BACKGROUND
Chronic low-grade inflammation is central to biological aging, but routine inflammatory biomarkers capture limited molecular heterogeneity. We aimed to develop a proteomic inflammaging score (PIS) and evaluate its practical utility.
METHODS
In 40,471 England participants from UK biobank, we used LASSO to identify proteins associated with six inflammatory biomarkers (CRP, SII, SIRI, MLR, NLR, PLR), and validated them in 5250 non-England cohort. Deep neural networks generated biomarker-specific scores, integrated into PIS via elastic-net Cox regression. We evaluated associations with mortality, age-related diseases, and aging biomarkers, and compared predictive utility (C-index, NRI, IDI) against conventional markers. DE-SWAN analysis was used to characterize nonlinear age-related proteomic changes, and genetics analyses were performed to investigate genetic architecture.
RESULTS
A total of 1112 proteins were identified to associated with all six inflammation biomarkers and 93 proteins retained in simplified versions. Both full (HR = 1.88, 95%CI: 1.79-1.98) and simplified (HR = 1.88, 95%CI: 1.79-1.97) PIS were positively associated with all-cause mortality and multiple aging-related phenotypes. PISs outperformed conventional inflammatory and aging biomarkers, significantly improving mortality prediction: for all-cause mortality, clinical indices plus simplified PIS achieved a C-index of 0.758 (95% CI, 0.752-0.765). External validation in the non-England cohort showed comparable predictive performance. Proteomic inflammation crests were near ages 50, 62-63 and 67 years. 25 lead SNPs were associated with PIS, linking PIS to inflammatory traits and aging biomarkers.
CONCLUSION
PIS provides a compact, interpretable proteomic measure of inflammaging and captures mortality, multisystem disease burden, and aging-related biology in population-scale cohorts.
BACKGROUND
MR elastography (MRE) has applications in breast cancer, but its optimal frequency and value in discriminating molecular subtypes remain unclear.
PURPOSE
To identify the preferable breast MRE frequency and evaluate MRE parameters in the precision diagnosis of breast cancer.
STUDY TYPE
Prospective.
POPULATION
One hundred fifty-four female patients (mean age 50 ± 10.67 years) were enrolled, including five with bilateral cancer, yielding 159 lesions.
FIELD STRENGTH/SEQUENCE
3.0 T, fast gradient-echo for DCE-MRI, single-shot EPI for DWI/ADC, SE-EPI for multifrequency MRE.
ASSESSMENT
The image quality of 10 frequency MRE sets was assessed (including overall image quality, diagnostic confidence, artifact impact, and signal-to-noise ratio). Stiffness (c) and viscosity (φ) were measured at the optimal frequency and compared across clinicopathological subgroups.
STATISTICAL TESTS
Independent-sample t-tests or one-way analysis of variance, Mann-Whitney U or Kruskal-Wallis H tests, Friedman test, χ2 tests. Spearman's rank correlation. Univariate and multivariate analyses. Receiver operating characteristic (ROC) curves, the area under the curve (AUC). p < 0.05 was considered statistically significant.
RESULTS
The 40-70 Hz multifrequency band demonstrated significantly superior image quality compared with all other bands. Subgroup analyses showed that c and φ differed significantly between ER-positive and ER-negative groups (c values: 2.54 (2.17-2.86) vs. 2.80 (2.37-3.30) m/s; φ values: 1.17 ± 0.21 vs. 1.24 ± 0.22 radians) and across groups with different Ki-67 expression levels (c values: 2.54 ± 0.54 vs. 2.77 ± 0.57 m/s), T stage, molecular subtypes (c values: 2.55 (2.20-2.82) vs. 2.69 (2.20-2.96) vs. 2.94 (2.52-3.33) m/s), and enhancement patterns (c values: 2.34 ± 0.41 vs. 2.73 ± 0.58 m/s). Multivariable analysis identified c [OR: 5.37 (2.13-15.54)] and age group [OR: 0.27 (0.09-0.82)] as significant independent predictors of triple-negative breast cancer, and a predictive model incorporating these variables demonstrated an AUC of 0.739 in the training set and 0.700 in the validation set.
DATA CONCLUSION
The 40-70 Hz multifrequency protocol may offer favorable image quality for breast MRE. MRE parameters, particularly stiffness, show potential for characterizing tissue biomechanical properties and could assist in distinguishing molecular subtypes.
EVIDENCE LEVEL
1.
STAGE OF TECHNICAL EFFICACY
Stage 2.
Xiaowen Ma, Yifeng Chen, Jinlong Zheng et al.· Journal of Magnetic Resonanc...· 1 citation
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