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Bone marrow proteomic profiling reveals TMEM109 as a biomarker for relapse in thrombotic thrombocytopenic purpura
Qing Wen1, Jia Chen1, Ting Sun1
1State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Tianjin Key Laboratory of Gene Therapy for Blood Diseases, Chinese Academy of Medical Sciences Key Laboratory of Gene Therapy for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China; Tianjin Institutes of Health Science, Tianjin, China.
Background:
Thrombotic thrombocytopenic purpura (TTP) is a rare but life-threatening thrombotic microangiopathy, with a substantial risk of relapse despite advances in therapy. Robust biomarkers to predict relapse are urgently needed to inform risk-adapted management. This study represents the first application of bone marrow proteomic profiling in TTP to explore relapse-associated biomarkers.
Objectives:
To identify clinical risk factors and novel protein biomarkers for relapse in TTP through integrated clinical and bone marrow proteomic analyses.
Methods:
We conducted a retrospective cohort study involving 123 patients diagnosed with TTP at a single center. Clinical and laboratory variables at initial presentation were analyzed to identify potential predictors of relapse using Cox proportional hazards models. To explore molecular correlates of relapse, bone marrow paraffin-embedded samples from 18 patients were subjected to quantitative proteomic profiling. Machine learning algorithms were applied to identify candidate relapse-associated proteins. Selected proteins were subsequently validated by immunohistochemistry of corresponding tissue sections.
Results:
Age ≤30 years and severe neuropsychiatric symptoms were independently associated with increased relapse risk, but demonstrated only moderate predictive performance (area under the curve = 0.706). Proteomic profiling revealed TMEM109 as a relapse-associated protein with superior discriminative capacity (area under the curve = 0.929). Immunohistochemistry analysis confirmed reduced TMEM109 expression in relapsed patients (P < .0001).
Conclusion:
TMEM109 is a promising biomarker for predicting TTP relapse. While clinical factors such as age and neuropsychiatric symptoms provide valuable prognostic information, TMEM109 may enhance relapse-risk stratification, offering potential for individualized monitoring and therapeutic decision-making. These findings underscore the value of proteomic profiling in complementing clinical evaluation in TTP.
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