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Integrating plasma proteomes with genome-wide association data for causal protein identification in multiple myeloma

BACKGROUND: Multiple myeloma (MM) is a severely debilitating and fatal B-cell neoplastic disease. The discovery of disease-associated proteins with causal genetic evidence offers a chance to uncover novel therapeutic targets. METHODS: First, we comprehensively investigated the causal association bet...

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Autores principales: Wang, Qiangsheng, Shi, Qiqin, Wang, Zhenqian, Lu, Jiawen, Hou, Jian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10542236/
https://www.ncbi.nlm.nih.gov/pubmed/37775746
http://dx.doi.org/10.1186/s12916-023-03086-0
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author Wang, Qiangsheng
Shi, Qiqin
Wang, Zhenqian
Lu, Jiawen
Hou, Jian
author_facet Wang, Qiangsheng
Shi, Qiqin
Wang, Zhenqian
Lu, Jiawen
Hou, Jian
author_sort Wang, Qiangsheng
collection PubMed
description BACKGROUND: Multiple myeloma (MM) is a severely debilitating and fatal B-cell neoplastic disease. The discovery of disease-associated proteins with causal genetic evidence offers a chance to uncover novel therapeutic targets. METHODS: First, we comprehensively investigated the causal association between 2994 proteins and MM through two-sample mendelian randomization (MR) analysis using summary-level data from public genome-wide association studies of plasma proteome (N = 3301 healthy individuals) and MM (598 cases and 180,756 controls). Sensitivity analyses were performed for these identified causal proteins. Furthermore, we pursued the exploration of enriched biological pathways, prioritized the therapeutic proteins, and evaluated their druggability using the KEGG pathway analysis, MR-Bayesian model averaging analysis, and cross-reference with current databases, respectively. RESULTS: We identified 13 proteins causally associated with MM risk (false discovery rate corrected P < 0.05). Six proteins were positively associated with the risk of MM, including nicotinamide phosphoribosyl transferase (NAMPT; OR [95% CI]: 1.35 [1.18, 1.55]), tyrosine kinase with immunoglobulin-like and EGF-like domains 1 (TIE1; 1.14 [1.06, 1.22]), neutrophil cytosol factor 2 (NCF2; 1.27 [1.12, 1.44]), carbonyl reductase 1, cAMP-specific 3',5'-cyclic phosphodiesterase 4D (PDE4D), platelet-activating factor acetylhydrolase IB subunit beta (PAFAH1B2). Seven proteins were inversely associated with MM, which referred to suppressor of cytokine signaling 3 (SOCS3; 0.90 [0.86, 0.94]), Fc-gamma receptor III-B (FCGR3B; 0.75 [0.65,0.86]), glypican-1 (GPC1; 0.69 [0.58,0.83]), follistatin-related protein 1, protein tyrosine phosphatase non-receptor type 4 (PTPN4), granzyme B, complement C1q subcomponent subunit C (C1QC). Three of the causal proteins, SOCS3, FCGR3B, and NCF2, were enriched in the osteoclast differentiation pathway in KEGG enrichment analyses while GPC1 (marginal inclusion probability (MIP):0.993; model averaged causal effects (MACE): − 0.349), NAMPT (MIP:0.433; MACE: − 0.113), and NCF2 (MIP:0.324; MACE:0.066) ranked among the top three MM-associated proteins according to MR-BMA analyses. Furthermore, therapeutics targeting four proteins are currently under evaluation, five are druggable and four are future breakthrough points. CONCLUSIONS: Our analysis revealed a set of 13 novel proteins, including six risk and seven protective proteins, causally linked to MM risk. The discovery of these MM-associated proteins opens up the possibility for identifying novel therapeutic targets, further advancing the integration of genome and proteome data for drug development. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12916-023-03086-0.
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spelling pubmed-105422362023-10-03 Integrating plasma proteomes with genome-wide association data for causal protein identification in multiple myeloma Wang, Qiangsheng Shi, Qiqin Wang, Zhenqian Lu, Jiawen Hou, Jian BMC Med Research Article BACKGROUND: Multiple myeloma (MM) is a severely debilitating and fatal B-cell neoplastic disease. The discovery of disease-associated proteins with causal genetic evidence offers a chance to uncover novel therapeutic targets. METHODS: First, we comprehensively investigated the causal association between 2994 proteins and MM through two-sample mendelian randomization (MR) analysis using summary-level data from public genome-wide association studies of plasma proteome (N = 3301 healthy individuals) and MM (598 cases and 180,756 controls). Sensitivity analyses were performed for these identified causal proteins. Furthermore, we pursued the exploration of enriched biological pathways, prioritized the therapeutic proteins, and evaluated their druggability using the KEGG pathway analysis, MR-Bayesian model averaging analysis, and cross-reference with current databases, respectively. RESULTS: We identified 13 proteins causally associated with MM risk (false discovery rate corrected P < 0.05). Six proteins were positively associated with the risk of MM, including nicotinamide phosphoribosyl transferase (NAMPT; OR [95% CI]: 1.35 [1.18, 1.55]), tyrosine kinase with immunoglobulin-like and EGF-like domains 1 (TIE1; 1.14 [1.06, 1.22]), neutrophil cytosol factor 2 (NCF2; 1.27 [1.12, 1.44]), carbonyl reductase 1, cAMP-specific 3',5'-cyclic phosphodiesterase 4D (PDE4D), platelet-activating factor acetylhydrolase IB subunit beta (PAFAH1B2). Seven proteins were inversely associated with MM, which referred to suppressor of cytokine signaling 3 (SOCS3; 0.90 [0.86, 0.94]), Fc-gamma receptor III-B (FCGR3B; 0.75 [0.65,0.86]), glypican-1 (GPC1; 0.69 [0.58,0.83]), follistatin-related protein 1, protein tyrosine phosphatase non-receptor type 4 (PTPN4), granzyme B, complement C1q subcomponent subunit C (C1QC). Three of the causal proteins, SOCS3, FCGR3B, and NCF2, were enriched in the osteoclast differentiation pathway in KEGG enrichment analyses while GPC1 (marginal inclusion probability (MIP):0.993; model averaged causal effects (MACE): − 0.349), NAMPT (MIP:0.433; MACE: − 0.113), and NCF2 (MIP:0.324; MACE:0.066) ranked among the top three MM-associated proteins according to MR-BMA analyses. Furthermore, therapeutics targeting four proteins are currently under evaluation, five are druggable and four are future breakthrough points. CONCLUSIONS: Our analysis revealed a set of 13 novel proteins, including six risk and seven protective proteins, causally linked to MM risk. The discovery of these MM-associated proteins opens up the possibility for identifying novel therapeutic targets, further advancing the integration of genome and proteome data for drug development. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12916-023-03086-0. BioMed Central 2023-09-29 /pmc/articles/PMC10542236/ /pubmed/37775746 http://dx.doi.org/10.1186/s12916-023-03086-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Wang, Qiangsheng
Shi, Qiqin
Wang, Zhenqian
Lu, Jiawen
Hou, Jian
Integrating plasma proteomes with genome-wide association data for causal protein identification in multiple myeloma
title Integrating plasma proteomes with genome-wide association data for causal protein identification in multiple myeloma
title_full Integrating plasma proteomes with genome-wide association data for causal protein identification in multiple myeloma
title_fullStr Integrating plasma proteomes with genome-wide association data for causal protein identification in multiple myeloma
title_full_unstemmed Integrating plasma proteomes with genome-wide association data for causal protein identification in multiple myeloma
title_short Integrating plasma proteomes with genome-wide association data for causal protein identification in multiple myeloma
title_sort integrating plasma proteomes with genome-wide association data for causal protein identification in multiple myeloma
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10542236/
https://www.ncbi.nlm.nih.gov/pubmed/37775746
http://dx.doi.org/10.1186/s12916-023-03086-0
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