This project aims to investigate the relationship between clonal hematopoiesis of indeterminate potential (CHIP) and cardiovascular-kidney-metabolic (CKM) syndrome by leveraging UK Biobank’s clinical imaging, genomic, and proteomic data.
Our central research questions are:
(1)Is the presence and burden of CHIP associated with a higher prevalence and severity of CKM syndrome as defined by metabolic risk factors, CKD markers, and cardiovascular imaging findings?
(2)Which molecular pathways (derived from integrated transcriptomic and proteomic data) mediate the interaction between CHIP and CKM syndrome?
(3) Can multi-omics signatures, combined with imaging biomarkers, predict adverse cardiovascular and renal outcomes?
Objectives:
(1)Prevalence & Stratification: Determine the prevalence of CHIP in the UK Biobank cohort and stratify subjects by CKM syndrome stage (ranging from stage 0: no risk factors to stage 4: clinical CVD/CKD).
(2)Multi-omics Profiling: Integrate genomic data (for CHIP mutation detection) with transcriptomic (RNA-seq) and proteomic profiles to identify differentially expressed genes and proteins associated with inflammation and metabolic dysregulation.
(3)Imaging Correlation: Analyze cardiac and renal imaging data to correlate structural and functional biomarkers with multi-omics signatures.
(4)Outcome Association: Use statistical models to correlate CHIP status and omics-derived risk factors with clinical outcomes (CVD events, CKD progression, mortality).
Scientific Rationale:
We hypothesize that CHIP may exacerbate CKM syndrome via shared inflammatory and metabolic pathways. The UK Biobank’s extensive dataset-including clinical imaging and multi-omics profiles-provides a unique opportunity to dissect these interactions. Integrating these data will advance our understanding of the biological mechanisms linking CHIP and CKM syndrome, improve risk stratification, and reveal potential molecular targets for intervention.