Development and preliminary clinical verification of an immune age model based on peripheral immune cells.

BACKGROUND

There is currently no standardized model for assessing immune aging, which may contribute to the development and clinical progression of age-related diseases. We have developed an immune-age prediction model and conducted preliminary validation in patients.

METHODS

A total of 523 healthy adults were recruited for the establishment of the model. Additionally, 53 patients with hematological tumors, 38 patients who had experienced a stroke, and 105 patients with COVID-19 infection were enrolled as the validation cohort. Flow cytometric analysis was conducted to obtain results for 50 TBNK lymphocyte subsets.

RESULTS

The proportion of patients exhibiting an immune age older than their actual age was 81.13% (43/53), 57.89% (22/38), and 65.71% (69/105) in individuals diagnosed with hematological tumors, stroke, and COVID-19 infection, respectively. In stroke patients with poor prognosis, the modified Rankin Scale (mRS) score at 90 days demonstrated a significant positive correlation with immune age (P < 0.01).

CONCLUSIONS

The practical and convenient model demonstrated superior performance in assessing immunosenescence compared to chronological age. Our findings provide preliminary evidence linking early immune aging to adverse outcomes in stroke patients, suggesting its potential as a predictor that warrants further investigation in larger cohorts.