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Abstracts from the International Congress of Parkinson’s and Movement Disorders.

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Integrating Olink Proteomics and Multimodal MRI to Reveal a Multimodal Signature of Parkinson’s Disease with REM Sleep Behavior Disorder

LH. Zhu, F. Wang, YY. Zhu, KF. Yin, CX. Liu, LF. Yang, Q. Cui, WN. Xiong, YB. Han, AL. Pang, XL. Yang (kunming, China)

Meeting: 2026 International Congress

Keywords: Rapid eye movement(REM)

Category: Parkinson's Disease: Non-Motor Symptoms (non-Cognitive/ non-Psychiatric)

Objective: To define the distinct multimodal biomarker profile of Parkinson’s disease with rapid eye movement sleep behavior disorder (PD-RBD) by integrating clinical data, Olink-based plasma proteomics, structural and functional neuroimaging, and to develop an accurate diagnostic model for this subtype.

Background: PD-RBD is an aggressive subtype marked by rapid progression. Its pathophysiology, particularly linking systemic inflammation to brain alterations, is unclear.

Method: This prospective study enrolled 176 participants (45 PD-RBD, 89 PD-nRBD, 42 controls). We assessed 92 inflammatory proteins (Olink), diffusion tensor imaging (DTI) for microstructure and glymphatic function (ALPS index), and resting-state fMRI for interhemispheric connectivity (VMHC). Ensemble machine learning was employed for feature selection and model construction, and mediation analysis was conducted to examine mechanistic relationships.

Results: Proteomic analysis identified significant upregulation of GDNF and downregulation of FGF‑21 in PD-RBD [Figure 1]. Neuroimaging revealed decreased fractional anisotropy in the left supplementary motor area, increased VMHC in the cerebellum and supplementary motor area (SMA), and a reduced ALPS index in PD-RBD [Figure 2]. Ten key multimodal features were selected, and a logistic regression model achieved exceptional diagnostic accuracy (AUC = 0.982) in distinguishing PD-RBD [Figure 3]. Mediation analysis revealed that the effects of FGF21, GDNF, and MCP-4 on PD-RBD were fully mediated by imaging markers: VMHC (for FGF21 and GDNF), ALPS index (for GDNF), and fractional anisotropy in the left SMA (for MCP-4) [Figure 4].

Conclusion: The integration of Olink proteomics with multimodal MRI through machine learning yields a highly accurate biomarker model, providing a robust framework for identifying this aggressive PD subtype and suggesting a link between systemic inflammation and brain connectivity in its pathophysiology.

Figure 1. Plasma proteomics in HC, PD-RBD, PD-nRBD

Figure 1. Plasma proteomics in HC, PD-RBD, PD-nRBD

Figure 2. Brain imaging in HC, PD-RBD, PD-nRBD

Figure 2. Brain imaging in HC, PD-RBD, PD-nRBD

Figure 3. ML model feature & results for PD-RBD

Figure 3. ML model feature & results for PD-RBD

Figure 4. Mediation of imaging & protein in PD-RBD

Figure 4. Mediation of imaging & protein in PD-RBD

To cite this abstract in AMA style:

LH. Zhu, F. Wang, YY. Zhu, KF. Yin, CX. Liu, LF. Yang, Q. Cui, WN. Xiong, YB. Han, AL. Pang, XL. Yang. Integrating Olink Proteomics and Multimodal MRI to Reveal a Multimodal Signature of Parkinson’s Disease with REM Sleep Behavior Disorder [abstract]. Mov Disord. 2026; 41 (suppl 1). https://www.mdsabstracts.org/abstract/integrating-olink-proteomics-and-multimodal-mri-to-reveal-a-multimodal-signature-of-parkinsons-disease-with-rem-sleep-behavior-disorder/. Accessed October 1, 2026.
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