Excessive local host-graft connectivity in aging and amyloid-loaded brain.

Abstract:

Transplantation is a clinically relevant approach for brain repair, but much remains to be understood about influences of the disease environment on transplant connectivity. To explore the effect of amyloid pathology in Alzheimer's disease (AD) and aging, we examined graft connectivity using monosynaptic rabies virus tracing in APP/PS1 mice and in 16- to 18-month-old wild-type (WT) mice. Transplanted neurons differentiated within 4 weeks and integrated well into the host visual cortex, receiving input from the appropriate brain regions for this area. Unexpectedly, we found a prominent several-fold increase in local inputs, in both amyloid-loaded and aged environments. State-of-the-art deep proteome analysis using mass spectrometry highlights complement system activation as a common denominator of environments promoting excessive local input connectivity. These data therefore reveal the key role of the host pathology in shaping the input connectome, calling for caution in extrapolating results from one pathological condition to another.

SEEK ID: http://lmmeisd-2.srv.mwn.de/publications/67

PubMed ID: 35687689

DOI: 10.1126/sciadv.abg9287

Projects: Published Datasets

Publication type: Journal

Journal: Science advances

Citation: Science advances,8(23):eabg9287

Date Published: 10th Jun 2022

URL:

Registered Mode: manually

Authors: Judith Thomas, Maria Fernanda Martinez-Reza, Manja Thorwirth, Yvette Zarb, Karl-Klaus Conzelmann, Stefanie M Hauck, Sofia Grade, Magdalena Götz

help Submitter
Citation
Thomas, J., Martinez-Reza, M. F., Thorwirth, M., Zarb, Y., Conzelmann, K.-K., Hauck, S. M., Grade, S., & Götz, M. (2022). Excessive local host-graft connectivity in aging and amyloid-loaded brain. In Science Advances (Vol. 8, Issue 23). American Association for the Advancement of Science (AAAS). https://doi.org/10.1126/sciadv.abg9287
Activity

Views: 98

Created: 15th Oct 2024 at 13:12

help Tags

This item has not yet been tagged.

help Attributions

None

Powered by
(v.1.15.0)
Copyright © 2008 - 2024 The University of Manchester and HITS gGmbH