Association between gene expression and functional‐metabolic architecture in Parkinson's disease

Author:

Zang Zhenxiang12ORCID,Zhang Xiaolong3ORCID,Song Tianbin12,Li Jiping4,Nie Binbin5,Mei Shanshan6,Hu Zhi'an3,Zhang Yuqing4,Lu Jie12ORCID

Affiliation:

1. Department of Radiology and Nuclear Medicine, Xuanwu Hospital Capital Medical University Beijing China

2. Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics Beijing China

3. Department of Physiology, College of Basic Medical Sciences Army Medical University Chongqing China

4. Beijing Institute of Functional Neurosurgery Xuanwu Hospital, Capital Medical University Beijing China

5. Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics Chinese Academy of Sciences Beijing China

6. Department of Neurology Xuanwu Hospital, Capital Medical University Beijing China

Abstract

AbstractGene expression plays a critical role in the pathogenesis of Parkinson's disease (PD). How gene expression profiles are correlated with functional‐metabolic architecture remains obscure. We enrolled 34 PD patients and 25 age‐and‐sex‐matched healthy controls for simultaneous 18F‐FDG‐PET/functional MRI scanning during resting state. We investigated the functional gradients and the ratio of standard uptake value. Principal component analysis was used to further combine the functional gradients and glucose metabolism into functional‐metabolic architecture. Using partial least squares (PLS) regression, we introduced the transcriptomic data from the Allen Institute of Brain Sciences to identify gene expression patterns underlying the affected functional‐metabolic architecture in PD. Between‐group comparisons revealed significantly higher gradient variation in the visual, somatomotor, dorsal attention, frontoparietal, default mode, and subcortical network (pFDR < .048) in PD. Increased FDG‐uptake was found in the somatomotor and ventral attention network while decreased FDG‐uptake was found in the visual network (pFDR < .008). Spatial correlation analysis showed consistently affected patterns of functional gradients and metabolism (p = 2.47 × 10−8). PLS analysis and gene ontological analyses further revealed that genes were mainly enriched for metabolic, catabolic, cellular response to ions, and regulation of DNA transcription and RNA biosynthesis. In conclusion, our study provided genetic pathological mechanism to explain imaging‐defined brain functional‐metabolic architecture of PD.

Publisher

Wiley

Subject

Neurology (clinical),Neurology,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology,Anatomy

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