Identifying potential drug targets for myocardial infarction through Mendelian randomization.
<h4>Background</h4>This study explored the associations between plasma and cerebrospinal fluid (CSF) proteins and myocardial infarction (MI) risk. Identifying specific proteins as biomarkers for MI could enhance our understanding of disease mechanisms and inform clinical practice.<h4&...
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| Format: | Article |
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Public Library of Science (PLoS)
2024-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0313770 |
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| author | Xiangyou Yu Shasha Liu |
| author_facet | Xiangyou Yu Shasha Liu |
| author_sort | Xiangyou Yu |
| collection | DOAJ |
| description | <h4>Background</h4>This study explored the associations between plasma and cerebrospinal fluid (CSF) proteins and myocardial infarction (MI) risk. Identifying specific proteins as biomarkers for MI could enhance our understanding of disease mechanisms and inform clinical practice.<h4>Methods</h4>We combined protein quantitative trait loci (pQTL) data for plasma and CSF proteins with genome-wide association study (GWAS) summary statistics for MI. Mendelian Randomization (MR) analyses were conducted to establish causal relationships, supported by Bayesian colocalization and Spearman correlation analyses. For plasma proteins, we used pQTL data from Cheng et al. to select 738 cis-acting SNPs associated with 734 proteins. The "TwoSampleMR" method and inverse-variance weighted MR were applied for evaluations.<h4>Results</h4>In plasma, CD8A and HDHD2 were identified as protective factors against MI, while DPEP1 was linked to increased risk. In CSF, CD30 Ligand was associated with MI risk. Bayesian colocalization supported the association for CD8A in plasma. No significant correlation was found between plasma and CSF results, suggesting distinct mechanisms for these biomarkers.<h4>Conclusion</h4>Our study identified several plasma and CSF proteins linked to MI risk, offering new insights into the disease's biological underpinnings. These findings could guide future research on MI biomarkers and contribute to improved prevention and treatment strategies. |
| format | Article |
| id | doaj-art-1a2bf50b976b4b8ba14787b262c08bad |
| institution | Kabale University |
| issn | 1932-6203 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-1a2bf50b976b4b8ba14787b262c08bad2025-01-08T05:32:39ZengPublic Library of Science (PLoS)PLoS ONE1932-62032024-01-011912e031377010.1371/journal.pone.0313770Identifying potential drug targets for myocardial infarction through Mendelian randomization.Xiangyou YuShasha Liu<h4>Background</h4>This study explored the associations between plasma and cerebrospinal fluid (CSF) proteins and myocardial infarction (MI) risk. Identifying specific proteins as biomarkers for MI could enhance our understanding of disease mechanisms and inform clinical practice.<h4>Methods</h4>We combined protein quantitative trait loci (pQTL) data for plasma and CSF proteins with genome-wide association study (GWAS) summary statistics for MI. Mendelian Randomization (MR) analyses were conducted to establish causal relationships, supported by Bayesian colocalization and Spearman correlation analyses. For plasma proteins, we used pQTL data from Cheng et al. to select 738 cis-acting SNPs associated with 734 proteins. The "TwoSampleMR" method and inverse-variance weighted MR were applied for evaluations.<h4>Results</h4>In plasma, CD8A and HDHD2 were identified as protective factors against MI, while DPEP1 was linked to increased risk. In CSF, CD30 Ligand was associated with MI risk. Bayesian colocalization supported the association for CD8A in plasma. No significant correlation was found between plasma and CSF results, suggesting distinct mechanisms for these biomarkers.<h4>Conclusion</h4>Our study identified several plasma and CSF proteins linked to MI risk, offering new insights into the disease's biological underpinnings. These findings could guide future research on MI biomarkers and contribute to improved prevention and treatment strategies.https://doi.org/10.1371/journal.pone.0313770 |
| spellingShingle | Xiangyou Yu Shasha Liu Identifying potential drug targets for myocardial infarction through Mendelian randomization. PLoS ONE |
| title | Identifying potential drug targets for myocardial infarction through Mendelian randomization. |
| title_full | Identifying potential drug targets for myocardial infarction through Mendelian randomization. |
| title_fullStr | Identifying potential drug targets for myocardial infarction through Mendelian randomization. |
| title_full_unstemmed | Identifying potential drug targets for myocardial infarction through Mendelian randomization. |
| title_short | Identifying potential drug targets for myocardial infarction through Mendelian randomization. |
| title_sort | identifying potential drug targets for myocardial infarction through mendelian randomization |
| url | https://doi.org/10.1371/journal.pone.0313770 |
| work_keys_str_mv | AT xiangyouyu identifyingpotentialdrugtargetsformyocardialinfarctionthroughmendelianrandomization AT shashaliu identifyingpotentialdrugtargetsformyocardialinfarctionthroughmendelianrandomization |