Integrative Variant Interpretation: Regulation, Epigenomics, and Disease Mechanisms

Most genetic variants linked to human disease sit outside protein-coding regions. Genome-wide association studies and large sequencing efforts now find them faster than we can explain them. Many of these variants alter gene regulation. They change enhancer activity, transcription factor binding, chromatin accessibility, DNA methylation, histone marks, 3D genome contacts, or post-transcriptional control. Linking a variant to a molecular mechanism, and then to a disease phenotype, is still one of the hardest problems in genomics and systems biology.This Research Topic brings together work that combines multiple layers of data to interpret variants in context. We welcome studies that integrate genomics with epigenomics, transcriptomics, proteomics, and other omics. This includes single-cell and spatial approaches, as well as clinical and population-scale datasets. We also want to highlight computational and experimental methods that move from association to causation. Examples are fine-mapping, QTL and colocalization analysis, massively parallel reporter assays, CRISPR-based perturbation screens, and machine learning models that predict regulatory effects.Themes of interest include, but are not limited to:• Interpretation of non-coding and regulatory variants, including those in enhancers, promoters, and non-coding RNAs• Epigenomic mechanisms of disease, including methylation and chromatin state changes, and epigenome-wide association studies• Multi-omic integration and network-based approaches to prioritise causal variants and genes• Single-cell and cell-type-specific regulatory maps for variant interpretation• Deep learning and AI models for predicting variant effects• Functional validation using reporter assays, genome editing, and model systems• Variants of uncertain significance in rare disease, cancer, and complex traits• Tools, databases, benchmarks, and standards for reproducible variant annotation• Ancestry diversity and equity in variant interpretation resourcesWe invite Original Research, Methods, Data Reports, Reviews, Mini Reviews, Perspectives, and Brief Research Reports. Our aim is to build a shared view of how regulatory and epigenomic evidence can turn variant lists into mechanistic insight and, ultimately, clinical value. Topic editors: Hasan Zulfiqar, Rahul Singh Jasrotia, Tao Zeng Source: https://www.frontiersin.org/research-topics/87476/integrative-variant-interpretation-regulation-epigenomics-and-disease-mechanisms