Nanoparticle-enriched mass spectrometry proteomics in British South Asians identifies links between genetic variants, plasma protein levels and disease risk

Beyond the classical plasma secretome: genetic architecture and disease associations of the expanded human plasma proteome in 13,445 Europeans

Circulating plasma proteins are key biomarkers and therapeutic targets, now measurable at scale through high-throughput technologies, yet whether expanding proteomics platforms beyond the classical plasma secretome enhances genetic discovery and causal inference remains poorly understood. Here, we use an expanded SomaScan 7k platform to map the genetic architecture of a broader segment of the plasma proteome and to evaluate how proteome expansion affects pQTL discovery, causal inference and therapeutic target prioritisation. After quality control, we analysed 7,144 aptamers targeting 6,267 proteins in the harmonised dataset of two European cohorts: INTERVAL (n = 9,251 participants) and CHRIS (n = 4,194), and conducted genome-wide pQTL association analyses followed by meta-analysis. We identified 7,870 significant pQTLs (P-value < 1.26 x 10E-11; 1,784 cis, 6,086 trans), of which 2,704 (34%) associations were not reported in five prior large-scale pQTL studies. Newly assessed proteins, which accounted for 53% (1,422/2,704) of the novel associations, were less likely to harbour cis-pQTLs associations (15%) than those in the previous platform version (28%), consistent with their lower expected plasma concentrations and predominantly intracellular localisation. Colocalization analyses revealed widespread sharing of genetic signals across proteins and characterised 22 pleiotropic trans-regulatory hotspots accounting for 68% of all trans-pQTLs. Through two-sample Mendelian randomization analyses on 2,003 phenotypes from the Million Veteran Program, UK Biobank, and FinnGen (combined N > 1.2 million), we identified 6,340 genetically supported protein-trait associations, highlighting disease mechanisms and potential therapeutic opportunities beyond currently drug-targeted circulating proteins. Together, these findings provide a systematic view of the genetic architecture of the expanded plasma proteome and demonstrate that plasma proteome expansion reveals genetically anchored disease biology beyond the classical secretome, while exposing inherent biological and technical constraints of studying low-abundance intracellular proteins in circulation.

Next-generation multiplexed targeted proteomics quantifies post-translational modifications in disease and compound-protein interactions with high throughput

Improvements enabling quantification of site-specific modifications, including post-translational modifications and covalent compound-protein interactions spanning diverse pathways are described.

Advances in Mass Spectrometry-Based Proteomics for Kidney Disease Biomarker Discovery and Clinical Translation.

The high prevalence and substantial burden of kidney diseases necessitate advanced approaches to elucidate molecular mechanisms and promote precision medicine. Mass spectrometry (MS)-based proteomics has evolved into a widely used analytical platform, delivering high-sensitivity, high-throughput protein profiling capabilities that have contributed substantially to biomarker discovery, mechanistic dissection, and therapeutic target identification across a broad range of kidney diseases. This review provides a comprehensive overview of MS-based proteomics applications in kidney disease research, covering progress in biomarker identification, pathogenic mechanism interrogation, and clinical translation. It highlights methodological advances, emerging trends, and persistent challenges that shape the field. Existing literature has uncovered abundant disease-specific biomarkers and revealed key pathogenic pathways, including podocyte injury-associated protein interaction networks, dysregulated complement activation, and metabolic reprogramming, and have critically assessed their translational potential. Additionally, investigations into posttranslational modifications such as phosphorylation and glycosylation have provided valuable insights for targeted therapies. Collectively, these findings illustrate the contributions of MS-based proteomics to the characterization of disease molecular heterogeneity, the identification of key pathogenic drivers, and the development of precision medicine approaches. This review further addresses current challenges in clinical applications, including sample heterogeneity, data complexity, and standardization issues. We additionally emphasize the critical need for minimum reporting standards and multicenter harmonization to accelerate the clinical translation of renal proteomics. Future research should focus on integrating multiomics and artificial intelligence-driven data mining to enhance precise disease subtyping, dynamic monitoring, and personalized treatment strategies.

A targeted mass-spectrometry plasma proteome for simultaneous multi-disease screening

Population health screening is fragmented across dozens of single-condition assays. We asked whether one targeted mass-spectrometry measurement of the plasma proteome could screen simultaneously for many common diseases. Using multiple-reaction-monitoring LC-MS/MS, we quantified 126 proteins (509 peptides) directly in crude plasma from 490 individuals spanning 16 diseases (eight cancers, three inflammatory or renal conditions, and five metabolic and lifestyle disorders) plus age- and sex-matched controls, each protein referenced to a stable-isotope-labelled internal standard. Proteome variation was organised primarily by disease rather than demographics. Cross-validated classifiers detected each disease against matched controls with a mean AUROC of 0.979, a 17-way model identified the specific disease at roughly ten times chance, and a 20-protein subset reproduced full-panel performance. We show that these within-cohort estimates are optimistic upper bounds because each disease was acquired as a separate case-control batch without independent validation. We quantify this, establishing analytical feasibility and defining the validation required for translation.

Using human proteomic and lipidomic to exploration drug target of bladder cancer

Proteoforms in Disease: Biomedical Applications of Top-Down Proteomics.

The proteome is a dynamic landscape of proteoforms arising from genetic mutations, alternative splicing, and post-translational modifications (PTMs), which collectively drive biological function and disease phenotypes. Mass spectrometry (MS)-based proteomics has emerged as an essential technique for elucidating this molecular complexity. Although bottom-up proteomics enables deep protein identification and quantification through peptide-level analysis, it disrupts molecular connectivity and introduces a peptide-to-protein inference problem, which is suboptimal for proteoform analysis. Top-down proteomics (TDP) offers a complementary approach by analyzing intact proteins, preserving molecular connectivity, and enabling direct characterization and quantification of proteoforms. This capability is increasingly vital for understanding heterogeneous human diseases. Here, we review the evolving role of TDP in biomedical research, highlighting studies that revealed proteoform-level alterations, identified candidate biomarkers, and advanced our understanding of the roles of proteoforms in human diseases.