ArticleNature genetics2024
Disease prediction with multi-omics and biomarkers empowers case-control genetic discoveries in the UK Biobank.
Article in Nature genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers, 1 of them a synthesis that pooled it.
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Who cites it
67 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
- Endocrine-Metabolic Crosstalk Between Diabetes Mellitus and Hypothyroidism: From Network Mechanisms to Translational Stratification.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 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
- Prediction of maternal and infant outcomes from longitudinal electronic health records with a mother-child AI agent.Nature medicine · 2026Article
- Best practices for using biological data in psychological research.Journal of mood and anxiety disorders · 2026Review
- Omics Approaches in Hantavirus Research: Current Advances, Challenges, and Future Perspectives.Biotech (Basel (Switzerland)) · 2026Review
- Machine learning-driven cancer diagnostics with improved robustness and interpretability.Chemical science · 2026Review
- An introduction to polygenic scores - methodological basics and recent advances.Medizinische Genetik : Mitteilungsblatt des Berufsverbandes Medizinische Genetik e.V · 2026Article
- Machine Learning Predicts Hepatocellular Carcinoma Risk from Routine Clinical Data: A Large Population-Based Multicentric Study.Cancer discovery · 2026Article
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- Supervised machine learning identifies impaired mitochondrial quality control in β-cells with development of type 2 diabetes.NPJ systems biology and applications · 2026Article
- Beyond data and technology: the need for new thinking to enable the era of precision prevention.BMC medicine · 2026Review
- Exploratory Analysis of Plasma Angiotensin-Converting Enzyme 2 and Angiotensin Peptides as Candidate Discriminatory Signals in Breast Cancer: A Pilot Case-Control Study.Biomedicines · 2026Article
- Multi-omics integration predicts the incidence of 17 diseases in the UK Biobank.Nature communications · 2026Article
- StackAge: an ensemble-based clock for precise quantification of biological age using multi-omics data.Briefings in bioinformatics · 2026Article
- The BHARAT study: a multi-modal, multi-omics investigation of aging signatures in the Indian population.Aging · 2026Observational
- Generative Artificial Intelligence Transitions Pharmaceutical Development from Empirical Screening to Predictive Molecular Design and Clinical Trial Optimization.Pharmaceuticals (Basel, Switzerland) · 2026Review
- Benchmarking large language models for extracting biobank-derived insights into health and disease.PLoS computational biology · 2026Article
- Potential value streams of an integrated Canadian serosurveillance network.Canadian journal of public health = Revue canadienne de sante publique · 2026Article
- Rapid and noninvasive artificial intelligence-assisted diagnostic method for oral squamous cell carcinoma.NPJ digital medicine · 2026Article
7 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
17 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The emergence of biobank-level datasets offers new opportunities to discover novel biomarkers and develop predictive algorithms for human disease. Here, we present an ensemble machine-learning framework (machine learning with phenotype associations, MILTON) utilizing a range of biomarkers to predict 3,213 diseases in the UK Biobank. Leveraging the UK Biobank's longitudinal health record data, MILTON predicts incident disease cases undiagnosed at time of recruitment, largely outperforming available polygenic risk scores. We further demonstrate the utility of MILTON in augmenting genetic association analyses in a phenome-wide association study of 484,230 genome-sequenced samples, along with 46,327 samples with matched plasma proteomics data. This resulted in improved signals for 88 known (P < 1 × 10
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.