Metabolic MRI Mapping of Cardiorenal Fluxes to Investigate SGLT2 Signaling Mechanisms and CKMS Progression Biomarkers
Description: Cardiovascular-Kidney-Metabolic (CKM) syndrome is a systemic disorder driven by obesity, diabetes, and chronic kidney disease, leading to heart failure and premature death. Current clinical staging depends on functional markers that identify injury only after irreversible damage occurs. This proposal establishes a multimodal Magnetic Resonance (MR) discovery engine to identify early in vivo imaging biomarkers during the transition from metabolic risk to subclinical cardiovascular disease. We posit that a loss of metabolic flexibility—the capacity of the heart and kidneys to adapt substrate use to demand—is a key early indicator. We will use an integrated multinuclear MR framework combining hyperpolarized 13C metabolic imaging, 31P energetic profiling, and 1H MRI. Aim 1 defines MR metabolic biosignatures in a diabetic mouse model to determine if metabolic remodeling precedes measurable changes in cardiac function or renal filtration. Aim 2 resolves how SGLT2i treatment modulates cardiorenal metabolic fluxes and whether these changes predict delayed functional decline. We expect SGLT2i to restore oxidative flux and suppress redox stress before functional improvements are visible. Aim 3 establishes translational feasibility in a human pilot cohort to evaluate stage-specific differences in metabolic profiles. By integrating systems-level assessments of substrate utilization and energetic reserves along the kidney-heart axis, this work provides a foundation for mechanism-driven staging and the assessment of new therapies. This research supports the American Heart Association’s mission by developing tools for preclinical detection and early intervention.
Funder: American Heart Association
Amount: $100,000
Funding type: research
Funder scheme: Rapid Impact Research Award
Start date: 2026-04-01
End date: 2028-03-31
Investigators: Donghyun Hong, Donghyun Hong
Institution: The Regents of the University of California, San Francisco
Funded outputs count: 0
Funder award ID: 26RIRA1634415
OpenAlex ID: G942677353