What does this research mean for the field?

A newly developed proteomic inflammaging score (PIS) outperforms conventional inflammatory biomarkers in predicting all-cause mortality, multisystem disease burden, and aging-related biological changes. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

To develop a proteomic inflammaging score (PIS) that captures the molecular heterogeneity of systemic inflammation and evaluate its capacity to predict mortality and age-related phenotypes.

September 15, 2026Experimental GerontologyOpen Access

Proteomic signatures of systemic inflammation in aging, multimorbidity, and mortality

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Authors

ZJZhou Jiang DLDanyang Ling ZCZiwei Chen

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Overview

Cohort study reveals proteomic inflammaging scores predict mortality and multimorbidity in UK adults, indicating broad utility for systemic biological aging assessment.

Key Points

To develop a proteomic inflammaging score (PIS) that captures the molecular heterogeneity of systemic inflammation and evaluate its capacity to predict mortality and age-related phenotypes.
Analyzed 40,471 participants from the UK Biobank using LASSO to identify proteins linked to six systemic inflammatory biomarkers (CRP, SII, SIRI, MLR, NLR, PLR).
Modeled biomarker-specific profiles with deep neural networks, integrated them into a composite PIS via elastic-net Cox regression, and validated the score in an external cohort of 5,250 participants.
Characterized age-related proteomic trajectories using DE-SWAN and assessed underlying genetic architecture using genome-wide analyses.
Both full (HR = 1.88, 95% CI: 1.79–1.98) and simplified 93-protein (HR = 1.88, 95% CI: 1.79–1.97) PIS were significantly associated with all-cause mortality and multiple aging-related phenotypes.
Adding simplified PIS to standard clinical indices improved mortality discrimination, achieving a C-index of 0.758 (95% CI: 0.752–0.765), with similar performance confirmed in external validation.
Proteomic inflammation demonstrated non-linear crests near ages 50, 62–63, and 67 years, and mapped to 25 lead SNPs linked to inflammatory traits.

Cite This Study

Jiang et al. (2026) studied this question.

synapsesocial.com/papers/6aa9132f9013453be30a0ef2 https://doi.org/10.1016/j.exger.2026.113321

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September 15, 2026Experimental GerontologyOpen Access

Proteomic signatures of systemic inflammation in aging, multimorbidity, and mortality

View Full Paper

Ask AI

Bookmark

Authors

ZJZhou Jiang DLDanyang Ling ZCZiwei Chen

Discussion

Member takes

Overview

Cohort study reveals proteomic inflammaging scores predict mortality and multimorbidity in UK adults, indicating broad utility for systemic biological aging assessment.

Key Points

To develop a proteomic inflammaging score (PIS) that captures the molecular heterogeneity of systemic inflammation and evaluate its capacity to predict mortality and age-related phenotypes.
Analyzed 40,471 participants from the UK Biobank using LASSO to identify proteins linked to six systemic inflammatory biomarkers (CRP, SII, SIRI, MLR, NLR, PLR).
Modeled biomarker-specific profiles with deep neural networks, integrated them into a composite PIS via elastic-net Cox regression, and validated the score in an external cohort of 5,250 participants.
Characterized age-related proteomic trajectories using DE-SWAN and assessed underlying genetic architecture using genome-wide analyses.
Both full (HR = 1.88, 95% CI: 1.79–1.98) and simplified 93-protein (HR = 1.88, 95% CI: 1.79–1.97) PIS were significantly associated with all-cause mortality and multiple aging-related phenotypes.
Adding simplified PIS to standard clinical indices improved mortality discrimination, achieving a C-index of 0.758 (95% CI: 0.752–0.765), with similar performance confirmed in external validation.
Proteomic inflammation demonstrated non-linear crests near ages 50, 62–63, and 67 years, and mapped to 25 lead SNPs linked to inflammatory traits.

Cite This Study

Jiang et al. (2026) studied this question.

synapsesocial.com/papers/6aa9132f9013453be30a0ef2 https://doi.org/10.1016/j.exger.2026.113321

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