How a Decade of Mass Spectrometry Breakthroughs Is Rewriting Stroke Medicine

Ischemic stroke remains the leading cause of acquired disability and one of the top causes of death worldwide, yet the molecular events that unfold inside the brain and bloodstream during and after an ischemic insult have long resisted complete characterization. A sweeping review published in Clinical Proteomics now maps how liquid chromatography coupled to tandem mass spectrometry, or LC-MS/MS, has transformed that picture between 2015 and 2025. Written by Arman Kulyyassov of the National Center for Biotechnology in Astana, Kazakhstan, the review argues that the last decade has delivered not incremental improvements but a wholesale reinvention of proteomic workflows, one that has simultaneously deepened mechanistic understanding of stroke biology and accelerated the hunt for clinically deployable biomarkers. The technology, in other words, has finally caught up with the complexity of the disease.

The heart of that reinvention lies in how mass spectrometrists acquire their data. For years, the field relied on data-dependent acquisition, or DDA, in which the instrument selects only the most abundant precursor ions for fragmentation in any given cycle. DDA surveys are inherently biased toward abundant proteins and suffer from stochastic sampling, producing notorious gaps in which the same peptide may be detected in one sample and missing from the next. The review describes a decisive shift toward data-independent acquisition, or DIA, in which the instrument fragments all ions within sequential isolation windows, along with targeted parallel reaction monitoring, or PRM, on high-resolution instruments. The result is superior proteome coverage, markedly enhanced quantitative accuracy, and a substantial reduction in missing values, three properties that matter enormously when the goal is to compare protein abundance across dozens or hundreds of patient specimens.

Hardware evolution matched the acquisition-mode revolution. Kulyyassov catalogs a series of instruments and platforms that have fundamentally reshaped the experimental pipeline: automated sample preparation systems that reduce hands-on variability, high-throughput liquid chromatography platforms such as the Evosep One and micro-pillar array columns known as µPAC that compress separation times while preserving chromatographic resolution, and ion-mobility separations embodied in the timsTOF family with trapped ion mobility spectrometry and parallel accumulation serial fragmentation, or PASEF, as well as cyclic ion mobility geometries that add an extra dimension of gas-phase separation before mass analysis. Next-generation mass analyzers, including the Orbitrap Astral and ZenoTOF, push sensitivity and scanning speed to levels unimaginable a decade ago. Together, these components allow deep, reproducible proteomic profiling from limited clinical material such as a few microliters of plasma or cerebrospinal fluid, something earlier workflows could only approximate.

In animal models of ischemic stroke, these advances have yielded a far richer catalogue of the proteins that rise and fall as injury unfolds. Studies built on DIA and targeted workflows have tracked dynamic protein changes in brain tissue, urine, and extracellular vesicles, the tiny membrane-bound packages that cells release into biofluids and that increasingly serve as molecular couriers of brain injury. The review links these protein signatures to well-established pathophysiological axes: neuroinflammation, oxidative stress, glutamate excitotoxic signaling, and endogenous neuroprotective responses. Because animal experiments permit time-course sampling and controlled reperfusion, typically through middle cerebral artery occlusion models with or without reperfusion, they allow researchers to watch proteome-wide perturbations evolve from the first minutes of vessel blockage through days of tissue repair, generating hypotheses that can then be tested against human specimens.

Human studies, meanwhile, have exploited the full span of accessible sample types. The review surveys proteomic investigations of plasma, serum, cerebrospinal fluid, urine, sputum, and even the thrombi retrieved during mechanical thrombectomy, each offering a different window on the ischemic cascade. From this literature, a set of promising diagnostic biomarkers has crystallized. Some panels can distinguish ischemic stroke from intracerebral hemorrhage, a distinction that is clinically urgent because the two conditions demand opposite treatments and cannot always be separated before imaging. Other candidate markers predict recurrence risk or track treatment response, including response to recombinant tissue plasminogen activator, the mainstay thrombolytic therapy whose narrow therapeutic window makes rapid, reliable decision tools especially valuable.

One recurring theme of the review is the importance of post-translational modifications, the chemical tags such as phosphorylation, acetylation, and lactylation that change a protein’s function without changing its abundance. The abbreviation list alone hints at this frontier, with categories for differentially expressed lysine lactylation sites and for up- and down-regulated modification sites. Lactylation, in particular, connects protein regulation to cellular metabolism and the lactate accumulation that follows oxygen deprivation, making it an attractive reporter of ischemic stress. Detecting PTMs reproducibly requires enrichment strategies, careful fragmentation, and informatics capable of scoring modified peptides at scale, and the review frames PTM analysis as a critical dimension of modern stroke proteomics rather than a specialist afterthought.

Data processing has matured in parallel with the instrumentation, and the review gives bioinformatics its due as an equal pillar of the field. Tools such as DIA-NN and Spectronaut, purpose-built for interrogating large DIA datasets against spectral libraries or library-free predictions, now make it routine to quantify thousands of proteins with statistical rigor, while Skyline serves as the workbench for designing and validating targeted PRM assays. The review also evaluates partial least squares discriminant analysis and related machine-learning approaches that turn protein abundance matrices into classification models for diagnosis or prognosis. Increasingly, the emphasis falls on multi-omics integration, weaving proteomic measurements together with genomic, transcriptomic, and metabolomic layers so that a single perturbed pathway can be seen from several angles at once.

The translational payoff is beginning to look tangible. Biomarker panels capable of differentiating ischemic from hemorrhagic stroke, stratifying recurrence risk, or monitoring response to reperfusion therapy could ultimately shorten the interval between emergency arrival and definitive treatment, the single most important determinant of neurological outcome. Extracellular vesicle proteomics offers a route to biomarkers that cross the blood-brain barrier, since vesicles shed by injured neurons and glia carry cargo into peripheral blood that no freely circulating protein can match. Thrombus proteomics, likewise, provides a molecular autopsy of the clot itself, revealing which pathways produced the embolus and potentially guiding secondary prevention. None of these applications has yet reached routine clinical deployment, but the review positions them as the near-term frontier rather than distant speculation.

Kulyyassov is candid about the obstacles that stand between discovery and the clinic. Translating these findings into precision diagnostics and personalized therapies, the review concludes, will require continued standardization of pre-analytical and analytical procedures, rigorous validation in large and diverse patient cohorts, and closer integration with other omics technologies. The history of proteomics is littered with biomarkers that dazzled in small studies and dissolved at scale, and the quantitative accuracy that DIA and PRM deliver is a necessary but not sufficient remedy. Standard operating procedures for sample handling, consensus metrics for assay performance, and independent multicenter replication remain prerequisites before any protein panel can sit beside computed tomography in a stroke unit.

What the decade of work summarized in this review ultimately demonstrates is that proteomics has matured from a descriptive exercise into a quantitative, reproducible, and clinically oriented discipline. The convergence of data-independent acquisition, ion-mobility-enhanced mass analyzers, automated sample preparation, and robust software has made it feasible to profile the protein landscape of ischemic stroke with a depth and consistency that were out of reach in 2015. As the author notes, these advances have significantly deepened mechanistic understanding of the disease and accelerated biomarker discovery, even as the harder work of validation and standardization continues. For a condition that kills and disables millions each year, the prospect of blood-based protein diagnostics built on this decade of engineering progress is one of the more quietly consequential stories in modern stroke research.

Subject of Research: Advances in LC-MS/MS proteomics technology for ischemic stroke biomarker discovery

Article Title: Proteomics in ischemic stroke: a decade of advances in LC-MS/MS technology

Article References: Kulyyassov, A. (2026). Proteomics in ischemic stroke: a decade of advances in LC-MS/MS technology. Clinical Proteomics. https://doi.org/10.1186/s12014-026-09636-x

Image Credits: AI Generated

DOI: 10.1186/s12014-026-09636-x

Keywords: ischemic stroke, proteomics, LC-MS/MS, data-independent acquisition, mass spectrometry, biomarkers, cerebrospinal fluid, extracellular vesicles, post-translational modifications, DIA-NN, neuroinflammation, liquid chromatography