| Title: | A plasma proteomics-based candidate biomarker panel predictive of amyotrophic lateral sclerosis |
| Journal: | Nature Medicine |
| Published: | 19 Aug 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/40830661/ |
| DOI: | https://doi.org/10.1038/s41591-025-03890-6 |
Publication 19718
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
Abstract
Identifying a reliable biomarker for amyotrophic lateral sclerosis (ALS) is crucial for clinical practice. Here, in this cross-sectional study, we used the Olink Explore 3072 platform to investigate plasma proteomics as a biomarker tool for this neurodegenerative condition. Thirty-three proteins were differentially abundant in the plasma of patients with ALS (n = 183) versus controls (n = 309). We replicated our findings in an independent cohort (n = 48 patients with ALS and n = 75 controls). We then applied machine learning to create a model that diagnosed ALS with high accuracy (area under the curve, 98.3%). By analyzing plasma samples from individuals before ALS symptoms emerged, we estimated the age of clinical onset and showed that the disease process - impacting skeletal muscle, nerves and energy metabolism - occurs years before symptoms appear. Our research suggests that plasma proteins can be a biomarker for this fatal disease and offers molecular insights into its prodromal phase.</p>
40 Authors
- Ruth Chia
- Ruin Moaddel
- Justin Y. Kwan
- Memoona Rasheed
- Paola Ruffo
- Natalie Landeck
- Paolo Reho
- Rosario Vasta
- Andrea Calvo
- Cristina Moglia
- Antonio Canosa
- Umberto Manera
- Allison Snyder
- Sara Saez-Atienzar
- Maurizio Grassano
- Maura Brunetti
- Federico Casale
- Anindita Ray
- Kumar Arvind
- Betul Comertpay
- Min Zhu
- J. Raphael Gibbs
- Camille Alba
- Ted M. Dawson
- Liana S. Rosenthal
- Anna J. Hall
- Alexander Y. Pantelyat
- Derek P. Narendra
- Debra J. Ehrlich
- Keenan A. Walker
- Peter Kosa
- Bibiana Bielekova
- Josephine M. Egan
- Julián Candia
- Toshiko Tanaka
- Luigi Ferrucci
- Clifton L. Dalgard
- Sonja W. Scholz
- Adriano Chiò
- Bryan J. Traynor
1 Application
| Application ID | Title |
|---|---|
| 33601 | Dissecting the genetic architecture of neurodegenerative diseases |
Enabling scientific discoveries that improve human health