Integrative Analysis of Multi-omics Data Expands Druggable Targets for Circadian Medicine

Circadian rhythms control nearly all physiological processes, and their disruption is a risk factor for many diseases. Accordingly, aligning drug administration with the body’s internal clock, known as circadian medicine, is increasingly recognized as a promising therapeutic strategy. However, there is no systemic effort to identify therapeutic targets for circadian medicine. To address this gap, we constructed a Rhythmic Interacting Network for Multi-Omics (RHINO) by integrating 18 types of omics data across 107 pathological conditions. RHINO enables systematic exploration of circadian regulation across biological layers, uncovers disease-associated rhythmic disruptions, and prioritizes druggable targets. As proof of concept, we systematically integrated rhythmic 3D chromatin conformation, enhancer activity, and gene expression data to identify disease-sensitive rhythmic genes and their upstream regulators, which led to estrogen receptor α (ERα). We validated the time-dependent effects of estradiol on body weight regulation and hepatic metabolic gene expression. All together, RHINO (https://hanlaboratory.com/RHINO), an AI-powered multi-omics platform, offers an integrative framework for accelerating discoveries in chronobiology and advancing precision circadian medicine.