Multi-Omics Integration for Precision Medicine and Biomarker Discovery

The field of genetics is undergoing a profound transformation driven by the rapid evolution of multi-omics technologies. By combining genomic, transcriptomic, epigenomic, proteomic, and metabolomic data, researchers are now able to interrogate the molecular complexity of human diseases with unprecedented resolution. While individual omics layers have delivered insights into the genetic basis of traits and disease mechanisms, their integration reveals emergent patterns and interactions that cannot be captured from single data types alone. Recent progress in sequencing, mass spectrometry, and computational analytics has enabled large-scale multi-omics profiling in both experimental and clinical settings. However, major challenges remain, including data harmonization across platforms, feature selection from high-dimensional datasets, and translating computational findings into reproducible and clinically actionable biomarkers. The field now stands at a critical juncture — where methodological innovation must meet translational application to fully realize the promise of precision medicine.This Research Topic aims to gather studies that advance the integration of multi-omics data for precision medicine and biomarker discovery, with a particular focus on genetically anchored analyses. Contributions should bridge molecular multi-layer analysis and clinical relevance, exploring how integrative frameworks can refine disease subtyping, improve patient stratification, and inform targeted therapeutics. Through this collection, we seek to consolidate current advances in computational modeling, multi-scale data analysis, and functional validation, while highlighting novel approaches that enhance reproducibility, interpretability, and real-world clinical impact.To gather further insights into the integrative landscape of human genetics and its precision medicine applications, we welcome articles addressing — but not limited to — the following themes:o Genomics-anchored multi-omics frameworks linking genotype to molecular phenotypeo eQTL, mQTL, and pQTL studies connecting genetic variation to expression and regulationo Single-cell and spatial multi-omics for tissue and tumor microenvironment characterizationo Systems genetics approaches for complex and rare disease mechanismso AI and machine learning models for multi-modal feature integration and biomarker predictiono Regulatory network reconstruction using integrated epigenomic and transcriptomic datao Clinical translation of multi-omics biomarkers for diagnosis, prognosis, and treatment responseo Data standards, reproducibility, and FAIR principles in multi-omics researcho Population-scale and longitudinal multi-omics in biobank or cohort studies Topic editors: Teresa Colombo, Dusanka Savic Pavicevic, Alejandro Q Nato Jr Source: https://www.frontiersin.org/research-topics/83071/multi-omics-integration-for-precision-medicine-and-biomarker-discovery