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Zhu J, Liu S, Walker KA, Zhong H, Ghoneim DH, Zhang Z, Surendran P, Fahle S, Butterworth A, Alam MA, Deng HW, Wu C, Wu L. Associations between genetically predicted plasma protein levels and Alzheimer's disease risk: a study using genetic prediction models. Alzheimers Res Ther 2024; 16:8. [PMID: 38212844 PMCID: PMC10782590 DOI: 10.1186/s13195-023-01378-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2023] [Accepted: 12/30/2023] [Indexed: 01/13/2024]
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.
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Affiliation(s)
- Jingjing Zhu
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, 96813, USA
| | - Shuai Liu
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, 96813, USA
| | - Keenan A Walker
- Laboratory of Behavioral Neuroscience, National Institute On Aging, Intramural Research Program, Baltimore, MD, USA
| | - Hua Zhong
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, 96813, USA
| | - Dalia H Ghoneim
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, 96813, USA
| | - Zichen Zhang
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Praveen Surendran
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Sarah Fahle
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Adam Butterworth
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Md Ashad Alam
- Tulane Center for Biomedical Informatics and Genomics., Division of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University, 1440 Canal Street, New Orleans, LA, 70112, USA
- Center for Outcomes Research, Ochsner Clinic Foundation, New Orleans, LA, 70121, USA
| | - Hong-Wen Deng
- Tulane Center for Biomedical Informatics and Genomics., Division of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University, 1440 Canal Street, New Orleans, LA, 70112, USA
| | - Chong Wu
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
| | - Lang Wu
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, 96813, USA.
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Zhu J, Wu K, Liu S, Masca A, Zhong H, Yang T, Ghoneim DH, Surendran P, Liu T, Yao Q, Liu T, Fahle S, Butterworth A, Alam MA, Vadgama JV, Deng Y, Deng HW, Wu C, Wu Y, Wu L. Proteome-wide association study and functional validation identify novel protein markers for pancreatic ductal adenocarcinoma. Gigascience 2024; 13:giae012. [PMID: 38608280 PMCID: PMC11010651 DOI: 10.1093/gigascience/giae012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 01/17/2024] [Accepted: 03/11/2024] [Indexed: 04/14/2024] Open
Abstract
Pancreatic ductal adenocarcinoma (PDAC) remains a lethal malignancy, largely due to the paucity of reliable biomarkers for early detection and therapeutic targeting. Existing blood protein biomarkers for PDAC often suffer from replicability issues, arising from inherent limitations such as unmeasured confounding factors in conventional epidemiologic study designs. To circumvent these limitations, we use genetic instruments to identify proteins with genetically predicted levels to be associated with PDAC risk. Leveraging genome and plasma proteome data from the INTERVAL study, we established and validated models to predict protein levels using genetic variants. By examining 8,275 PDAC cases and 6,723 controls, we identified 40 associated proteins, of which 16 are novel. Functionally validating these candidates by focusing on 2 selected novel protein-encoding genes, GOLM1 and B4GALT1, we demonstrated their pivotal roles in driving PDAC cell proliferation, migration, and invasion. Furthermore, we also identified potential drug repurposing opportunities for treating PDAC. SIGNIFICANCE PDAC is a notoriously difficult-to-treat malignancy, and our limited understanding of causal protein markers hampers progress in developing effective early detection strategies and treatments. Our study identifies novel causal proteins using genetic instruments and subsequently functionally validates selected novel proteins. This dual approach enhances our understanding of PDAC etiology and potentially opens new avenues for therapeutic interventions.
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Affiliation(s)
- Jingjing Zhu
- Department of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawaiʻi at Mānoa, Honolulu, HI 96813, USA
| | - Ke Wu
- Division of Cancer Research and Training, Department of Internal Medicine, Charles R. Drew University of Medicine and Science, David Geffen UCLA School of Medicine and UCLA Jonsson Comprehensive Cancer Center, Los Angeles, CA 90095, USA
| | - Shuai Liu
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaiʻi Cancer Center, University of Hawaiʻi at Mānoa, Honolulu, HI 96813, USA
| | - Alexandra Masca
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaiʻi Cancer Center, University of Hawaiʻi at Mānoa, Honolulu, HI 96813, USA
| | - Hua Zhong
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaiʻi Cancer Center, University of Hawaiʻi at Mānoa, Honolulu, HI 96813, USA
| | - Tai Yang
- Department of Biostatistics, University of Michigan–Ann Arbor, Ann Arbor, MI 48109, USA
| | - Dalia H Ghoneim
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaiʻi Cancer Center, University of Hawaiʻi at Mānoa, Honolulu, HI 96813, USA
| | - Praveen Surendran
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB2 0SR, UK
| | - Tanxin Liu
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Qizhi Yao
- Division of Surgical Oncology, Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, TX 77030, USA
- Center for Translational Research on Inflammatory Diseases (CTRID), Michael E. DeBakey VA Medical Center, Houston, TX 77030, USA
| | - Tao Liu
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, USA
| | - Sarah Fahle
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB2 0SR, UK
| | - Adam Butterworth
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB2 0SR, UK
- NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB2 0SR, UK
| | - Md Ashad Alam
- Tulane Center for Biomedical Informatics and Genomics, Division of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University, New Orleans, LA 70112, USA
| | - Jaydutt V Vadgama
- Division of Cancer Research and Training, Department of Internal Medicine, Charles R. Drew University of Medicine and Science, David Geffen UCLA School of Medicine and UCLA Jonsson Comprehensive Cancer Center, Los Angeles, CA 90095, USA
| | - Youping Deng
- Department of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawaiʻi at Mānoa, Honolulu, HI 96813, USA
| | - Hong-Wen Deng
- Tulane Center for Biomedical Informatics and Genomics, Division of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University, New Orleans, LA 70112, USA
| | - Chong Wu
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Yong Wu
- Division of Cancer Research and Training, Department of Internal Medicine, Charles R. Drew University of Medicine and Science, David Geffen UCLA School of Medicine and UCLA Jonsson Comprehensive Cancer Center, Los Angeles, CA 90095, USA
| | - Lang Wu
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaiʻi Cancer Center, University of Hawaiʻi at Mānoa, Honolulu, HI 96813, USA
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