Decoding the Relationship between Alzheimer's Disease and Type-2 Diabetes via the Protein Aggregation Prism

Area of Science:

• Biophysics
• Computational Biology
• Molecular Medicine

Background:

• Alzheimer's disease (AD) and type-2 diabetes (T2D) are linked to amyloid-beta (Aβ) and human islet amyloid polypeptide (hIAPP) aggregation, respectively.
• These peptide aggregates exhibit mutual influence despite distinct deposition sites (brain and pancreas).

Purpose of the Study:

• To investigate the crosstalk between Aβ and hIAPP aggregation using atomistic simulations.
• To compare the kinetics and thermodynamics of self- and cross-aggregation, and the effect of preformed fibrillar templates.

Main Methods:

• Atomistic simulations were employed to model Aβ42 and hIAPP self- and cross-aggregation.
• Kinetics, thermodynamics, and the impact of fibrillar templates were analyzed.

Main Results:

• Fibrillar templates, particularly hIAPP, generally accelerate aggregation and alter aggregation rate hierarchies.
• Mutual impact flips based on templating: hIAPP aggravates Aβ aggregation without templates, while the reverse occurs with templates.
• Equilibrium aggregability shows Aβ > hIAPP, with templates increasing aggregability for both; aggregation follows the liquid-liquid phase separation (LLPS) model.

Conclusions:

• Aβ and hIAPP exhibit complex, template-dependent crosstalk influencing aggregation kinetics and thermodynamics.
• Aggregation involves polymorphic oligomers stabilized by electrostatics, consistent with LLPS.
• Understanding this peptide interaction is crucial for developing therapeutic strategies for AD and T2D.