Integrating additional omics data, such as proteomics, metabolomics, and epigenetics, could provide a more comprehensive understanding of the molecular mechanisms underlying prediabetes and improve the predictive power of the models, as demonstrated by recent studies employing multiomics and explainable artificial intelligence approaches for early diagnosis of insulin resistance and related metabolic conditions (52). The gene discussed is INS; the disease is prediabetes syndrome.