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PubMed2025

Comparative Analysis of Primary Sarcopenia and End-Stage Renal Disease-Related Muscle Wasting Using Multi-Omics Approaches.

BACKGROUND: Age-related primary sarcopenia and end-stage renal disease (ESRD)-related muscle wasting are discrete entities; however, both manifest as a decline in skeletal muscle mass and strength. The etiological pathways differ, with aging factors implicated in sarcopenia and a combination of uremic factors, including haemodialysis, contributing to ESRD-related muscle wasting. Understanding these molecular nuances is imperative for targeted interventions, and the integration of proteomic and metabolomic data elucidate these intricate processes. METHODS: We generated detailed clinical data and multi-omics data (plasma proteomics and metabolomics) for 78 participants to characterise sarcopenia (n = 28; mean age, 72.6 ± 7.0 years) or ESRD (n = 22; 61.6 ± 5.5 years) compared with controls (n = 28; 69.3 ± 5.7 years). Muscle mass was measured using bioelectrical impedance analysis and handgrip strength. Five-times sit-to-stand test performance was measured for all participants. Sarcopenia was diagnosed in accordance with the 2019 Consensus Guidelines from the Asian Working Group for Sarcopenia. An abundance of 234 metabolites and 722 protein groups was quantified in all plasma samples using liquid chromatography with tandem mass spectrometry. RESULTS: Muscle mass, handgrip strength and lower limb muscle function significantly lower in the sarcopenia group and the ESRD group compared with those in the control group. Metabolomics revealed altered metabolites, highlighting exclusive differences in ESRD-related muscle wasting. Metabolite set enrichment analysis revealed the involvement of numerous metabolic intermediates associated with urea cycle, amino acid metabolism and nucleic acid metabolism. Catecholamines, including epinephrine, dopamine and serotonin, are significantly elevated in the plasma of patients within the ESRD group. Proteomics data exhibited a clearer distinction among the three groups compared with the metabolomics data, particularly in distinguishing the control group from the sarcopenia group. The ciliary neurotrophic factor receptor was top-ranked in terms of the variable importance of projection scores. Plasma AHNAK protein levels was higher in the sarcopenia group but was lower in the ESRD group. Proteomic set enrichment analysis revealed enrichment of several pathways related to sarcopenia, such as hemopexin, defence response and cell differentiation, in sarcopenia group. Multi-omic integration analysis revealed associations between relevant metabolites, including catecholamines, and a group of annotated proteins in extracellular exosomes. CONCLUSIONS: We identified distinct multi-omic signatures in individuals with ESRD or sarcopenia, providing new insights into the mechanisms underlying ESRD-related muscle wasting, which differ from primary sarcopenia. These findings may support interventions for context-dependent muscle loss and contribute to the development of targeted treatments and preventive strategies for muscle wasting.

Humans↗

PubMed2026

Genomic and integrative based progression biomarker discovery in adult sepsis: toward clinical stratification and precision medicine.

Sepsis is a life-threatening syndrome characterized by a heterogeneous host response to infection that remains a major cause of mortality worldwide. Current clinical scoring systems capture organ dysfunction but fail to reflect the underlying biological diversity, limiting their utility for patient stratification and targeted therapy. This review provides a comprehensive overview of molecular biomarker approaches used to predict sepsis course and prognosis in adult patients, covering genetic, transcriptomic, proteomic, and integrative strategies up to May 2026. Here, we summarize findings from genetic association studies, along with analyses based on polygenic risk scores to aggregate genetic effects, Mendelian randomization, and rare-variant sequencing approaches. We also review transcriptomic and proteomic strategies for endotyping, and diagnostic and prognostic discrimination. Lastly, we discuss how multi-omics integration is emerging as a promising framework to assist in distinguishing causal therapeutic targets from non-causal biomarkers. We also address the challenges that still constrain clinical translation towards precision medicine.

Biomarker↗

PubMed2003

Proteomics and transcriptomics analyses of secretagogin down-regulation in human non-functional pituitary adenomas.

In order to explore the presence of, and the potential role of, secretagogin in human pituitary adenomas, an analytical strategy that integrated comparative proteomics and comparative transcriptomics was used to detect the protein and the mRNA expression, respectively, of secretagogin in human non-functional pituitary adenomas compared to controls. Proteomics methods included two-dimensional gel electrophoresis, 2D gel image analysis, mass spectrometry [matrix-assisted laser desorption/ionization-time of flight-peptide mass fingerprinting (MALDI-TOF PMF) and liquid chromatography-electrospray ionization-quadrupole-ion trap tandem mass spectrometry (LC-ESI-Q-IT MS/MS)], and database analysis. Transcriptomics methods included the GeneChip microarray, image processing, and data analysis. The proteomics and transcriptomics data demonstrated that secretagogin was significantly down-regulated at the protein and mRNA levels, respectively, in the human non-functional (NF) pituitary adenomas (NF-, LH+, FSH+, and FSH+ + LH+). For the secretagogin protein, the expression level was NF- < FSH+ + LH+ < FSH+ < LH+ < Control, with a range of down-regulation of 2.2-6.9 fold in non-functional pituitary adenomas compared to controls, with a significant difference (p < 0.001). For secretagogin mRNA, the expression level was NF- < LH+ < FSH+ + LH+ < FSH+ < Control, with a range of down-regulation of 1.8-18.6 fold in non-functional pituitary adenomas compared to controls that was significant (p < 0.05). The secretagogin protein expression correlated significantly with its mRNA expression. Those results suggest that secretagogin might play a role in human non-functional pituitary adenomas. This novel finding may provide clues to clarify the basic molecular mechanisms of pituitary adenoma formation, and to identify new tumor-related markers.

Adenoma↗

PubMed2003

Proteomics in biomarker discovery and drug development.

Proteomics is a research field aiming to characterize molecular and cellular dynamics in protein expression and function on a global level. The introduction of proteomics has been greatly broadening our view and accelerating our path in various medical researches. The most significant advantage of proteomics is its ability to examine a whole proteome or sub-proteome in a single experiment so that the protein alterations corresponding to a pathological or biochemical condition at a given time can be considered in an integrated way. Proteomic technology has been extensively used to tackle a wide variety of medical subjects including biomarker discovery and drug development. By complement with other new technique advances in genomics and bioinformatics, proteomics has a great potential to make considerable contribution to biomarker identification and to revolutionize drug development process. This article provides a brief overview of the proteomic technologies and their application in biomarker discovery and drug development.

Animals↗

PubMed2004

MitoP2, an integrated database on mitochondrial proteins in yeast and man.

The aim of the MitoP2 database (http://ihg.gsf.de/mitop2) is to provide a comprehensive list of mitochondrial proteins of yeast and man. Based on the current literature we created an annotated reference set of yeast and human proteins. In addition, data sets relevant to the study of the mitochondrial proteome are integrated and accessible via search tools and links. They include computational predictions of signalling sequences, and summarize results from proteome mapping, mutant screening, expression profiling, protein-protein interaction and cellular sublocalization studies. For each individual approach, specificity and sensitivity for allocating mitochondrial proteins was calculated. By providing the evidence for mitochondrial candidate proteins the MitoP2 database lends itself to the genetic characterization of human mitochondriopathies.

Computational Biology↗

PubMed2006

Proteomic analysis of fast and slow muscles from normal and kyphoscoliotic mice using protein arrays, 2-DE and MS.

A proteomic strategy based upon the integrated use of SELDI-TOF/MS, 2-DE and MALDI-TOF/MS has been used to identify a panel of fast muscle protein markers: MLC1F, MLC3F, fast troponin C (STNC) and slow muscle markers: MLC1SB and MLC2v. MLC3F, MLC1F and STNC were virtually absent in the physiologically pure slow soleus muscle of kyphoscoliotic mutant mice compared to control BDmice, whereas MLC2v increased threefold. A SELDI-TOF/MS peak at 18,012 Da in spectra from strong anionic exchange protein array fractions of fast vastus muscle was confirmed as STNC by its specific depletion from crude extracts of vastus muscle using an anti-TNC mAb. SELDI-TOF/MS also identified MLC2F phosphorylation in crude muscle extracts after treatment with alkaline phosphatase. High probability protein identifications were achieved by SELDI-TOF/MS PMF based upon the resolution of large peptides formed by partial cleavage and high peptide coverage. When the pI from 2-D gels and molecular weight estimations from SELDI-TOF/MS were entered into the TagIdent algorithm, high probability protein identity predictions were obtained that were confirmed later by PMF. We confirm that SELDI-TOF/MS can be integrated with other proteomics techniques for the efficient analysis of protein expression changes and PTMs associated with physiological changes in skeletal muscle.

Animals↗

PubMed2005

The molecular make-up of a tumour: proteomics in cancer research.

The enormous progress in proteomics, enabled by recent advances in MS (mass spectrometry), has brought protein analysis back into the limelight of cancer research, reviving old areas as well as opening new fields of study. In this review, we discuss the basic features of proteomic technologies, including the basics of MS, and we consider the main current applications and challenges of proteomics in cancer research, including (i) protein expression profiling of tumours, tumour fluids and tumour cells; (ii) protein microarrays; (iii) mapping of cancer signalling pathways; (iv) pharmacoproteomics; (v) biomarkers for diagnosis, staging and monitoring of the disease and therapeutic response; and (vi) the immune response to cancer. All these applications continue to benefit from further technological advances, such as the development of quantitative proteomics methods, high-resolution, high-speed and high-sensitivity MS, functional protein assays, and advanced bioinformatics for data handling and interpretation. A major challenge will be the integration of proteomics with genomics and metabolomics data and their functional interpretation in conjunction with clinical results and epidemiology.

Biomarkers, Tumor↗

PubMed2002

Millennium Award. Proteomics for the development of DNA tolerizing vaccines to treat autoimmune disease.

Autoimmune disease affects 3% of the world population, yet current therapies that globally suppress immune function are inadequate. Tremendous need exists for specific and curative therapies, and we describe a strategy for development of antigen-specific therapies that inactivate pathogenic lymphocytes causing tissue injury. Major barriers to development of antigen-specific therapies for T-cell-mediated autoimmune diseases, such as multiple sclerosis, rheumatoid arthritis, and autoimmune diabetes, include (i) lack of knowledge of the specificity of autoimmune responses, for which proteomic technologies represent powerful tools to identify the self-protein targets of the autoimmune response, and (ii) lack of methods to induce specific immune tolerance, for which DNA tolerizing vaccines represent a promising strategy. We termed our approach Reverse Genomics: use of the proteomics-determined specificity of the autoantibody response to develop and select DNA tolerizing vaccines. Studies performed using animal models for multiple sclerosis and autoimmune diabetes support our Reverse Genomics approach. Through integration of proteomics with specific tolerizing therapies, we are developing a comprehensive approach to treat human autoimmune disease.

Animals↗

PubMed2003

An automated matrix-assisted laser desorption/ionization quadrupole Fourier transform ion cyclotron resonance mass spectrometer for "bottom-up" proteomics.

Here we describe a new quadrupole Fourier transform ion cyclotron resonance hybrid mass spectrometer equipped with an intermediate-pressure MALDI ion source and demonstrate its suitability for "bottom-up" proteomics. The integration of a high-speed MALDI sample stage, a quadrupole analyzer, and a FT-ICR mass spectrometer together with a novel software user interface allows this instrument to perform high-throughput proteomics experiments. A set of linearly encoded stages allows sub-second positioning of any location on a microtiter-sized target with up to 1536 samples with micrometer precision in the source focus of the ion optics. Such precise control enables internal calibration for high mass accuracy MS and MS/MS spectra using separate calibrant and analyte regions on the target plate, avoiding ion suppression effects that would result from the spiking of calibrants into the sample. An elongated open cylindrical analyzer cell with trap plates allows trapping of ions from 1000 to 5000 m/z without notable mass discrimination. The instrument is highly sensitive, detecting less than 50 amol of angiotensin II and neurotensin in a microLC MALDI MS run under standard experimental conditions. The automated tandem MS of a reversed-phase separated bovine serum albumin digest demonstrated a successful identification for 27 peptides covering 45% of the sequence. An automated tandem MS experiment of a reversed-phase separated yeast cytosolic protein digest resulted in 226 identified peptides corresponding to 111 different proteins from 799 MS/MS attempts. The benefits of accurate mass measurements for data validation for such experiments are discussed.

Calibration↗

PubMed2003

ArrayTrack--supporting toxicogenomic research at the U.S. Food and Drug Administration National Center for Toxicological Research.

The mapping of the human genome and the determination of corresponding gene functions, pathways, and biological mechanisms are driving the emergence of the new research fields of toxicogenomics and systems toxicology. Many technological advances such as microarrays are enabling this paradigm shift that indicates an unprecedented advancement in the methods of understanding the expression of toxicity at the molecular level. At the National Center for Toxicological Research (NCTR) of the U.S. Food and Drug Administration, core facilities for genomic, proteomic, and metabonomic technologies have been established that use standardized experimental procedures to support centerwide toxicogenomic research. Collectively, these facilities are continuously producing an unprecedented volume of data. NCTR plans to develop a toxicoinformatics integrated system (TIS) for the purpose of fully integrating genomic, proteomic, and metabonomic data with the data in public repositories as well as conventional (Italic)in vitro(/Italic) and (Italic)in vivo(/Italic) toxicology data. The TIS will enable data curation in accordance with standard ontology and provide or interface a rich collection of tools for data analysis and knowledge mining. In this article the design, practical issues, and functions of the TIS are discussed through presenting its prototype version, ArrayTrack, for the management and analysis of DNA microarray data. ArrayTrack is logically constructed of three linked components: a) a library (LIB) that mirrors critical data in public databases; b) a database (MicroarrayDB) that stores microarray experiment information that is Minimal Information About a Microarray Experiment (MIAME) compliant; and c) tools (TOOL) that operate on experimental and public data for knowledge discovery. Using ArrayTrack, we can select an analysis method from the TOOL and apply the method to selected microarray data stored in the MicroarrayDB; the analysis results can be linked directly to gene information in the LIB.

Databases, Factual↗

PubMed2005

Bridging proteomics and systems biology: what are the roads to be traveled?

The comprehensive study of proteomes has become an important part of attempts to uncover the systemic properties of biological systems. Proteomics provides data of a quality which increasingly fulfills strict requirements of systems biology for quantitative and qualitative information. Notably, proteomics can generate rich datasets that describe dynamic changes of proteomes. On the other hand, large-scale modeling requires the development of mathematic tools that are adequate for the processing of largely uncertain biological data. In this review, recent developments that pave the way for the integration of proteomics into systems biology are discussed. These developments include the standardization of data acquisition and presentation, the increased comprehensiveness of proteomics studies in description of functional status, localization and dynamics of proteins, and advanced modeling approaches.

Animals↗

PubMed2005

Report of the roundtable discussion organised by the Swiss Proteomics Society (SPS), Bern, 8th December 2004.

How close are we to using proteomics tools in the every day practice of physicians? What are the socio-economical issues our health care system may face with the advent of biomarkers for early diagnosis? How to get the specialists from the various disciplines integrated in proteomics to establish a common understanding of the clinical issues and develop the necessary standards (methods, biochemicals and IT)? These were the kind of questions a panel of specialists tried to answer during the roundtable discussion that took place in Bern during the Swiss Proteomics Society 2004 congress.

Automation↗

PubMed2006

An integrated approach to mapping the proteome of the human bone marrow stromal cell.

Bone marrow stromal cells, also known as mesenchymal stem or progenitor cells, are thought to play a critical role in hematopoiesis. Because hematopoiesis is dysregulated in leukemic individuals, expression profiling in leukemic stromal cells might yield valuable insights into mechanisms of normal and dysregulated hematopoiesis. Here, proteomics was used to identify expressed proteins in normal and leukemic bone marrow stromal cells. Isobaric tags for relative and absolute quantification (iTRAQ) technology and MS/MS were used to identify and quantify proteins in bone marrow stromal cells from two normal and two leukemic individuals. Approximately 900 distinct proteins were identified with >95% confidence, 73 of which were differentially expressed in leukemic stromal cells. cDNA microarray analysis on Affymetrix oligonucleotide gene chips showed that transcripts correlated with approximately 90% of the expressed proteins. A novel integrated approach for mining and visualization of iTRAQ data is presented. The results provide an initial assessment of the proteome in human bone marrow stromal cells, laying the groundwork for comprehensive analysis of the proteome in these cells, and ultimately, for improved understanding of normal and dysregulated hematopoiesis.

Adult↗

PubMed2006

Proteomic analysis of low-abundant integral plasma membrane proteins based on gels.

To characterize low-copy integral membrane proteins and offer some methods for human liver proteome projects, we fractionated highly purified rat liver plasma membrane (PM). PM was purified through two sucrose density gradient centrifugations, and treated with 0.1 M Na(2)CO(3), chloroform/methanol and Triton X-100. Proteins were separated by electrophoresis and submitted to mass spectrometry analysis. Four hundred and fifty-seven non-redundant membrane proteins were identified, of which 23% (105) were integral membrane proteins with one or more transmembrane domains. One hundred and fifty-three (33.5%) had no location annotation and 68 were unknown-function proteins. The proteins from different fractions were complementory. A database search for all identified proteins revealed that 53 proteins were involved in the cell communication pathway. More interestingly, more than 50% of the proteins had a protein abundance index concentration of less than 0.1 mol/l, and 12% proteins a concentration 100 times less than that of arginase 1 and actin.

Animals↗

PubMed2004

Mycobacterium tuberculosis functional network analysis by global subcellular protein profiling.

Trends in increased tuberculosis infection and a fatality rate of approximately 23% have necessitated the search for alternative biomarkers using newly developed postgenomic approaches. Here we provide a systematic analysis of Mycobacterium tuberculosis (Mtb) by directly profiling its gene products. This analysis combines high-throughput proteomics and computational approaches to elucidate the globally expressed complements of the three subcellular compartments (the cell wall, membrane, and cytosol) of Mtb. We report the identifications of 1044 proteins and their corresponding localizations in these compartments. Genome-based computational and metabolic pathways analyses were performed and integrated with proteomics data to reconstruct response networks. From the reconstructed response networks for fatty acid degradation and lipid biosynthesis pathways in Mtb, we identified proteins whose involvements in these pathways were not previously suspected. Furthermore, the subcellular localizations of these expressed proteins provide interesting insights into the compartmentalization of these pathways, which appear to traverse from cell wall to cytoplasm. Results of this large-scale subcellular proteome profile of Mtb have confirmed and validated the computational network hypothesis that functionally related proteins work together in larger organizational structures.

Automation↗

PubMed2004

Common interchange standards for proteomics data: Public availability of tools and schema.

The Proteomics Standards Initiative (PSI) aims to define community standards for data representation in proteomics and to facilitate data comparision, exchange and verification. To this end, a Level 1 Molecular Interaction XML data exchange format has been developed which has been accepted for publication and is freely available at the PSI website (http.//psidev.sf.net/). Several major protein interaction databases are already making data available in this format. A draft XML interchange format for mass spectrometry data has been written and is currently undergoing evaluation whilst work is ongoing to develop a proteomics data integration model, MIAPE.

Computational Biology↗

PubMed2002

Plant genomics: present state and a perspective on future developments.

The year 2001 may well be called the Year of the Human Genome. Less in the limelight, but equally exciting for plant scientists, is the rapid progress in plant genomics. With relatively modest resources, a lot has been achieved. The Arabidopsis genomic sequence (125 megabases [Mb]) is essentially finished, and rice sequencing is progressing rapidly. For many species, expressed sequence tag (EST) resources are plentiful, allowing broad inter-specific comparisons. At the same time, development of integrated physical-genetic maps for large-genome crop species is not progressing as rapidly as desired, while resources for the complete sequencing of these crops are not likely to become available. Some important plant genomes are so large that their complete sequencing may not be practical for many years. Significant plant genome research is concentrated in industry, and not freely available, creating some frustration in the academic community. Growing interest is anticipated in the development of metabolic profiling technologies, RNA profiling, proteomics and integrated systems approaches to plant biology.

Computational Biology↗

PubMed2006

Capillary separations enabling tissue proteomics-based biomarker discovery.

Development of the capability to enable large-scale proteome studies, analogous to comprehensive gene expression analysis, will clearly have far-reaching impacts on protein biomarker investigations of human diseases such as cancer through interrogation of the archived fresh frozen and formalin-fixed and paraffin-embedded tissue collections. This review therefore focuses on the most recent advances in microdissection techniques and proteome platforms for procuring homogeneous subpopulations of tumor cells or structures and performing comprehensive analysis of protein profiles within tissue specimens, respectively. Developments in capillary separations capable of providing extremely high resolving power and selective analyte enrichment are particularly highlighted for their roles within the broader context of a state-of-the-art integrated tissue proteome effort. The capabilities of CIEF-based multidimensional separations for performing proteome analysis from minute samples create new opportunities in the pursuit of biomarker discovery using enriched and selected cell populations procured from tissue specimens. These proteome technological advances combined with recently developed tissue microdissection techniques provide powerful tools for those seeking to gain a greater understanding at the global level of the cellular machinery associated with human diseases such as cancer.

Biomarkers↗