Plasma proteomics at population scale\\ What survives, what travels, and what reaches the clinic

Measuring thousands of circulating proteins in tens of thousands of people with linked health records has changed what can be asked of a blood sample. Plasma proteomic models now match or exceed clinical models for the future onset of many diseases, and the proteome is being used to build aging clocks, disease atlases, and new classifications of disease. This review argues that the transformation is real but conditional. A proteomic signal deserves clinical attention only if it survives validation that does not leak, travels across platforms, cohorts, and populations, and changes decisions in a way that benefits patients. We examine each condition in turn, using worked examples from our own program in the UK Biobank Pharma Proteomics Project: detection-versus-lethality analyses of prostate, colorectal, and lung cancer and a pan-cancer extension; a proteome-derived taxonomy of disease; endotype decomposition of obesity and sarcopenia; a negative test of in-vitro senescence signatures; and the discovery of a temporal-leakage artifact in our own work. We then describe what separates a publishable association from a deployable test. A section written for general practitioners explains what proteomic risk reports are, which are ready for use, how to read one, what patients are likely to bring in first, and what harms to anticipate.