Synergistic blood-based diagnostic value of AP3B1 and BMPR2 in Parkinson's disease

  • NPJ Parkinsons Dis. 2025 Oct 28;11(1):310. doi: 10.1038/s41531-025-01134-5.
Xiyan Zhao  #  1 ,  Li Yang  #  1 ,  Yumin Luan  2 ,  Tao Ding  2 ,  Xinglong Yang  3 ,  Xin Geng  3 ,  Tuo Zhang  4 ,  Jigang Pan  4 ,  Ziwen Xiao  5  6 ,  Wei Pan  7  8 ,  Tengxiang Chen  9  10
Affiliations
  • 1. Guizhou Institute of Precision Medicine, The Affiliated Hospital of Guizhou Medical University, Guiyang, China.
  • 2. Department of Rehabilitation, First Affiliated Hospital of Kunming Medical University, Kunming, China.
  • 3. Department of Neurology, First Affiliated Hospital of Kunming Medical University, Kunming, China.
  • 4. Guizhou Provincial Key Laboratory of Pathogenesis & Drug Research on Common Chronic Diseases, Guizhou Medical University, Guiyang, China.
  • 5. Guizhou Institute of Precision Medicine, The Affiliated Hospital of Guizhou Medical University, Guiyang, China. [email protected].
  • 6. Department of Obstetrics and Gynecology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China. [email protected].
  • 7. Guizhou Institute of Precision Medicine, The Affiliated Hospital of Guizhou Medical University, Guiyang, China. [email protected].
  • 8. Department of Obstetrics and Gynecology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China. [email protected].
  • 9. Guizhou Institute of Precision Medicine, The Affiliated Hospital of Guizhou Medical University, Guiyang, China. [email protected].
  • 10. Guizhou Provincial Key Laboratory of Pathogenesis & Drug Research on Common Chronic Diseases, Guizhou Medical University, Guiyang, China. [email protected].
  • # Contributed equally.
PMID: 41152257 DOI: 10.1038/s41531-025-01134-5
Abstract

Reliable blood-based biomarkers for Parkinson's disease (PD) are needed for minimally invasive diagnosis. We identified a synergistic mRNA biomarker pair, AP3B1 and BMPR2, detectable in blood through an integrative multi-omics workflow. DEGs from a meta-analysis of PD versus healthy controls (HCs) were intersected with DEG-enriched pathway genes and analysed via three-step SMR to identify PD risk candidates, from which machine learning (SVM-RFE and random forest) prioritized AP3B1 and BMPR2. Knockdown of each gene in SH-SY5Y-derived neurons reproduced Parkinsonian phenotypes, with protein docking and co-immunoprecipitation suggesting a direct interaction. An XGBoost model built on PPMI blood RNA-seq (n = 2585) using 25 established PD biomarkers (baseline AUC ~ 0.595) improved to 0.745 with addition of both AP3B1 and BMPR2. qRT-PCR in a cohort of clinical blood samples confirmed their downregulation in PD. These findings support AP3B1 and BMPR2 as a synergistic biomarker pair with speculative biological relevance and possible translational potential.

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