Robustness and fragility in immunosenescence

Area of Science:

• Immunology
• Computational Biology
• Theoretical Biology

Background:

• The adaptive immune system balances specificity with broad protection.
• Aging (immunosenescence) leads to increased susceptibility to infections.
• The role of naive versus memory cell populations in immune aging is complex.

Purpose of the Study:

• To model the tradeoffs in adaptive immunity during aging.
• To investigate how cumulative cell population changes affect system robustness and fragility.
• To understand immunosenescence as a consequence of adaptive mechanisms.

Main Methods:

• Developed a computational model of adaptive immune cell populations.
• Utilized a stochastic shape space model to characterize binding affinities.
• Simulated infections to monitor cell population evolution and system loss over time.

Main Results:

• Immune cell populations evolve towards overspecialization with repeated infections.
• This leads to a heavy-tailed distribution of system losses over time.
• Initial exposure tuning reduces loss for similar infections but increases vulnerability to novel ones.

Conclusions:

• Immunosenescence arises naturally from adaptive immune system mechanisms, not performance degradation.
• The system becomes "robust, yet fragile" due to overspecialization.
• This fragility, increasing with age, is a hallmark of Highly Optimized Tolerance.