Associations between genetically predicted plasma protein levels and Alzheimer’s disease risk: a study using genetic prediction models

Jingjing Zhu; Shuai Liu; Keenan A. Walker; Hua Zhong; Dalia H. Ghoneim; Zichen Zhang; Praveen Surendran; Sarah Fahle; Adam Butterworth; Md Ashad Alam; Hong-Wen Deng; Chong Wu; Lang Wu

doi:10.1186/s13195-023-01378-4

Alzheimer’s Research & Therapy (Jan 2024)

Associations between genetically predicted plasma protein levels and Alzheimer’s disease risk: a study using genetic prediction models

Jingjing Zhu,
Shuai Liu,
Keenan A. Walker,
Hua Zhong,
Dalia H. Ghoneim,
Zichen Zhang,
Praveen Surendran,
Sarah Fahle,
Adam Butterworth,
Md Ashad Alam,
Hong-Wen Deng,
Chong Wu,
Lang Wu

Affiliations

Jingjing Zhu: Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa
Shuai Liu: Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa
Keenan A. Walker: Laboratory of Behavioral Neuroscience, National Institute On Aging, Intramural Research Program
Hua Zhong: Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa
Dalia H. Ghoneim: Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa
Zichen Zhang: Department of Biostatistics, The University of Texas MD Anderson Cancer Center
Praveen Surendran: MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge
Sarah Fahle: MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge
Adam Butterworth: MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge
Md Ashad Alam: Tulane Center for Biomedical Informatics and Genomics., Division of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University
Hong-Wen Deng: Tulane Center for Biomedical Informatics and Genomics., Division of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University
Chong Wu: Department of Biostatistics, The University of Texas MD Anderson Cancer Center
Lang Wu: Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa

DOI: https://doi.org/10.1186/s13195-023-01378-4
Journal volume & issue: Vol. 16, no. 1
pp. 1 – 16

Abstract

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Abstract Background Specific peripheral proteins have been implicated to play an important role in the development of Alzheimer’s disease (AD). However, the roles of additional novel protein biomarkers in AD etiology remains elusive. The availability of large-scale AD GWAS and plasma proteomic data provide the resources needed for the identification of causally relevant circulating proteins that may serve as risk factors for AD and potential therapeutic targets. Methods We established and validated genetic prediction models for protein levels in plasma as instruments to investigate the associations between genetically predicted protein levels and AD risk. We studied 71,880 (proxy) cases and 383,378 (proxy) controls of European descent. Results We identified 69 proteins with genetically predicted concentrations showing associations with AD risk. The drugs almitrine and ciclopirox targeting ATP1A1 were suggested to have a potential for being repositioned for AD treatment. Conclusions Our study provides additional insights into the underlying mechanisms of AD and potential therapeutic strategies.

Published in Alzheimer’s Research & Therapy

ISSN: 1758-9193 (Online)
Publisher: BMC
Country of publisher: United Kingdom
LCC subjects: Medicine: Internal medicine: Neurosciences. Biological psychiatry. Neuropsychiatry: Neurology. Diseases of the nervous system
Website: https://alzres.biomedcentral.com

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Abstract

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