ArticleNature medicine2024
Proteomic signatures improve risk prediction for common and rare diseases.
Article in Nature medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 125 papers, 1 of them a synthesis that pooled it.
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Who cites it
125 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Applications and challenges of biomarker-based predictive models in proactive health management.Frontiers in public health · 2025Pooled it
- Biomarkers of Pre-COPD Lung Function Trajectories in Middle Age: A Prospective Study From 1st to 6th Decade.Respirology (Carlton, Vic.) · 2026Article
- Distinct Plasma Proteomic Signatures Distinguish MASLD From Non-Steatotic Individuals but Not From MetALD.Liver international : official journal of the International Association for the Study of the Liver · 2026Article
- Genomic Medicine Sweden: Advancing precision medicine at the national level.Journal of internal medicine · 2026Review
- Explainable Plasma Proteomics-Based Machine Learning for Osteoporosis Diagnosis, Prognosis, and Protein Biomarker Discovery in the UK Biobank.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026Article
- Longitudinal alignments and syntheses of multimodal clinical data for personalized medicine with the PULSE framework.Nature computational science · 2026Article
- Catalytic profiling of extracellular vesicles maps altered cancer metabolism.Nature nanotechnology · 2026Article
- Identification of Pre-Diagnostic Protein Biomarkers for Liver Cirrhosis Based on Prospective Analysis of a Large-Scale Plasma Proteomics in the UK Biobank.Proteomics. Clinical applications · 2026Article
- Integrative Analysis Uncover the Effects and Multi-Omics Features of Thigh Muscle Fat Infiltration.Aging cell · 2026Article
- Plasma Proteomic Profiles Predict Subsequent Obstructive Sleep Apnea Diagnosis in Adults With Metabolic Dysfunction-Associated Steatotic Liver Disease.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026Article
- Context-aware monitoring: rethinking comprehensive screening in the era of AI.NPJ digital medicine · 2026Article
- Translational bottlenecks in blood-based proteomics.EMBO molecular medicine · 2026Article
- The landscape of plasma proteomic links to human organ imaging.Nature communications · 2026Article
- An automated, digital immunoassay on a microfluidic cartridge for on-demand cytokine profiling.Microsystems & nanoengineering · 2026Article
- Predicting health and disease: a conceptual framework for AI in preventive and precision medicine.BMJ health & care informatics · 2026Review
- Observational
- ProMeta: a meta-learning framework for robust disease diagnosis and prediction from plasma proteomics.Bioinformatics (Oxford, England) · 2026Article
- Molecular damage associated with ageing drives inflammation in cardiovascular disease.Nature reviews. Cardiology · 2026Review
- Plasma proteomic signatures improve risk stratification and personalized screening for gastric cancer.Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association · 2026Article
- NMR-Based Metabolic Profiling of Biobank Derived Blood Samples for the Identification of Liver Disease Biomarkers.Biomolecules & therapeutics · 2026Article
65 more citing papers are in PubMed but not listed here.
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Authors and funding
22 authors.
Funding
Abstract
For many diseases there are delays in diagnosis due to a lack of objective biomarkers for disease onset. Here, in 41,931 individuals from the United Kingdom Biobank Pharma Proteomics Project, we integrated measurements of ~3,000 plasma proteins with clinical information to derive sparse prediction models for the 10-year incidence of 218 common and rare diseases (81-6,038 cases). We then compared prediction models developed using proteomic data with models developed using either basic clinical information alone or clinical information combined with data from 37 clinical assays. The predictive performance of sparse models including as few as 5 to 20 proteins was superior to the performance of models developed using basic clinical information for 67 pathologically diverse diseases (median delta C-index = 0.07; range = 0.02-0.31). Sparse protein models further outperformed models developed using basic information combined with clinical assay data for 52 diseases, including multiple myeloma, non-Hodgkin lymphoma, motor neuron disease, pulmonary fibrosis and dilated cardiomyopathy. For multiple myeloma, single-cell RNA sequencing from bone marrow in newly diagnosed patients showed that four of the five predictor proteins were expressed specifically in plasma cells, consistent with the strong predictive power of these proteins. External replication of sparse protein models in the EPIC-Norfolk study showed good generalizability for prediction of the six diseases tested. These findings show that sparse plasma protein signatures, including both disease-specific proteins and protein predictors shared across several diseases, offer clinically useful prediction of common and rare diseases.
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