ABSTRACT Introduction It is increasingly evident that the multifactorial nature of cardiovascular disease requires the combination of different omics approaches for improving our mechanistic understanding, identifying novel drug targets, and developing accurate diagnostic, predictive, and prognostic biomarker panels. Areas covered We review the current state and the potential of multi-omics in cardiovascular disease, with a specific focus on plasma-, spatial-, and single-cell approaches. We discuss lipidomics as a genotype‑to‑phenotype bridge, the utility of remote longitudinal monitoring via microsampling/dried blood spots, and emerging clinical‑trial integrations of multi-omics approaches. We outline critical gaps in standardization and how to overcome these, pre‑analytical challenges and constraints that are often neglected, and data‑integration methods spanning from canonical correlation analysis to modern machine learning approaches. Expert opinion Multi‑omics can shape cardiovascular care by identifying drug targets in diseased tissue and by yielding small, usable biomarker panels.

ABSTRACT Background Pancreatic ductal adenocarcinoma (PDAC) lacks a reliable diagnostic biomarker, largely due to its asymptomatic onset and frequent late-stage detection, resulting in a poor 5-year survival rate. Identifying biomarkers for timely diagnosis is critical. Cancer cells display distinct protein regulation changes that drive disease hallmarks, and characterizing these across PDAC subtypes may provide insights into disease progression. Research design and methods In this study, a label-free quantitative (LFQ) proteomics approach using mass spectrometry (MS) was employed to profile circadian rhythm-regulated proteins in the secretome of PDAC cell lines. Results LFQ analysis revealed rhythmic protein regulation patterns, reflecting temporal control of biological processes in PDAC. Upregulated pathways included signal transduction, glycolysis, angiogenesis, and protein synthesis, indicating enhanced metabolic and proliferative activity. Downregulated immune pathways suggested potential immune modulation. Comparative analysis revealed subtype-specific patterns: the quasi-mesenchymal subtype exhibited higher levels of metabolic and extracellular matrix (ECM) remodeling proteins, while the classical subtype showed higher levels of ECM-degrading proteins, consistent with known phenotypic differences. Conclusion These findings highlight rhythmically regulated proteins as potential subtype-specific markers in PDAC and provide a basis for future validation studies. Mass spectrometry proteomics data are available via the ProteomeXchange Consortium (PRIDE: PXD054693).

ABSTRACT Introduction Mass spectrometry (MS)-based proteomics, especially the targeted applications, hold great potential as Laboratory Developed Tests (LDTs) for clinical applications. They are suitable for widespread clinical use due to their impressive sample/protein multiplexing capabilities, analytical sensitivity and replicability, adaptability to diverse clinical samples, and highly evolved sample processing protocols. Although multiple LDTs have been developed and approved by regulatory agencies, various areas still need improvement. Areas covered This article focuses on introducing MS-based LDT as a potential clinical technology, its superiority over low-throughput or antibody-based methods, existing hurdles in the adoption of such LDTs in clinics, what they can adopt to, and regulatory and analytical considerations that need to be addressed to develop a robust MS-based LDT. Expert opinion Recent efforts to optimize instrumentation and sample preparation for MS-based applications have made these LDTs promising contenders for clinical utilization. With focused research to answer quality assessment requirements, data interpretability, method scalability, and ease of use, MS-based LDTs can revolutionize clinical diagnostics. Drawing parallels to other omics technologies, these LDTs can address the long-standing multiplexing hinge and further establish multi-protein diagnostics as next-generation diagnostics of low-throughput methods.

ABSTRACT Introduction Protein tyrosine sulfation is of growing scientific interest due to its biological and clinical significance, yet it remains an underexplored post-translational modification (PTM). Catalyzed by Golgi-localized TPST1 and TPST2, tyrosine sulfation modulates protein-protein interactions and receptor-ligand binding in inflammation, hemostasis, immunity, and viral entry. Despite functional relevance, this modification is underrepresented in databases such as UniProt (accessed July 2025), in large part due to a lack of robust analytical strategies. Advances in mass spectrometry (MS)-based analyses have recently improved sensitivity of detection, expanding the known tyrosine ‘sulfome.’ Systematic profiling of sulfated residues can now be undertaken, expanding knowledge of their regulatory roles in both health and disease, and for pioneering new sulfation-targeted therapeutics. Areas covered We review known biological roles of protein sulfation by TPSTs and approaches for characterization of sulfation of tyrosine and other residues such as cysteine. More broadly, we consider how these strategies might be useful in a clinical context. Expert opinion High throughput MS-based proteomics has proven invaluable for the discovery of PTMs, advancing understanding of their roles in human health and disease. With recent advances in strategies for the characterization of protein sulfation, the field is now ready for exploration in a clinical context.

ABSTRACT Introduction Clinical proteomics has become a pivotal component of precision medicine, significantly advancing the understanding of disease mechanisms and informing therapeutic strategies. This review explores how clinical proteomics is transforming diagnostic and therapeutic approaches across multiple fields. Areas covered This review highlights recent developments and applications of clinical proteomics in cardiovascular and neurological disorders, as well as its impact on drug development. Technologies such as mass spectrometry and protein microarrays have enhanced diagnostic precision, facilitated the discovery of novel biomarkers, and uncovered new therapeutic targets. In cardiovascular medicine, proteomics supports early disease detection and patient risk stratification, while in neurology, it helps identify disease-specific protein signatures that guide targeted interventions. The integration of proteomics with databases like Universal Protein Resource (UniProt) and the Human Protein Atlas, alongside the use of advanced bioinformatics tools, has streamlined data analysis and accelerated the design of personalized therapies. Expert opinion Clinical proteomics is rapidly evolving, offering unprecedented opportunities to refine diagnostics, personalize therapies, and improve patient outcomes. Overcoming current challenges in standardization and validation will be essential for its full integration into clinical practice.

ABSTRACT Background Streptococcus pneumoniae meningitis (SPM) is a critical pediatric infection with a high mortality rate. This study aimed to investigate changes in the cerebrospinal fluid (CSF) proteome in SPM patients and identify biomarkers for SPM diagnosis and treatment monitoring. Research design and methods Here, we retrospectively collected and evaluated CSF proteomes of 47 SPM and 116 non-CNS-infected patients (Control), including longitudinal samples from 11 SPM patients. Candidate biomarkers were validated by parallel reaction monitoring (PRM) in 146 samples (36 longitudinal/12 SPM, 110 Control) and evaluated via receiver operating characteristic (ROC) analysis. Results We identified 648 differentially expressed proteins (DEPs) associated with complement activation and oxidative stress. SPM patients with abnormal CSF white blood cells (SPMAN) exhibited dysregulation in coagulation and fibrinolysis, while those with normal counts (SPMN) displayed redox homeostasis alterations. The ELANE and H4C1 panel achieved a superior diagnostic accuracy (AUC = 0.967), and the combination of IGKV1–17, IGKC, and IGKV4–1 effectively tracked therapy response (AUC = 0.872). Conclusion This study establishes CSF proteomic signatures of pediatric SPM, providing dual-purpose biomarker panels for clinical diagnosis and treatment monitoring, with implications for targeted interventions.

ABSTRACT Introduction Recent failures of therapeutic interventions aimed at elevating high-density lipoprotein cholesterol (HDL-C) have renewed the need to reconceptualize HDL. The HDL proteome constitutes over 50% of the HDL mass and it is the richest among lipoproteins. HDL is also the most heterogeneous lipoprotein, and unraveling the determinants of its pleiotropic functions requires new approaches to characterize HDL subspecies as well as harmonization of isolation and quantification methodologies. Areas covered We have reviewed studies focusing on HDL proteomes from the past 5 years, with particular focus on recent developments in mass spectrometry-based proteomics applied to HDL, and the studies of HDL heterogeneity and function. Emphasis is also given on the quantification of the proteome of HDL-specific subspecies and on the studies relating the HDL proteome to its function. We further discuss the need for harmonization in HDL subpopulations and subspecies isolation and in proteome quantification. Expert opinion The HDL proteome is undisputedly related to the HDL function. The development of new approaches to isolate HDL subspecies, together with the implementation of consistent quantification strategies, is needed to provide new insights into the structure–function relationship of HDL particles, unravel the role of HDL in the pathology of diseases, and provide new metrics of HDL.

ABSTRACT Introduction Advances in various proteomics technologies, especially high-throughput and reproducibility, have enabled the systematic exploration of the circulating thrombosis proteome. This includes dissecting biological systems and pathways imperative to thrombosis, such as platelet activation, coagulation cascade, complement system, and endothelial cells. These insights strengthen our understanding of the cause and effect of thrombosis and improve precision medicine by identifying better biomarkers and biomarker panels, which may aid clinicians in decision-making in venous thromboembolism (VTE) and other thrombotic patients. This progress has the potential to reduce thrombosis-related morbidity and mortality, ultimately improving patient quality of life. Areas covered This review highlights recent advances and applications of mass spectrometry and affinity-based proteomics in thrombosis over the past three years (2022–2024), focusing on the thrombotic proteome signature related to VTE. Expert opinion Plasma proteomics, predominantly driven by mass spectrometry and affinity-based proteomics, has shown promise in identifying novel disease biomarkers and pathways. With the recent advances in the field, proteomics holds the potential to revolutionize precision medicine. As thrombosis is an intravascular disease, analysis of the blood proteome can capture environmental, genetic, and epigenetic contributors to risk variation in thrombosis, revealing novel protein biomarkers for diagnosis and risk prediction and new biological pathways.

ABSTRACT Introduction The emergence of personalized medicine (PM) has shifted the focus of healthcare from the traditional ‘one-size-fits-all’ approach to strategies tailored to individual patients, accounting for genetic, environmental, and lifestyle factors. Acoustic ejection mass spectrometry (AEMS) is a novel technology that offers a robust and scalable platform for high-throughput MS readout. AEMS achieves analytical speeds of one sample per second while maintaining high data quality, broad compound coverage, and minimal sample preparation, making it an invaluable tool for PM. Areas covered This article explores the potential of AEMS in critical PM applications, including therapeutic drug monitoring (TDM), proteomics, metabolomics, and mass spectrometry imaging. AEMS simplifies conventional workflows by minimizing sample preparation, enhancing automation compatibility, and enabling direct analysis of complex biological matrices. Expert Opinion Integrating AEMS with orthogonal separation techniques such as differential mobility spectrometry (DMS) further addresses challenges in isomer discrimination, expanding the platform’s analytical capabilities. Additionally, the development of high-throughput data processing tools could further enable AEMS to accelerate the development of personalized medicine.