ArticleNPJ genomic medicine2022
Methylation risk scores are associated with a collection of phenotypes within electronic health record systems.
Article in NPJ genomic medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
46 citing papers in PubMed, 2 syntheses or guidelines pooled it, 55 citations in OpenAlex.
- Childhood internalising symptoms at ages 3 and 6: a meta-analysis of epigenome-wide associations from cord and peripheral blood.Journal of child psychology and psychiatry, and allied disciplines · 2026Pooled it
- DNA methylation risk score for type 2 diabetes is associated with gestational diabetes.Cardiovascular diabetology · 2024Pooled it
- Blood-Based DNA Methylation Models Improve Short-term Cardiovascular Risk Stratification in Individuals With Type 2 Diabetes.Diabetes care · 2026Article
- Integrating polygenic and methylation risk scores for pleural mesothelioma risk stratification.International journal of cancer · 2026Article
- Physiological health Age (PhysAge): a novel multi-system molecular timepiece predicts health and mortality in older adults.GeroScience · 2026Article
- OMICmAge quantifies biological age by integrating multi-omics with electronic medical records.Nature aging · 2026Article
- Review
- Building epigenetic risk scores of opioid use disorder: Insights from human postmortem brain data.Translational psychiatry · 2026Article
- Epigenetics of Childhood Obesity.Hormone research in paediatrics · 2026Review
- Posttraumatic stress disorder and epigenetic signatures of inflammation in middle-aged women.Psychoneuroendocrinology · 2025Article
- DNA methylation and machine learning: challenges and perspective toward enhanced clinical diagnostics.Clinical epigenetics · 2025Review
- Scalable screening of ternary-code DNA methylation dynamics associated with human traits.Cell genomics · 2025Article
- Review
- Emerging Biomarkers and Innovative Therapeutic Strategies in Diabetic Kidney Disease: A Pathway to Precision Medicine.Diagnostics (Basel, Switzerland) · 2025Review
- Genome-Wide DNA Methylation Identifies Potential Disease-Specific Biomarkers and Pathophysiologic Mechanisms in Irritable Bowel Syndrome, Inflammatory Bowel Disease, and Celiac Disease.Neurogastroenterology and motility · 2025Article
- A SuperLearner-based pipeline for the development of DNA methylation-derived predictors of phenotypic traits.PLoS computational biology · 2025Article
- Type-2 diabetes epigenetic biomarkers: present status and future directions for global and Indigenous health.Frontiers in molecular biosciences · 2025Review
- Leveraging DNA methylation to create Epigenetic Biomarker Proxies that inform clinical care: A new framework for Precision Medicine.medRxiv : the preprint server for health sciences · 2024Article
- An epigenetic human cytomegalovirus infection score predicts viremia risk in seropositive lung transplant recipients.Epigenetics · 2024Article
- MOSES: a methylation-based gene association approach for unveiling environmentally regulated genes linked to a trait or disease.Clinical epigenetics · 2024Article
Corrections and comments
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Authors and funding
10 authors at 1 institution in 1 country.
Funding
Abstract
Inference of clinical phenotypes is a fundamental task in precision medicine, and has therefore been heavily investigated in recent years in the context of electronic health records (EHR) using a large arsenal of machine learning techniques, as well as in the context of genetics using polygenic risk scores (PRS). In this work, we considered the epigenetic analog of PRS, methylation risk scores (MRS), a linear combination of methylation states. We measured methylation across a large cohort (n = 831) of diverse samples in the UCLA Health biobank, for which both genetic and complete EHR data are available. We constructed MRS for 607 phenotypes spanning diagnoses, clinical lab tests, and medication prescriptions. When added to a baseline set of predictive features, MRS significantly improved the imputation of 139 outcomes, whereas the PRS improved only 22 (median improvement for methylation 10.74%, 141.52%, and 15.46% in medications, labs, and diagnosis codes, respectively, whereas genotypes only improved the labs at a median increase of 18.42%). We added significant MRS to state-of-the-art EHR imputation methods that leverage the entire set of medical records, and found that including MRS as a medical feature in the algorithm significantly improves EHR imputation in 37% of lab tests examined (median R
Identifiers
What OpenQuestion holds
Registered trials
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.