Williams, Julie ORCID: https://orcid.org/0000-0002-4069-0259
2026.
Are we fully exploiting genetic discoveries to understand and treat Alzheimer’s disease?
Mammalian Genome
37
(1)
, 60.
10.1007/s00335-026-10227-2
|
Preview |
PDF
- Accepted Post-Print Version
Available under License Creative Commons Attribution. Download (224kB) | Preview |
Abstract
Discovering relationships between clinical diseases and variation in DNA provides connections to putative disease pathways and novel targets for future therapies. This genetic strategy is and will continue to shape our understanding of disease mechanisms, epidemiology, advance clinical trials and drug discovery and revolutionise therapeutic development. Over the last decade genome-wide association studies (GWAS) have driven most of these advances for common diseases with genetic components (Sims et al. 2020). The effects of human genetic variability combined with the small individual effect sizes of disease associations commonly observed, have been overcome by powerful GWAS studies with stringent levels of proof, underpinned by large international collaborations with in-built replication across different laboratories and countries. These studies have been particularly informative for brain diseases, of which Alzheimer’s disease is a prime example. This commentary will provide a brief overview of the genetics of Alzheimer’s disease, illustrate how this can inform disease mechanisms and treatments and review whether we are exploiting the full potential of genetic discoveries, highlighting the failure of pharmaceutical companies to harness the wealth of genetic knowledge in clinical trials, for example.
| Item Type: | Article |
|---|---|
| Date Type: | Publication |
| Status: | Published |
| Schools: | Schools > Medicine |
| Additional Information: | RRS applied 21/07/2026 |
| Publisher: | Springer |
| ISSN: | 0938-8990 |
| Date of First Compliant Deposit: | 28 April 2026 |
| Date of Acceptance: | 28 March 2026 |
| Last Modified: | 21 Jul 2026 10:45 |
| URI: | https://orca.cardiff.ac.uk/id/eprint/186679 |
Actions (repository staff only)
![]() |
Edit Item |





Altmetric
Altmetric