Converging peripheral blood microRNA profiles in Parkinson's disease and progressive supranuclear palsy

Abstract

MicroRNAs act via targeted suppression of messenger RNA translation in the DNA-RNA-protein axis. The dysregulation of microRNA(s) reflects the epigenetic changes affecting the cellular processes in multiple disorders. To understand the complex effect of dysregulated microRNAs linked to neurodegeneration, we performed a cross-sectional microRNA expression analysis in idiopathic Parkinson's disease (n = 367), progressive supranuclear palsy (n = 35) and healthy controls (n = 416) from the Luxembourg Parkinson's Study, followed by prediction modelling, enriched pathway analysis and target simulation of dysregulated microRNAs using probabilistic Boolean modelling. Forty-six microRNAs were identified to be dysregulated in Parkinson's disease versus controls and 16 in progressive supranuclear palsy versus controls with 4 overlapping significantly dysregulated microRNAs between the comparisons. Predictive power of microRNA subsets (including up to 100 microRNAs) was modest for differentiating Parkinson's disease or progressive supranuclear palsy from controls (maximal cross-validated area under the receiver operating characteristic curve 0.76 and 0.86, respectively) and low for progressive supranuclear palsy versus Parkinson's disease (maximal cross-validated area under the receiver operating characteristic curve 0.63). The enriched pathway analysis revealed natural killer cell pathway to be dysregulated in both, Parkinson's disease and progressive supranuclear palsy versus controls, indicating that the immune system might play an important role in both diseases. Probabilistic Boolean modelling of pathway dynamics affected by dysregulated microRNAs in Parkinson's disease and progressive supranuclear palsy revealed partially overlapping dysregulation in activity of the transcription factor EB, endoplasmic reticulum stress signalling, calcium signalling pathway, dopaminergic transcription and peroxisome proliferator-activated receptor gamma coactivator-1α activity, though involving different mechanisms. These findings indicated a partially convergent (sub)cellular end-point dysfunction at multiple levels in Parkinson's disease and progressive supranuclear palsy, but with distinctive underlying molecular mechanisms.

Keywords: Boolean modelling; Parkinson's disease; microRNA; natural killer cell; progressive supranuclear palsy.

Graphical Abstract

Figure 1

Flowchart describing selection criteria and analytical pipeline in Luxembourg Parkinson's Study. PD, Parkinson's disease; iPD, idiopathic Parkinson’s disease; PSP, progressive supranuclear palsy; miRNA, microRNA.

Figure 2

miRNA expression analysis in Luxembourg Parkinson's Study. Volcano plots showing minus log₁₀ transformed P-values (significance, y-axis) against log₂ fold change (effect size, x-axis) of miRNA expression assessed by microarray. The first row shows miRNA expression without adjustment for confounders (A-K). The second row shows results of MLR adjusting for confounders (L to P adjusted for age and sex; Q to S adjusted for age; T to V adjusted for sex). Sample size per group and per comparison is shown in brackets next to the plot designation letter. Significant P-values at FWER of 5% (Bonferroni) are above the dashed line, and significant P-values at an FDR of 5% (Benjamini–Hochberg) are highlighted in colour. Significantly upregulated and downregulated are highlighted in red and blue colours, respectively. Number of significantly dysregulated miRNA(s) in bottom of each plot at FWER and at FDR in brackets (left corner, negative effect size; right corner, positive effect size). iPD, idiopathic Parkinson's disease; EPD, early-stage Parkinson’s disease; EPSP, earlier-stage progressive supranuclear palsy; HC, controls; PSP, progressive supranuclear palsy; AAA, age at assessment; sex, female/male.

Figure 3

Predictive modelling between disease groups and controls using miRNA subsets. Cross-validated AUC from logistic lasso regression (binary outcomes) on the y-axis against maximum number of miRNAs on the x-axis for intergroup prediction of idiopathic Parkinson's disease (n = 367), HC (n = 416) and progressive supranuclear palsy (n = 35). Early-stage Parkinson’s disease (n = 226) and earlier-stage progressive supranuclear palsy (n = 28) were defined by disease duration since diagnosis ≤ 5 years. The second row also includes the unpenalized covariates age and sex in the models (HCvPD_adj, HCvPSP_adj and PDvPSP_adj). The numbers at the bottom indicate the AUC with at most 0, 10 and 100 miRNAs (non-zero coefficients other than intercept, AAA and sex). The black and grey dots show the predictive performance of standard lasso and ridge regression, respectively.