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Biomedical subjects

Vincent Albrecht

Publications and source records attributed to Vincent Albrecht.

3 recordsLinked to original sources

Unlocking the Circulating Proteome: Toward Clinical Translation.

Blood-based proteomics is approaching a translational inflection point. Driven by advances in measurement technologies, rapid expansion of analytical capabilities, and growing adoption across research and medical communities, there is increasing demand for clinically actionable biomarkers. As the field transitions away from purely large-scale discovery-oriented studies toward more informed, targeted, application-driven analyses, the generation of proteomic data is no longer the bottleneck. Instead, the central challenge is to translate these measurements into robust, reproducible, and clinically meaningful insights. In this Review, we assess recent technological and methodological developments, evaluate persistent preanalytical and interpretative limitations, and outline the key steps required for clinical translation. We focus on three deeply interconnected dimensions: the capabilities and constraints of current measurement platforms, the role of computational and machine learning approaches in extracting biological and clinical signals, and the emergence of large-scale population studies that create new opportunities for validation and generalization. Finally, we discuss a forward-looking vision in which proteomics plays a central role in dynamic, multilayered omics frameworks, where integration with genomics, temporal profiling, and imaging can deepen our understanding of health, disease, and therapeutic response.

Humans

Limited Impact of Column Chemistry and Length on Proteome Coverage Under High-Speed DIA.

The evolution of mass spectrometry (MS)-based proteomics has been driven by continuous technological advances in sample preparation, liquid-phase separations, instrumentation, and data acquisition. Chromatographic performance has been recognized as a contributing factor to identification depth, particularly on earlier-generation MS platforms. Recent advances in MS sampling speed and sensitivity now raise the question of how strongly chromatographic quality continues to determine overall proteome coverage. We investigate how column chemistry and length influence proteome coverage and chromatographic selectivity under modern data-independent acquisition conditions, and whether traditional optimization priorities still apply. Spanning a matrix of experiments with five distinct stationary phases, including C18 chemistries, C8, and Phenyl-Hexyl, across eight column lengths (40-140 mm), we evaluate protein identification performance using data-independent acquisition on the Orbitrap Astral mass spectrometer. Despite differences in stationary-phase chemistry and column length, we observed remarkably convergent proteome coverage metrics. All C18 and C8 phases consistently achieved over 150,000 precursor- and approximately 9000 protein group identifications, regardless of column length variations. While retention fingerprints persisted across chemistries, these chromatographic differences did not translate into meaningful variations in proteome coverage under high-speed acquisition conditions at 200 Hz. Within the range of modern sub-2 μm reversed-phase materials tested, identification depth showed limited dependence on column chemistry and length, suggesting that for state-of-the-art stationary phases, method development priorities may increasingly favor operational robustness, throughput, and reproducibility over traditional separation optimization.

Proteome

Bridging the Gap From Proteomics Technology to Clinical Application: Highlights From the 68th Benzon Foundation Symposium.

The 68th Benzon Foundation Symposium brought together leading experts to explore the integration of mass spectrometry-based proteomics and artificial intelligence to revolutionize personalized medicine. This report highlights key discussions on recent technological advances in mass spectrometry-based proteomics, including improvements in sensitivity, throughput, and data analysis. Particular emphasis was placed on plasma proteomics and its potential for biomarker discovery across various diseases. The symposium addressed critical challenges in translating proteomic discoveries to clinical practice, including standardization, regulatory considerations, and the need for robust "business cases" to motivate adoption. Promising applications were presented in areas such as cancer diagnostics, neurodegenerative diseases, and cardiovascular health. The integration of proteomics with other omics technologies and imaging methods was explored, showcasing the power of multimodal approaches in understanding complex biological systems. Artificial intelligence emerged as a crucial tool for the acquisition of large-scale proteomic datasets, extracting meaningful insights, and enhancing clinical decision-making. By fostering dialog between academic researchers, industry leaders in proteomics technology, and clinicians, the symposium illuminated potential pathways for proteomics to transform personalized medicine, advancing the cause of more precise diagnostics and targeted therapies.

Proteomics