Plasma proteomics of all-cause and cause-specific mortality in individuals with and without type 2 diabetes: Results from two population-based KORA cohorts
Authors: Luo H , Petrera A , Hauck S M , Rathmann W , Herder C , Hoyer A , Peters A , Thorand B 
Published: October 2024

Abstract

Background
Protein biomarkers may contribute to the identification of vulnerable subgroups for premature mortality in middle-aged and older adults.

Purpose
Given the distinctive impact of type 2 diabetes (T2D) on mortality rates and protein levels, this study aimed to explore the association of proteins with all-cause and cause-specific mortality separately among individuals with and without baseline T2D and to assess their impact on the prediction of all-cause mortality.

Methods
Using proximity extension assay technology, we measured 233 cardiovascular (CV) disease- and inflammation-related proteins in two population-based KORA (Cooperative Health Research in the Region of Augsburg) cohorts. The discovery KORA S4 study, with 15.6 years of follow-up, included 1545 participants (T2D group: 116 total, 62 CV, 31 cancer-related and 23 other-cause deaths; non-T2D group: 321 total, 114 CV, 120 cancer-related and 87 other-cause deaths). The validation KORA-Age1 study, with 6.9 years of follow-up, included 1031 participants (T2D group: 76 total, 45 CV, 19 cancer-related and 12 other-cause deaths; non-T2D group: 169 total, 74 CV, 39 cancer-related and 56 other-cause deaths). Cox regression was used to examine associations of proteins with all-cause and cause-specific mortality. Furthermore, eXtreme Gradient Boosting was applied for identification of the most relevant proteins for the prediction of all-cause mortality stratifying by baseline T2D status. The predictive performance of the protein-based model and combined model including both proteins and clinical risk factors was compared to a clinical risk factor-based model using the C-index, category-free net reclassification index (cfNRI), and relative integrated discrimination improvement (IDI).

Results
After validation, we identified 48 proteins associated with all-cause mortality in the T2D group and 64 in the non-T2D group, respectively (37 overlapping proteins). Out of these, 45, eight, and 32 were associated with CV, cancer-related, and other-cause mortality in the T2D group, while 53, 42, and 48 were associated with the respective cause-specific mortality outcomes in the non-T2D group in the pooled analysis of both studies. The combined model improved the prediction of all-cause mortality in both the KORA S4 and KORA-Age1 cohorts among individuals with baseline T2D (KORA-Age1: ΔC-index: 0.065, 95%=0.009-0.129; cfNRI: 0.370, 95%=0.203-0.812; IDI: 0.129, 95%=0.059-0.253) as well as those without T2D (KORA-Age1: ΔC-index: 0.037, 95%=0.015-0.071; cfNRI: 0.370, 95%=0.236-0.632; IDI: 0.053, 95%=0.028-0.104), respectively, compared to the clinical model.

Conclusion
This study discovered shared and unique proteins in individuals with and without T2D, unveiling the complex dynamics of mortality. Moreover, our findings support the role of proteins in improving prediction of premature mortality beyond clinical risk factors in different T2D subgroups, providing insights for future prevention strategies.