Mining genetic, transcriptomic and imaging data in Parkinson’s disease

Cerri, Guglielmo; Tognon, Manuel; Altmann, André; Giugno, Rosalba

doi:10.1109/ichi52183.2021.00105

Cited by 3 publications

(3 citation statements)

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“…This may be reflected in our non-significant interaction effects. On the other hand, the association of rs9638616 and brain imaging measures has not previously been investigated, and studies of similar or smaller sample sizes have shown significant associations for SNVs with brain phenotype [16][17][18][21][22][23][24][25][26][27]. Based on comparable imaging genetic studies of individual risk variants and PD brain phenotypes, our study is sufficiently powered for similar-sized effects (Supplementary Material 1).…”

Section: Discussionmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

“…Imaging-genetic studies of PD have analyzed individual candidate genes and single-nucleotide variants (SNVs) in sample sizes in the range of tens to hundreds [16][17][18][21][22][23][24][25][26][27], finding varied associations to brain structure and function. Indeed, despite brain microstructure and function undergoing a complex regulation, these studies show that multiple different SNVs are individually penetrant for MRI-derived brain phenotypes [16][17][18][21][22][23][24][25][26][27]. However, no study has evaluated rs9638616, no study has assessed a range of voxelwise measures of tract microstructure, functional connectivity or cortical morphology together in a candidate-SNV approach, and no study has investigated whether brain changes mediate the relationship between genotype and PD-associated symptoms, which could provide causal evidence for a pathophysiological mechanism [28].…”

Section: Introductionmentioning

confidence: 99%

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Parkinson’s Disease Risk Variant rs9638616 is Non-Specifically Associated with Altered Brain Structure and Function

Welton,

Teo,

Chan

et al. 2024

Journal of Parkinson’s Disease

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Background: A genome-wide association study (GWAS) variant associated with Parkinson’s disease (PD) risk in Asians, rs9638616, was recently reported, and maps to WBSCR17/GALNT17, which is involved in synaptic transmission and neurite development. Objective: To test the association of the rs9638616 T allele with imaging-derived measures of brain microstructure and function. Methods: We analyzed 3-Tesla MRI and genotyping data from 116 early PD patients (aged 66.8±9.0 years; 39% female; disease duration 1.25±0.71 years) and 57 controls (aged 68.7±7.4 years; 54% female), of Chinese ethnicity. We performed voxelwise analyses for imaging-genetic association of rs9638616 T allele with white matter tract fractional anisotropy (FA), grey matter volume and resting-state network functional connectivity. Results: The rs9638616 T allele was associated with widespread lower white matter FA (t = –1.75, p = 0.042) and lower functional connectivity of the supplementary motor area (SMA) (t = –5.05, p = 0.001), in both PD and control groups. Interaction analysis comparing the association of rs9638616 and FA between PD and controls was non-significant. These imaging-derived phenotypes mediated the association of rs9638616 to digit span (indirect effect: β= –0.21 [–0.42,–0.05], p = 0.031) and motor severity (indirect effect: β= 0.15 [0.04,0.26], p = 0.045). Conclusions: We have shown that a novel GWAS variant which is biologically linked to synaptic transmission is associated with white matter tract and functional connectivity dysfunction in the SMA, supported by changes in clinical motor scores. This provides pathophysiologic clues linking rs9638616 to PD risk and might contribute to future risk stratification models.

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