 candidate differentially abundant proteins after omentin-1 treatment: 30 downregulated and 3 upregulated in Large White pigs, and 107 downregulated and 90 upregulated in Meishan pigs, associated with enriched 116 Gene Ontology terms. Key proteins were associated with cell cycle, DNA replication, gene expression, and posttranscriptional/posttranslational regulation. Responses differed between breeds. CDK5RAP2 and SIX1 were linked to proliferative control in Large White pigs, whereas AKT1S1 and RHOA were among the proteins associated with the broader proteomic response observed in Meishan pigs. Meishan pigs showed dynamic apoptotic protein regulation, including HTRA2, PARP2, and DFFA. Complementary in vitro experiments demonstrated that omentin-1 downregulated cyclins and caspase-3, upregulated BCL2, increased BCL2/BAX ratio, and modulated ERK1/2, AKT, AMPKα, and STAT3 phosphorylation. Together, these findings suggest that omentin-1 modulates proteomic networks and intracellular signaling associated with anterior pituitary cell function during the mid-luteal phase of the estrous cycle.

Animals↗

PubMed2024

Secretome Analysis Using Affinity Proteomics and Immunoassays: A Focus on Tumor Biology.

The study of the cellular secretome using proteomic techniques continues to capture the attention of the research community across a broad range of topics in biomedical research. Due to their untargeted nature, independence from the model system used, historically superior depth of analysis, as well as comparative affordability, mass spectrometry-based approaches traditionally dominate such analyses. More recently, however, affinity-based proteomic assays have massively gained in analytical depth, which together with their high sensitivity, dynamic range coverage as well as high throughput capabilities render them exquisitely suited to secretome analysis. In this review, we revisit the analytical challenges implied by secretomics and provide an overview of affinity-based proteomic platforms currently available for such analyses, using the study of the tumor secretome as an example for basic and translational research.

Humans↗

PubMed2024

Proteomic Heterogeneity of the Extracellular Matrix Identifies Histologic Subtype-Specific Fibroblast in Gastric Cancer.

Gastric cancer (GC) is a highly heterogeneous disease regarding histologic features, genotypes, and molecular phenotypes. Here, we investigate extracellular matrix (ECM)-centric analysis, examining its association with histologic subtypes and patient prognosis in human GC. We performed quantitative proteomic analysis of decellularized GC tissues that characterizes tumorous ECM, highlighting proteomic heterogeneity in ECM components. We identified 20 tumor-enriched proteins including four glycoproteins, serpin family H member 1 (SERPINH1), annexin family (ANXA3/4/5/13), S100A family (S100A6/8/9), MMP14, and other matrisome-associated proteins. In addition, histopathological characteristics of GC reveals differential expression in ECM composition, with the poorly cohesive carcinoma-not otherwise specified (PCC-NOS) subtype being distinctly demarcated from other histologic subtypes. Integrating ECM proteomics with single-cell RNA sequencing, we identified crucial molecular markers in the PCC-NOS-specific stroma. PCC-NOS-enriched matrisome proteins and gene expression signatures of adipogenic cancer-associated fibroblasts (CAFadi) are closely linked, both associated with adverse outcomes in GC. Using tumor microarray analysis, we confirmed the CAFadi surface marker, ATP binding cassette subfamily A member 8 (ABCA8), predominantly present in PCC-NOS tumors. Our ECM-focused analysis paves the way for studies to determine their utility as biomarkers for patient stratification, offering valuable insights for linking molecular and histologic features in GC.

Humans↗

PubMed2026

Subcellular Proteomic Analyses Reveal REEP5 Knockdown in the Mouse Heart Disrupts Mitochondrial Networks.

Receptor Expression-Enhancing Protein 5 (REEP5) is a cardiac-enriched, membrane-shaping protein localized to the sarco(endo)plasmic reticulum (SR/ER), where it supports membrane network architecture and cardiomyocyte function. While REEP5 has been implicated in calcium handling and contractility, its role in regulating inter-organelle communication and mitochondrial homeostasis remains less well-understood. In this study, we used recombinant adeno-associated virus serotype 9-mediated shRNA knockdown of Reep5 in mouse hearts, combined with subcellular fractionation and data-independent acquisition mass spectrometry, to define proteomic remodeling across microsomal (SR/ER), mitochondrial, and cytosolic compartments. Loss of REEP5 altered the composition of SR/ER membrane-shaping proteins, including upregulation of RTN4, ATL3, and CKAP4, suggesting a partial compensatory response. Microsomal, mitochondrial and cytosolic proteomes exhibited broad reorganization, with enrichment of proteins involved in redox adaptation and proteostasis, alongside depletion of mitochondrial import machinery and antioxidant enzymes. Imaging of isolated cardiomyocytes confirmed fragmented mitochondrial networks and increased reactive oxygen species, consistent with proteomic signatures of disrupted mitochondrial dynamics and oxidative stress. Gene ontology enrichment across all fractions highlighted widespread dysregulation in organelle-specific processes, including translation, protein localization, and metabolic remodeling. Notably, several altered pathways converged on mitochondria-associated membranes, suggesting that REEP5 may support SR/ER-mitochondria tethering and functional crosstalk. These findings position REEP5 as a key regulator of organelle homeostasis in the heart and underscore how its loss disrupts mitochondrial integrity and inter-organelle communication across cellular compartments.

Animals↗

PubMed2026

Proteome Unravels Mechanism Differences in Embryogenesis Between Honey Bee Drone and Worker (Apis mellifera L.).

The physiological and social behaviors differ widely between honeybee workers and drones. All the organ rudiments of adult bees are formed during the embryonic stage. The initial molecular bases at the proteomic level for both embryonic developments have been identified, but a comprehensive understanding of the significant events involved in embryonic establishment remains elusive. To elucidate the molecular regulatory mechanisms underlying tissue differentiation during the embryogenesis of drones and workers, we implemented a state-of-the-art approach that combines in-hive inspection and targeted sampling (at nine embryogenesis stages) with high-throughput proteomics technology to investigate the developmental differences. In-hive inspection of hatching timing revealed an average developmental gap of approximately 3.6 h between the two embryos. Furthermore, proteomic analyses indicate that drone and worker embryos adopt distinct developmental strategies. Notably, proteins involved in fatty acid metabolism and key biological pathways related to organ formation-such as the Hedgehog and Wnt signaling pathways-are activated earlier in drones, suggesting that tissue development begins sooner in drone embryos than in workers. Additionally, the upregulation of cytoskeletal proteins and antioxidants in drone embryos likely supports their larger cell size and higher metabolic stress, reflecting distinct molecular characteristics of male development. Ribosomal proteins essential for biosynthetic support remain consistently expressed throughout the late stages in male embryos, indicating that drone embryogenesis lasts longer than that of workers. This work provides novel insights into the molecular foundations of honeybee embryogenesis and lays both theoretical and practical groundwork for future research into the mechanisms driving embryonic development.

Animals↗

PubMed2026

Proteomic analysis reveals early pathological defects in corticospinal motor neurons of a spastin model of hereditary spastic paraplegia, which are improved by NU-9 treatment.

Upper motor neuron (UMN) degeneration is a characteristic feature of hereditary spastic paraplegia (HSP), a genetically heterogeneous heritable neurodegenerative disorder resulting from mutations in over ninety genes. The mutations in the SPAST gene, which encodes the microtubule-severing protein spastin, are responsible for about 40% of all HSP cases. To date, the cellular and molecular mechanisms linking mutant spastin protein to UMN vulnerability in HSP patients remain unknown and there are no disease modifying therapies. To address this knowledge gap, we isolated pure populations of corticospinal motor neurons (CSMN; a.k.a. UMN in mice) from SPASTC448Y-UeGFP reporter mice at two pre-symptomatic time points and performed bottom-up proteomic analyses to reveal changes in their proteome that informs the underlying causes of their initial vulnerability. We find dynamic changes in their proteome and that limitations with cytoarchitectural integrity and stability of key organelles contribute to their neuronal vulnerability. Since the compound NU-9 was shown to improve similar cellular problems in CSMN that are diseased due to misfolded SOD1 toxicity and TDP-43 pathology, we further investigated its effect on the well-established pathological features of HSP that are recapitulated in the SPASTC448Y mice. We find that NU-9 treatment (100 mg/kg, for 100 days) significantly prevented degeneration of corticospinal axons, restored the integrity of mitochondria and endoplasmic reticulum, and reduced the presence of electron-dense accumulations in the CSMN of SPASTC448Y mice.

Animals↗

PubMed2004

Rice proteomics: recent developments and analysis of nuclear proteins.

Rice is the most important cereal crop in Asia, and is considered as a model cereal plant for genetic and molecular studies. An immense progress has been made in rice genome sequence analysis during the last decade. This prompted the researcher to identify the functions, modifications, and regulations of every encoded protein. Proteome analysis provides information to predict the translation and relative concentration of gene products, including the extent of modification, none of which can be accurately predicted from the nucleic acid sequence alone. During the last couple of years, considerable researches were conducted to analyze rice proteome, and only recently a remarkable progress has been made to systematically analyze and characterize the functional role of various tissues and organelles in rice. In this review, the rice proteomic research has been compiled and also presented a comprehensive analysis of rice nuclear proteins. In rice nucleus, 549 proteins were resolved using 2D-PAGE. Among them, 257 proteins were systematically analyzed by Edman sequencing and mass spectrometry and identified 190 proteins following database searching (http://gene64.dna.affrc.go.jp/RPD/main.html). The identified proteins were sorted into different functional categories. In these data, the proteins involved in signaling and gene regulations dominated others, reflecting the role of nucleus in gene expression and regulation.

Cell Nucleus↗

PubMed2004

Focus on plant proteomics.

Proteomics covers the systematic analysis of proteins expressed by a genome, from the identification of their primary amino-acid sequence to the determination of their relative amounts, their state of modification and association with other proteins or molecules of different types. Tremendous progress has been made in this field in the past few years, especially in plant biology, mostly due to major developments of mass spectrometry dedicated to protein analyses and advanced information technology. The aim of this special issue of Plant Physiology and Biochemistry devoted to Plant Proteomics is not to present a comprehensive coverage of this rapidly expanding field but to focus on the representation of some key aspects to illustrate the importance of proteomics in plant functional genomics.

Genome, Plant↗

PubMed2025

Demonstrating the potential of untargeted hair proteomics for personalized biomarkers in stress-associated disorders.

Biomarker research in psychopathology increasingly employs high-dimensional Omics approaches. Yet, proteomics based on human hair remain largely unexplored, despite its potential to efficiently capture stable biological signals accumulated over weeks to months. This study leveraged machine learning to investigate the potential of the hair proteome-all detectable peptides and proteins-as a biomarker source for stress-associated psychopathology. We analyzed protein profiles from hair segments of women with non-suicidal self-injury disorder and healthy controls (N = 68). Of 1114 identified proteins, 611 were sufficiently abundant for analyses. Partial Least Squares Discriminant Analysis achieved stable 84.4 % cross-validated accuracy for classification of clinical groups (p < .001), outperforming models based on data-derived clusters (60 %), stress-related proteins (73 %), and simulated hair cortisol from meta-analytic effect sizes (53-59 %). Predicted class probabilities strongly correlated with clinical symptoms and well-being (r > .60). Key predictive proteins were linked to pain perception, oxidative stress, and cholesterol homeostasis. Approximately 15 % of proteins differed significantly between groups, with the strongest candidates related to ribosomal function-an emerging target in depression. These findings establish hair proteomics as a promising, non-invasive biomarker source for psychiatric research with potential clinical applications in risk assessment and personalized interventions.

Humans↗

PubMed2025

Single-cell proteomics using mass spectrometry.

Over the past 2 to 3 years, mass-spectrometry-based single-cell proteomics (SCP) has experienced transformative improvements in microfluidic and robotic sample preparation, innovative MS1- and MS2-based multiplexing strategies, and specialized hardware (e.g., timsTOF Ultra 2, Astral), which have dramatically boosted sensitivity, throughput, and proteome coverage from picogram-level protein inputs. Concurrently, tailored computational workflows that encompass normalization, imputation, and no-code platforms have addressed pervasive missing data challenges and standardized analyses, collectively enabling high-throughput, reproducible profiling of cellular heterogeneity. This minireview summarizes the latest progress in SCP technology and software solutions, highlighting how the closer integration of analytical, computational, and experimental strategies will facilitate a deeper and broader coverage of single-cell proteomes.

Single-Cell Analysis↗

PubMed2007

Mass spectrometry: uncovering the cancer proteome for diagnostics.

Despite impressive scientific achievements over the past few decades, cancer is still a leading cause of death. One of the major reasons is that most cancer patients are diagnosed with advanced disease. This is clearly illustrated with ovarian cancer in which the overall 5-year survival rates are only 20-30%. Conversely, when ovarian cancer is detected early (stage 1), the 5-year survival rate increases to 95%. Biomarkers, as tools for preclinical detection of cancer, have the potential to revolutionize the field of clinical diagnostics. The emerging field of clinical proteomics has found applications across a wide spectrum of cancer research. This chapter will focus on mass spectrometry as a proteomic technology implemented in three areas of cancer: diagnostics, tissue imaging, and biomarker discovery. Despite its power, it is also important to realize the preanalytical, analytical, and postanalytical limitations currently associated with this methodology. The ultimate endpoint of clinical proteomics is individualized therapy. It is essential that research groups, the industry, and physicians collaborate to conduct large prospective, multicenter clinical trials to validate and standardize this technology, for it to have real clinical impact.

Animals↗

PubMed2003

Advances in quantitative proteomics via stable isotope tagging and mass spectrometry.

The high-throughput identification and accurate quantification of proteins are essential components of proteomic strategies for studying cellular functions and processes. Techniques that are largely based on stable isotope protein or peptide labeling and automated tandem mass spectrometry are increasingly being applied in quantitative proteomic studies. Over the past year, significant progress has been made toward improving and diversifying these technologies with respect to the methods for stable isotope labeling, process automation and data processing and analysis. Advances in stable isotope protein labeling and recent biological studies that used stable isotope based quantitative proteomics techniques are reviewed.

Affinity Labels↗