Improving prediction models of amyotrophic lateral sclerosis (ALS) using polygenic, pre-existing conditions, and survey-based risk scores in the UK Biobank-Reference-Cited by-同舟云学术

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Improving prediction models of amyotrophic lateral sclerosis (ALS) using polygenic, pre-existing conditions, and survey-based risk scores in the UK Biobank

Published:2024-09-09 Issue: Volume: Page:
ISSN:0340-5354
Container-title:Journal of Neurology
language:en
Short-container-title:J Neurol

Author:

Jin Weijia^ORCID,Boss Jonathan^ORCID,Bakulski Kelly M.^ORCID,Goutman Stephen A.^ORCID,Feldman Eva L.^ORCID,Fritsche Lars G.^ORCID,Mukherjee Bhramar^ORCID

Funder

ALS Association

Centers for Disease Control and Prevention

National Institutes of Health

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s00415-024-12644-2.pdf

Reference52 articles.

1. Feldman EL et al (2022) Amyotrophic lateral sclerosis. Lancet 400(10360):1363–1380

2. Goutman SA et al (2022) Recent advances in the diagnosis and prognosis of amyotrophic lateral sclerosis. Lancet Neurol 21(5):480–493

3. Goutman SA et al (2022) Emerging insights into the complex genetics and pathophysiology of amyotrophic lateral sclerosis. Lancet Neurol 21(5):465–479

4. Nowicka N et al (2019) Risk factors and emerging therapies in amyotrophic lateral sclerosis. Int J Mol Sci 20(11):2616

5. Longinetti E, Fang F (2019) Epidemiology of amyotrophic lateral sclerosis: an update of recent literature. Curr Opin Neurol 32(5):771–776

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