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. 2024 Apr 30;22(1):404.
doi: 10.1186/s12967-024-05178-8.

​Comprehensive mendelian randomization analysis of plasma proteomics to identify new therapeutic targets for the treatment of coronary heart disease and myocardial infarction

Ziyi Sun #  1   2 , Zhangjun Yun #  2   3 , Jianguo Lin #  1   4 , Xiaoning Sun  1   4 , Qingqing Wang  1 , Jinlong Duan  5 , Cheng Li  6 , Xiaoxiao Zhang  1   4 , Siyu Xu  1   2 , Zeqi Wang  7 , Xingjiang Xiong #  8 , Kuiwu Yao #  9   10
Affiliations

​Comprehensive mendelian randomization analysis of plasma proteomics to identify new therapeutic targets for the treatment of coronary heart disease and myocardial infarction

Ziyi Sun et al. J Transl Med. .

Abstract

Background: Ischemic heart disease is one of the leading causes of mortality worldwide, and thus calls for development of more effective therapeutic strategies. This study aimed to identify potential therapeutic targets for coronary heart disease (CHD) and myocardial infarction (MI) by investigating the causal relationship between plasma proteins and these conditions.

Methods: A two-sample Mendelian randomization (MR) study was performed to evaluate more than 1600 plasma proteins for their causal associations with CHD and MI. The MR findings were further confirmed through Bayesian colocalization, Summary-data-based Mendelian Randomization (SMR), and Transcriptome-Wide Association Studies (TWAS) analyses. Further analyses, including enrichment analysis, single-cell analysis, MR analysis of cardiovascular risk factors, phenome-wide Mendelian Randomization (Phe-MR), and protein-protein interaction (PPI) network construction were conducted to verify the roles of selected causal proteins.

Results: Thirteen proteins were causally associated with CHD, seven of which were also causal for MI. Among them, FES and PCSK9 were causal proteins for both diseases as determined by several analytical methods. PCSK9 was a risk factor of CHD (OR = 1.25, 95% CI: 1.13-1.38, P = 7.47E-06) and MI (OR = 1.36, 95% CI: 1.21-1.54, P = 2.30E-07), whereas FES was protective against CHD (OR = 0.68, 95% CI: 0.59-0.79, P = 6.40E-07) and MI (OR = 0.65, 95% CI: 0.54-0.77, P = 5.38E-07). Further validation through enrichment and single-cell analysis confirmed the causal effects of these proteins. Moreover, MR analysis of cardiovascular risk factors, Phe-MR, and PPI network provided insights into the potential drug development based on the proteins.

Conclusions: This study investigated the causal pathways associated with CHD and MI, highlighting the protective and risk roles of FES and PCSK9, respectively. FES. Specifically, the results showed that these proteins are promising therapeutic targets for future drug development.

Keywords: Biomarker; Coronary heart disease; Drug target; Myocardial infarction; Protein; Proteome-wide mendelian randomization.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Flowchart of the study design. CHD coronary heart disease, MI myocardialinfarction
Fig. 2
Fig. 2
Genetically predicted circulating proteins in relation to CHD and MI risk. MR volcano plots of plasma proteins versus risk of (a) CHD and (b) MI. (a) and (b) show MR analyses of plasma proteins on CHD and MI risk using Wald ratios or IVW, respectively. OR for increased risk of CHD or MI were expressed as per SD increase in plasma protein levels. Forest plot results of circulating proteins in the discovery and replication phases in relation to (c) CHD and (d) MI risk. OR are scaled to per one SD increase in the genetically predicted circulating proteins levels. Color differences represent different data sets. *, P < 0.05, **, P < 0.01, ***, P < 0.001
Fig. 3
Fig. 3
Results of colocalization analysis of (a) CHD causal proteins and (b) MI causal proteins. Circle size indicates the colocalization P value for PPH4, and the circle’s color indicates the evidence’s classification. (c) Heatmap of MR analysis of 13 causal proteins with 18 cardiovascular risk factors. In each cell, the upper value represents the OR value, and the P value is in parentheses
Fig. 4
Fig. 4
Results of Phe-MR analysis of (a) PCSK9 and (b) FES with 1403 disease traits. Horizontal coordinates represent different disease categories. The horizontal dashed line corresponds to P = 3.56 × 10 − 5 (0.05/1403). Diseases or characteristics statistically significant with causal proteins are labeled
Fig. 5
Fig. 5
Enrichment analysis and PPI network results. Results of DO enrichment analysis for (a) 13 CHD causal proteins and (b) 7 MI causal proteins. Horizontal coordinates represent the proportion of genes corresponding to causal proteins to the total gene set. Vertical coordinates represent disease entries. (c) PPI network of 13 CHD causal proteins and (d) 7 MI causal proteins. Purple represents causal proteins, green represents corresponding drug proteins, intersecting proteins are represented by half purple and half green, and edges represent interactions between proteins
Fig. 6
Fig. 6
Expression of genes encoding causal proteins at the single-cell level. (a) Cells from MI and SAP samples were annotated into four cell subpopulations. FES gene expression in (b) MI and (c) SAP samples. The closer the color to yellow, the stronger the expression
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