Dataset Information

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

ABSTRACT: Gene 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 ¹⁸ F-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 (p_FDR < .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 (p_FDR < .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.

SUBMITTER: Zang Z

PROVIDER: S-EPMC10543112 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature

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

Zang Zhenxiang Z Zhang Xiaolong X Song Tianbin T Li Jiping J Nie Binbin B Mei Shanshan S Hu Zhi'an Z Zhang Yuqing Y Lu Jie J

Human brain mapping 20230822 16

Gene 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 <sup>18</sup> F-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 gr ...[more]

PMID: 37605831

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Project description:Importance. Biological markers of Parkinson’s disease are essential for achieving disease modification. Objective. To determine the association of SNCA blood transcript levels with prevalence of Parkinson’s disease. Background. The SNCA locus is preferentially transcribed in neurons and blood cells. Non-coding genetic variants and neuronal aggregates of α-synuclein protein associate this locus with sporadic Parkinson’s disease and suggest a potential role for abnormal SNCA transcription in the disease mechanism. Here we investigated variation in intracellular SNCA gene expression and SNCA transcript isoform abundance in circulating blood cells of cases with PD and controls in a network of biobanks that represent regional, national, and international populations. Design, Setting, Participants. Three cross-sectional, case-control studies nested in observational biomarker studies. 222 cases with early-stage clinical PD and 183 controls were enrolled from 2005 to 2010 in the Harvard Biomarker Study (HBS) at two Harvard-affiliated tertiary care centers. 76 cases with dopamine transporter imaging (DAT)-confirmed PD and 42 controls were enrolled between August 2007 and December 2008 in the Blood α-Synuclein, Gene Expression and Smell Testing as Diagnostic and Prognostic Biomarkers in Parkinson’s Disease Study (PROBE) study from 22 US tertiary care centers. 202 DAT-confirmed cases with de novo PD and 138 controls were enrolled in the Parkinson’s Progression Markers Initiative (PPMI) between July 2010 and November 2012 from 22 US and international tertiary care centers. Main Outcome Measures. Association of intracellular SNCA transcript abundance with PD estimated on analog and digital expression platforms. Results. Reduced levels of SNCA transcripts were associated with early-stage clinical PD, neuroimaging-confirmed PD, and untreated, neuroimaging-confirmed PD in accessible, peripheral blood cells from a total of 863 individuals. SNCA expression was reduced by 17%, 22%, and 16% in cases compared to controls in the HBS, PROBE, and PPMI study with P values of 0.004, 0.025, and 0.018, respectively, after adjusting for clinical, hematological, and processing covariates. Specific SNCA transcripts with long 3’ untranslated regions (UTR) and those skipping exon 5 are implicated in the accumulation and mitochondrial targeting of α-synuclein protein in Parkinson’s pathology. These transcript isoforms were linked to PD through digital expression analysis. Individuals in the lowest quartile of SNCA expression values had covariate-adjusted odds ratios for PD of 2.14 (95% C. I. 1.1-4.1), 4.5 (95% C. I. 1.3-15), and 2.1 (1.1-4.0) compared to individuals in the highest quartile of expression values in the HBS, PROBE, and PPMI study, respectively. Conclusions and Relevance. Reduced levels of SNCA expression, particularly of disease-relevant transcripts with extended 3’ UTR or exon 5 skipping, are associated with early-stage PD. These findings support a potential role for SNCA as a transcriptional marker of PD and may have implications for patient stratification and risk assessment.

Project description:BackgroundCurrent evidence on management of impulse control disorders (ICDs) in Parkinson's disease (PD) remains scarce, and exploring modifiable risk factors is crucial.ObjectiveWe evaluated the profiles of ICDs in PD patients and aimed to determine the associations between ICDs, metabolic syndrome components and other clinical features.MethodsWe enrolled patients diagnosed with PD in this study and conducted comprehensive clinical assessments.ResultsWe recruited 39 PD patients with ICDs and 66 PD patients without ICDs. Out of the 39 patients with ICDs, 19 (48.7%) had one impulse control disorder, while 20 (51.3%) had two or more. The most commonly reported symptom of ICDs was compulsive eating (48.7%). Significant differences were observed between the PD patients with and without ICDs in terms of their HbA1c levels, history of diabetes mellitus, dopamine agonist use, levodopa equivalent dose of dopamine agonists (LED DA), and Hamilton Depression Rating Scale (HAMD) scores. HbA1c levels were significantly higher in the PD patients with compulsive eating. Stepwise logistic regression analyses were performed with the dependent variables of ICDs (yes/no) and compulsive eating (yes/no). Among the 105 PD patients, those with ICDs exhibited higher levels of HbA1c, HAMD score and LED DA than those without ICDs (p < 0.01). Among 39 PD patients with ICDs, those with compulsive eating exhibited higher levels of HbA1c (OR = 2.148, 95% CI = 1.004-4.594, p < 0.05). Among 105 PD patients, those with compulsive eating exhibited higher levels of HbA1c, LED DA and HAMD score (p < 0.05).ConclusionThis study provides insights into the profiles of ICDs in PD patients and their associations with various clinical features. Compulsive eating was the most common ICDs symptom reported. Notably, HbA1c levels were found to be higher in patients with compulsive eating, indicating that poor blood glucose control may be a potential risk factor for ICDs in PD. However, it should be noted that the higher HbA1c levels could also be a consequence of compulsive eating rather than a causal factor for ICDs in PD. Further research is needed to confirm the modifiable risk factors for ICDs in PD.

Dataset Information

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

Publications

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

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