Biomarker identification for Alzheimer’s disease through integration of comprehensive Mendelian randomization and proteomics data
Abstract Background Alzheimer’s disease (AD) is the main cause of dementia with few effective therapies. We aimed to identify potential plasma biomarkers or drug targets for AD by investigating the causal association between plasma proteins and AD by integrating comprehensive Mendelian randomization...
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| Format: | Article |
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BMC
2025-03-01
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| Series: | Journal of Translational Medicine |
| Online Access: | https://doi.org/10.1186/s12967-025-06317-5 |
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| author | Hui Zhan Davis Cammann Jeffrey L. Cummings Xianjun Dong Jingchun Chen |
| author_facet | Hui Zhan Davis Cammann Jeffrey L. Cummings Xianjun Dong Jingchun Chen |
| author_sort | Hui Zhan |
| collection | DOAJ |
| description | Abstract Background Alzheimer’s disease (AD) is the main cause of dementia with few effective therapies. We aimed to identify potential plasma biomarkers or drug targets for AD by investigating the causal association between plasma proteins and AD by integrating comprehensive Mendelian randomization (MR) and multi-omics data. Methods Using two-sample MR, cis protein quantitative trait loci (cis-pQTLs) for 1,916 plasma proteins were used as an exposure to infer their causal effect on AD liability in individuals of European ancestry, with two large-scale AD genome-wide association study (GWAS) datasets as the outcome for discovery and replication. Significant causal relationships were validated by sensitivity analyses, reverse MR analysis, and Bayesian colocalization analysis. Additionally, we investigated the causal associations at the transcriptional level with cis gene expression quantitative trait loci (cis-eQTLs) data across brain tissues and blood in European ancestry populations, as well as causal plasma proteins in African ancestry populations. Results In those of European ancestry, the genetically predicted levels of five plasma proteins (BLNK, CD2AP, GRN, PILRA, and PILRB) were causally associated with AD. Among these five proteins, GRN was protective against AD, while the rest were risk factors. Consistent causal effects were found in the brain for cis-eQTLs of GRN, BLNK, and CD2AP, while the same was true for PILRA in the blood. None of the plasma proteins were significantly associated with AD in persons of African ancestry. Conclusions Comprehensive MR analyses with multi-omics data identified five plasma proteins that had causal effects on AD, highlighting potential biomarkers or drug targets for better diagnosis and treatment for AD. |
| format | Article |
| id | doaj-art-8647d0d332004648bb1322ccea6326b6 |
| institution | OA Journals |
| issn | 1479-5876 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Translational Medicine |
| spelling | doaj-art-8647d0d332004648bb1322ccea6326b62025-08-20T01:57:25ZengBMCJournal of Translational Medicine1479-58762025-03-0123111610.1186/s12967-025-06317-5Biomarker identification for Alzheimer’s disease through integration of comprehensive Mendelian randomization and proteomics dataHui Zhan0Davis Cammann1Jeffrey L. Cummings2Xianjun Dong3Jingchun Chen4Interdisciplinary Neuroscience Program, University of Nevada, Las Vegas (UNLV)Nevada Institute of Personalized Medicine, University of Nevada, Las Vegas (UNLV)Chambers-Grundy Center for Transformative Neuroscience, Department of Brain Health, Kirk Kerkorian School of Medicine, University of Nevada, Las Vegas (UNLV)Stephen and Denise Adams Center for Parkinson’s Disease Research, Yale School of Medicine, Yale UniversityInterdisciplinary Neuroscience Program, University of Nevada, Las Vegas (UNLV)Abstract Background Alzheimer’s disease (AD) is the main cause of dementia with few effective therapies. We aimed to identify potential plasma biomarkers or drug targets for AD by investigating the causal association between plasma proteins and AD by integrating comprehensive Mendelian randomization (MR) and multi-omics data. Methods Using two-sample MR, cis protein quantitative trait loci (cis-pQTLs) for 1,916 plasma proteins were used as an exposure to infer their causal effect on AD liability in individuals of European ancestry, with two large-scale AD genome-wide association study (GWAS) datasets as the outcome for discovery and replication. Significant causal relationships were validated by sensitivity analyses, reverse MR analysis, and Bayesian colocalization analysis. Additionally, we investigated the causal associations at the transcriptional level with cis gene expression quantitative trait loci (cis-eQTLs) data across brain tissues and blood in European ancestry populations, as well as causal plasma proteins in African ancestry populations. Results In those of European ancestry, the genetically predicted levels of five plasma proteins (BLNK, CD2AP, GRN, PILRA, and PILRB) were causally associated with AD. Among these five proteins, GRN was protective against AD, while the rest were risk factors. Consistent causal effects were found in the brain for cis-eQTLs of GRN, BLNK, and CD2AP, while the same was true for PILRA in the blood. None of the plasma proteins were significantly associated with AD in persons of African ancestry. Conclusions Comprehensive MR analyses with multi-omics data identified five plasma proteins that had causal effects on AD, highlighting potential biomarkers or drug targets for better diagnosis and treatment for AD.https://doi.org/10.1186/s12967-025-06317-5 |
| spellingShingle | Hui Zhan Davis Cammann Jeffrey L. Cummings Xianjun Dong Jingchun Chen Biomarker identification for Alzheimer’s disease through integration of comprehensive Mendelian randomization and proteomics data Journal of Translational Medicine |
| title | Biomarker identification for Alzheimer’s disease through integration of comprehensive Mendelian randomization and proteomics data |
| title_full | Biomarker identification for Alzheimer’s disease through integration of comprehensive Mendelian randomization and proteomics data |
| title_fullStr | Biomarker identification for Alzheimer’s disease through integration of comprehensive Mendelian randomization and proteomics data |
| title_full_unstemmed | Biomarker identification for Alzheimer’s disease through integration of comprehensive Mendelian randomization and proteomics data |
| title_short | Biomarker identification for Alzheimer’s disease through integration of comprehensive Mendelian randomization and proteomics data |
| title_sort | biomarker identification for alzheimer s disease through integration of comprehensive mendelian randomization and proteomics data |
| url | https://doi.org/10.1186/s12967-025-06317-5 |
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