September 10, 2025Open Access

Proteomic prediction of disease largely reflects environmental risk exposure

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Observational analysis identifies that most plasma biomarkers associate with environmental risk, suggesting predictive value implies health risk.

Only 8% of protein-disease associations suggest causal relationships, highlighting a predominance of non-causal markers.
Proteomic signatures linked to diseases like lung cancer reveal significant associations with smoking, emphasizing environmental risk.
A newly developed proteomic score for smoking demonstrates the plasma proteome's potential as a quantitative index of smoking behavior.
Findings point to the plasma proteome serving as environmental sensors rather than direct disease indicators, impacting disease prevention strategies.

Tsuo et al. (2025) studied this question.

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September 10, 2025Open Access

View Full Paper

Ask AI

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Authors

Observational analysis identifies that most plasma biomarkers associate with environmental risk, suggesting predictive value implies health risk.

Only 8% of protein-disease associations suggest causal relationships, highlighting a predominance of non-causal markers.
Proteomic signatures linked to diseases like lung cancer reveal significant associations with smoking, emphasizing environmental risk.
A newly developed proteomic score for smoking demonstrates the plasma proteome's potential as a quantitative index of smoking behavior.
Findings point to the plasma proteome serving as environmental sensors rather than direct disease indicators, impacting disease prevention strategies.

Tsuo et al. (2025) studied this question.

View Full Paper

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Bookmark