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Updated: Jun 13, 2026

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
Published on: October 3, 2025
Optimized post-GWAS analysis identifies therapeutic targets for essential thrombocythemia and polycythemia vera
Xiaoli Li1,2, Wenbin An1,2, Xin Wang1,2
1State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.
Background:
Limited insight into the biology of essential thrombocythemia (ET) and polycythemia vera (PV) has constrained therapeutic development. We therefore aimed to prioritize genetically supported molecular determinants underlying disease susceptibility and hematologic phenotypes, and to distinguish shared and subtype-specific regulation.
Methods:
We implemented an optimized post-GWAS framework combining omics-wide Bayesian colocalization with Mendelian randomization (MR) to prioritize genetically supported molecular determinants of ET and PV. Colocalization-guided MR analyses were used to infer causal relationships, with additional analyses incorporating other phenotypic traits to support biological interpretation.
Results:
Here, we show that higher genetically predicted levels of PARP1, BRAP, ERP29, PPP1CC, and RPN1 are consistently associated with risk of both ET and PV, whereas MYB is specifically associated with ET. Several biomarkers influenced blood cell counts, with BRAP, ERP29, and PPP1CC increasing platelet, red blood cell, and white blood cell counts, while MYB increased platelet production but reduced red and white blood cells. Additionally, MYB promoted BRAP, ERP29, PPP1CC, and EPO signaling while suppressing THPO, whereas MYB gene effects showed opposite patterns on these pathways, blood cell counts, and ET risk. BRAP, PPP1CC, and ERP29 exerted concordant regulatory effects on MPL, RPN1, THPO, and PARP1, except for EPO, which they negatively regulated. Finally, hypermethylation at cg17916418 and cg23511909 suppressed RPN1 expression and increased ET and PV risk, with RPN1 acting as a key mediator.
Conclusions:
This study provides a genetics-guided map of shared and subtype-specific molecular features in ET and PV, highlighting potential therapeutic pathways and molecular signals distinguishing the two diseases.
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