Multi-omics differences in the bone marrow between essential thrombocythemia and prefibrotic primary myelofibrosis.
Anqi ZhangTing SunDandan YuRongfeng FuXiaofan LiuFeng XueWei LiuMankai JuXinyue DaiHuan DongWenjing GuJia ChenYing ChiHuiyuan LiWentian WangRenchi YangYunfei ChenLei ZhangPublished in: Clinical and experimental medicine (2024)
Essential thrombocythemia (ET) and prefibrotic primary myelofibrosis (pre-PMF) are Philadelphia chromosome-negative myeloproliferative neoplasms. These conditions share overlapping clinical presentations; however, their prognoses differ significantly. Current morphological diagnostic methods lack reliability in subtype differentiation, underlining the need for improved diagnostics. The aim of this study was to investigate the multi-omics alterations in bone marrow biopsies of patients with ET and pre-PMF to improve our understanding of the nuanced diagnostic characteristics of both diseases. We performed proteomic analysis with 4D direct data-independent acquisition and microbiome analysis with 2bRAD-M sequencing technology to identify differential protein and microbe levels between untreated patients with ET and pre-PMF. Laboratory and multi-omics differences were observed between ET and pre-PMF, encompassing diverse pathways, such as lipid metabolism and immune response. The pre-PMF group showed an increased neutrophil-to-lymphocyte ratio and decreased high-density lipoprotein and cholesterol levels. Protein analysis revealed significantly higher CXCR2, CXCR4, and MX1 levels in pre-PMF, while APOC3, APOA4, FABP4, C5, and CFB levels were elevated in ET, with diagnostic accuracy indicated by AUC values ranging from 0.786 to 0.881. Microbiome assessment identified increased levels of Mycobacterium, Xanthobacter, and L1I39 in pre-PMF, whereas Sphingomonas, Brevibacillus, and Pseudomonas_E were significantly decreased, with AUCs for these genera ranging from 0.833 to 0.929. Our study provides preliminary insights into the proteomic and microbiome variations in the bone marrow of patients with ET and pre-PMF, identifying specific proteins and bacterial genera that warrant further investigation as potential diagnostic indicators. These observations contribute to our evolving understanding of the multi-omics variations and possible mechanisms underlying ET and pre-PMF.
Keyphrases
- bone marrow
- single cell
- immune response
- mesenchymal stem cells
- acute lymphoblastic leukemia
- dna methylation
- machine learning
- gene expression
- binding protein
- mycobacterium tuberculosis
- inflammatory response
- escherichia coli
- electronic health record
- toll like receptor
- staphylococcus aureus
- fatty acid
- deep learning
- cystic fibrosis
- pseudomonas aeruginosa
- amino acid
- data analysis
- low density lipoprotein
- chronic myeloid leukemia