Work

Toward more predictive genetic mouse models of Alzheimer's disease

Year: 2015

Type: review

Abstract: Genetic mouse models for Alzheimer's disease (AD) have been widely used to understand aspects of the biology of the disease, but have had limited success in translating these findings to the clinic. In this review, we discuss the benefits and limitations of existing genetic models and recent advances in technologies (including high throughput sequencing and genome editing) that promise more predictive models. We summarize widely used biomarkers and behavioral tests for mouse models of AD and highlight best practices that will maximize translatability of preclinical findings.

Source: Brain Research Bulletin

DOI: 10.1016/j.brainresbull.2015.12.003

Authors: Kristen D. Onos, Stacey J. Sukoff Rizzo, Gareth R. Howell, Michael Sasner

Institutions: Jackson Laboratory, Tufts University

Language: English

Topic: Alzheimer's disease research and treatments

Subfield: Physiology (medical)

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $3,280