PlateletBase: A Comprehensive Knowledgebase for Platelet Research and Disease Insights

Figure 1. Database content and features A. The function of platelets in physiological and pathological processes. B. Schematic diagram of the database construction process. C. Entry statistics of various data types. CAD, coronary artery disease; DIC, disseminated intravascular coagulation; GPIb–V–IX, glycoprotein Ib–V–IX complex; vWF, von Willebrand factor; ADP, adenosine diphosphate; TXA2, thromboxane A2; mRNA, messenger RNA; miRNA, microRNA; lncRNA, long non-coding RNA; circRNA, circular RNA; GWAS, genome-wide association study; TWAS, transcriptome-wide association study; LigRec, ligand and receptor; SNP, single nucleotide polymorphism.

Figure 2. Statistics from platelet-associated genomic datasets A. Manhattan plot showing the relationship between chromosome position and −log10 P value for all platelet-related GWAS loci. The top 3 most frequent (phenotype or disease involved) loci are highlighted in orange, and SNPs with −log10 P value > 300 are labeled. B. Bar graph showing the top 10 phenotype–SNP pairs, SNPs, and genes in platelet-related GWAS loci. C. Bar graph showing the top 10 genes carrying clinical mutations associated with platelets. D. Ring diagrams showing the disease composition corresponding to the top 4 clinical gene mutations. E. Bar chart showing the distribution of top 5 tissues associated with platelet count and MPV based on TWAS data. MPV, mean platelet volume.

Figure 3. Statistics from curated platelet transcriptomic and proteomic data A. Sankey diagram showing the disease distribution of the transcriptomic datasets. The numbers in parentheses indicate sample size. B. Heatmap showing feature gene expression in platelets for several major disease types. C. Bar chart showing the enriched terms of top 150 genes highly expressed in platelets from healthy individuals. D. Sankey diagram showing the disease distribution of the proteomic data.

Figure 4. Statistics from omics knowledge and drugs associated with platelets A. Word cloud displaying all platelet-related molecular signaling pathways in the database. The font size and color are proportional to the rank of the pathways and the number of genes in each pathway, respectively. B. Bar chart showing the top 10 most frequent ligand genes. C. Bar chart showing the top 10 most frequent receptor genes. D. Bar chart showing the top 10 most frequent platelet-associated drug-target genes. E. Venn diagram showing gene overlap.

Figure 5. Case report of gray platelet syndrome A. NBEAL2-related GWAS locus information. B. Molecular pathway information associated with NBEAL2. C. List of drugs related to NBEAL2. D. Protein network diagram related to NBEAL2. TF, transcription factor; RBP, RNA-binding protein.

Figure 6. Case report of angina pectoris A. Basic information about the differentially expressed gene CAPN10 related to angina pectoris. B. Box plots showing the expression levels of CAPN10 in angina pectoris vs. “others” (left) and in angina pectoris vs. healthy individuals (right). “Others” indicates all patients with other disease states. C. CAPN10 expression rank across all conditions. D. The top 100 genes exhibiting high expression-based correlation with CAPN10 at the same biological level were identified. These genes were found to be enriched in platelet-related molecular signaling pathways through enrichment analysis and visualized using the plot function in PlateletBase. TPM, transcripts per million.