Quantitative 3D microscopy reveals a genetic network predicting the local activity of anti-Aβ compounds

Kirschenbaum, D.; Voigt, F.; Dadgar-Kiani, E.; Catto, F.; Trevisan, C.; Bichsel, O.; Shirani, H.; Nilsson, P. K. R.; Frontzek, K.; Paganetti, P.; Helmchen, F.; Lee, J.-H.; Aguzzi, A.

doi:10.1101/2021.01.15.426090

bioRxiv · 10.1101/2021.01.15.426090

Quantitative 3D microscopy reveals a genetic network predicting the local activity of anti-Aβ compounds

Kirschenbaum, D.·Voigt, F.·Dadgar-Kiani, E.·Catto, F.·Trevisan, C.·Bichsel, O.·Shirani, H.·Nilsson, P. K. R.·Frontzek, K.·Paganetti, P.·Helmchen, F.·Lee, J.-H.·Aguzzi, A.

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Abstract

Many efforts targeting amyloid-{beta} (A{beta}) plaques for the treatment of Alzheimers Disease thus far have resulted in failures during clinical trials. Regional and temporal heterogeneity of efficacy and dependence on plaque maturity may have contributed to these disappointing outcomes. In this study, we mapped the regional and temporal specificity of various anti-A{beta} treatments through high-resolution light-sheet imaging of electrophoretically-cleared brains. We assessed the effect on amyloid plaque formation and growth in Thy1-APP/PS1 mice subjected to {beta}-secretase inhibitors, polythiophenes, or anti-A{beta} antibodies. Each treatment showed unique spatiotemporal A{beta} clearance, with polythiophenes emerging as a potent anti-A{beta} compound. Furthermore, aligning with a spatial-transcriptomic atlas revealed transcripts that correlate with the efficacy of each A{beta} therapy. As observed in this study, there is a striking dependence of specific treatments on the location and maturity of A{beta} plaques. This may also contribute to the clinical trial failures of A{beta}-therapies, suggesting that combinatorial regimens may be significantly more effective in clearing amyloid deposition.

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Kirschenbaum, D., Voigt, F., Dadgar-Kiani, E., Catto, F., Trevisan, C., Bichsel, O., Shirani, H., Nilsson, P. K. R., Frontzek, K., Paganetti, P., Helmchen, F., Lee, J.-H., Aguzzi, A.. 2021-01-15. Quantitative 3D microscopy reveals a genetic network predicting the local activity of anti-Aβ compounds. https://doi.org/10.1101/2021.01.15.426090

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