From Molecular Signal to Clinical Action in Cardiovascular-Kidney-Metabolic Disease

To the Editor:

We read with interest the review by Marshall et al.,¹ which reframes cardiovascular-kidney-metabolic disease as an interconnected biological network and highlights the limits of conventional markers, such as estimated glomerular filtration rate, albuminuria, natriuretic peptides, lipids, and glycated hemoglobin. Its discussion of biomarker “silence,” metabolic dysfunction-associated steatotic liver disease (MASLD), and multiomics-enabled endotyping is timely. Our aim is not to diminish this contribution, but to clarify where mechanistic signal should end and clinically actionable evidence should begin.¹

The key translational issue is the evidentiary threshold between molecular detection and clinical action. Much current biomarker evidence remains associative, biologically plausible, or incrementally prognostic. Bedside use requires more evidence that a marker changes management beyond standard assessment and provides net clinical benefit across plausible decision thresholds.^2,3 PromarkerD illustrates this distinction; in CANVAS, it predicted incident chronic kidney disease risk but was less informative for a ≥ 30% decline in estimated glomerular filtration rate, showing that external validity and clinical utility may differ by outcome.² Explicitly distinguishing discovery-stage, externally validated, and action-linked biomarkers would strengthen the review’s translational framing.

MASLD also warrants more nuanced placement within cardiovascular-kidney-metabolic staging. The review convincingly positions MASLD within cardiovascular-kidney-metabolic biology, but its clinical meaning is unlikely to be binary. Current guidance emphasizes stepwise fibrosis assessment and links treatment escalation to disease severity, particularly significant fibrosis, rather than steatosis alone.⁴ If MASLD is used as a stage 1 modifier, its value may depend on fibrosis burden and accompanying atherogenic lipid risk, rather than diagnostic presence alone.

A further gap is the distance between omics-derived endotypes and routine-care tools. Multiomics can identify coherent inflammatory, fibrotic, metabolic, and microvascular phenotypes, but implementation requires more than biologic plausibility. Cross-ancestry transportability, assay standardization, reproducible reporting, and prospective utility testing should be considered prerequisites, not secondary refinements.⁵

A practical way forward is to summarize cardiovascular-kidney-metabolic biomarkers through a 3-step hierarchy—analytic validity, incremental value beyond standard care, and evidence that the result triggers a specific clinical action. Applying this hierarchy to MASLD and omics-guided endotyping would preserve the review’s mechanistic richness while helping readers distinguish biologic enrichment, validated risk prediction, and readiness for routine care.1, 2, 3, 4, 5

Disclosures

The authors declared no competing interests.

Author Contributions

GC conceived the idea and drafted the manuscript. YY and KW contributed to the reviewed the manuscript. All authors read and approved the final manuscript.

Declaration of AI and AI-Assisted Technologies in the Writing Process

Generative AI tool GPT 5.6 was used solely for language refinement and formatting assistance. All scientific interpretation and scholarly content were independently verified by the authors. After using this tool/service, the authors reviewed and edited the content as needed and take full responsibility for the content of the publication.