Chronic kidney disease (CKD) and metabolic syndrome are two major comorbidities affecting a substantial proportion of the general population, with a considerable increase in the associated disability-adjusted life-years lost over the decades. The association between CKD and metabolic syndrome is bidirectional rather than being a cause-effect relationship, as CKD patients are prone to develop metabolic syndrome, and vice versa. Nevertheless, the bidirectional nature and underlying mechanisms of these conditions are poorly investigated. Gaining deeper phenotypic and genetic insights into both diseases could lead to an enhanced understanding of CKD.
Using the UK Biobank, we aim to integrate a wide array of information-encompassing genetic, environmental, lifestyle factors, laboratory indicators, imaging, and omics data-to clarify the epidemiological and phenotypic characteristics of patients with comorbid chronic kidney disease and metabolic disorders. Our goal is to identify potential biomarkers of CKD progression, and temporal order of the CKD and other organ damage. Once identified, we will develop prediction models, early warning systems, and prevention strategies, ultimately helping to reduce the disease burden on both society and families in real-world therapeutic settings.
