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MicroRNA Expression Levels Are Altered in the Cerebrospinal Fluid of Patients with Young-Onset Alzheimer’s Disease

McKeever, Paul M., Schneider, Raphael, Taghdiri, Foad, Weichert, Anna, Multani, Namita, Brown, Robert A., Boxer, Adam L., Karydas, Anna, Miller, Bruce, Robertson, Janice, Tartaglia, Maria Carmela·2018·Molecular Neurobiology
DOI 10.1007/s12035-018-1032-xPMC PMC6208843
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Fig. 1 Workflow for the identification of altered miRNAs in the exosomal cerebrospinal fluid obtained from young-onset Alzheimer’s disease patients versus healthy controls. Pipeline of three phases: CSF sample collection phase, discovery phase, and validation phase. CSF cerebrospinal fluid, YOAD young-onset Alzheimer’s disease, HC healthy controls, LNA locked nucleic acid. Applied Biosystems (ABI) 7900 real-time PCR; receiver operating characteristics (ROC); Gene Set Enrichment Analysis (GSEA) of Gene Ontology Biological Processes terms
Fig. 1 Workflow for the identification of altered miRNAs in the exosomal cerebrospinal fluid obtained from young-onset Alzheimer’s disease patients versus healthy controls. Pipeline of three phases: CSF sample collection phase, discovery phase, and validation phase. CSF cerebrospinal fluid, YOAD young-onset Alzheimer’s disease, HC healthy controls, LNA locked nucleic acid. Applied Biosystems (ABI) 7900 real-time PCR; receiver operating characteristics (ROC); Gene Set Enrichment Analysis (GSEA) of Gene Ontology Biological Processes termsCC BY · PubMed Central
Fig. 2 Discovery phase reveals candidate miRNAs altered in the CSF of YOAD patients versus healthy controls. a Heatmap of differentially expressed miRNAs in the CSF of YOAD patients (n = 17) versus HC (n = 12) identified using one-way ANOVA and pairwise comparisons (p < 0.05). Relative expression level normalized using the geometric mean of spike-ins UniSp6 and cel-miR-39-3p and the endogenous miR-204-5p. Rows are sorted by decreasing fold-change relative to HC. b Six additional candidate microRNAs uncovered in the discovery phase using presence/absence of expression mining and Fisher’s exact test for determining significance. *p < 0.05; **p < 0.01
Fig. 2 Discovery phase reveals candidate miRNAs altered in the CSF of YOAD patients versus healthy controls. a Heatmap of differentially expressed miRNAs in the CSF of YOAD patients (n = 17) versus HC (n = 12) identified using one-way ANOVA and pairwise comparisons (p < 0.05). Relative expression level normalized using the geometric mean of spike-ins UniSp6 and cel-miR-39-3p and the endogenous miR-204-5p. Rows are sorted by decreasing fold-change relative to HC. b Six additional candidate microRNAs uncovered in the discovery phase using presence/absence of expression mining and Fisher’s exact test for determining significance. *p < 0.05; **p < 0.01CC BY · PubMed Central
Fig. 3 Validation phase uncovers miRNAs altered in the CSF of YOAD patients versus healthy controls. Independent validation of discovery phase results with quantitative real-time PCR showing relative expression in YOAD (n = 17) versus HC (n = 12) for a miR-16-5p, b miR-125b-5p, c miR-451a, and d miR-605-5p. Significance between groups was determined using ANOVA followed by pairwise comparisons with Bonferroni correction. *p < 0.05; ****p < 0.0001
Fig. 3 Validation phase uncovers miRNAs altered in the CSF of YOAD patients versus healthy controls. Independent validation of discovery phase results with quantitative real-time PCR showing relative expression in YOAD (n = 17) versus HC (n = 12) for a miR-16-5p, b miR-125b-5p, c miR-451a, and d miR-605-5p. Significance between groups was determined using ANOVA followed by pairwise comparisons with Bonferroni correction. *p < 0.05; ****p < 0.0001CC BY · PubMed Central
Fig. 4 Performance of miRNAs at distinguishing YOAD or LOAD patients from healthy controls. Receiver operating characteristics (ROC) curves plotted as true positive rate (sensitivity) versus false positive rate (100 − specificity) for a YOAD and b LOAD. Area under the curve (AUC) was calculated using the trapezoid method, and the confidence intervals (CI) were calculated using bootstrap sampling in R (v3.4.0)
Fig. 4 Performance of miRNAs at distinguishing YOAD or LOAD patients from healthy controls. Receiver operating characteristics (ROC) curves plotted as true positive rate (sensitivity) versus false positive rate (100 − specificity) for a YOAD and b LOAD. Area under the curve (AUC) was calculated using the trapezoid method, and the confidence intervals (CI) were calculated using bootstrap sampling in R (v3.4.0)CC BY · PubMed Central
Fig. 5 Validated miRNA targets and pathways overlap with sporadic YOAD transcriptome changes. a Five-set Venn diagram showing 2899 mRNAs identified as differentially expressed in the posterior cingulate cortex (PCC) overlap of published microarray data (GSE39420). A total of 874 miRNA targets altered in the exosomes of CSF from sporadic YOAD patients overlapped with the entire microarray dataset. b KEGG pathways were identified using DAVID (v6.8) with the 874 overlapping validated miRNA targets altered in CSF-derived exosomes from sporadic YOAD. Enriched KEGG pathways (y-axis) represented as −log10(p value) (x-axis). The number of genes shared for each pathway is shown at the end of each pathway bar
Fig. 5 Validated miRNA targets and pathways overlap with sporadic YOAD transcriptome changes. a Five-set Venn diagram showing 2899 mRNAs identified as differentially expressed in the posterior cingulate cortex (PCC) overlap of published microarray data (GSE39420). A total of 874 miRNA targets altered in the exosomes of CSF from sporadic YOAD patients overlapped with the entire microarray dataset. b KEGG pathways were identified using DAVID (v6.8) with the 874 overlapping validated miRNA targets altered in CSF-derived exosomes from sporadic YOAD. Enriched KEGG pathways (y-axis) represented as −log10(p value) (x-axis). The number of genes shared for each pathway is shown at the end of each pathway barCC BY · PubMed Central
Fig. 6 Validated miRNA targets share common gene ontologies with transcripts differentially expressed in the posterior cingulate cortex of sporadic YOAD versus healthy controls. Enrichment map representing Gene Ontology (GO) terms for a biological process (BP), b GO molecular function (MF), and c GO cellular compartment enriched in the 883 overlapping targets differentially expressed in the PCC of sporadic YOAD. For the enrichment maps, red nodes = enriched in sporadic YOAD class, blue nodes = depleted in the sporadic YOAD class. Node colors are scaled based on enrichment significance. Encircled node clusters were selected using the Cytoscape (v3.4.0) plug-in AutoAnnotate (v1.1.0). Overrepresented GO terms shown in bold were selected using the WordCloud (v3.1.0) plug-in based on the proportion of redundancy between node clusters. Lists of transcripts shown under enriched GO BP terms are ranked and ≥ 2 fold change (top upregulated transcripts shown next to red nodes and downregulated transcripts next to blue nodes). False discovery rate (FDR) = q < 0.001. Gene sets were pre-ranked using Gene Set Enrichment Analysis (GSEA)
Fig. 6 Validated miRNA targets share common gene ontologies with transcripts differentially expressed in the posterior cingulate cortex of sporadic YOAD versus healthy controls. Enrichment map representing Gene Ontology (GO) terms for a biological process (BP), b GO molecular function (MF), and c GO cellular compartment enriched in the 883 overlapping targets differentially expressed in the PCC of sporadic YOAD. For the enrichment maps, red nodes = enriched in sporadic YOAD class, blue nodes = depleted in the sporadic YOAD class. Node colors are scaled based on enrichment significance. Encircled node clusters were selected using the Cytoscape (v3.4.0) plug-in AutoAnnotate (v1.1.0). Overrepresented GO terms shown in bold were selected using the WordCloud (v3.1.0) plug-in based on the proportion of redundancy between node clusters. Lists of transcripts shown under enriched GO BP terms are ranked and ≥ 2 fold change (top upregulated transcripts shown next to red nodes and downregulated transcripts next to blue nodes). False discovery rate (FDR) = q < 0.001. Gene sets were pre-ranked using Gene Set Enrichment Analysis (GSEA)CC BY · PubMed Central

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Metadata

Authors
McKeever, P. M., Schneider, R., Taghdiri, F., Weichert, A., Multani, N., Brown, R. A., Boxer, A. L., Karydas, A., Miller, B., Robertson, J., & Tartaglia, M. C.
Venue
Molecular Neurobiology
Publisher
Springer Science and Business Media LLC
Published
2018-03-30
Volume
55
Issue
12
Pages
8826-8841
ISSN
  • 0893-7648
  • 1559-1182
DOI
10.1007/s12035-018-1032-x
PMC
PMC6208843
Cited by
166
References
30
Language
en
Licence
creativecommons.org/licenses/by/4.0 (tdm)

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