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Meta-analyses identify differentially expressed micrornas in Parkinson's disease.
Ann Neurol. 2019 06; 85(6):835-851.AN

Abstract

OBJECTIVE

MicroRNA (miRNA)-mediated (dys)regulation of gene expression has been implicated in Parkinson's disease (PD), although results of miRNA expression studies remain inconclusive. We aimed to identify miRNAs that show consistent differential expression across all published expression studies in PD.

METHODS

We performed a systematic literature search on miRNA expression studies in PD and extracted data from eligible publications. After stratification for brain, blood, and cerebrospinal fluid (CSF)-derived specimen, we performed meta-analyses across miRNAs assessed in three or more independent data sets. Meta-analyses were performed using effect-size- and p-value-based methods, as applicable.

RESULTS

After screening 599 publications, we identified 47 data sets eligible for meta-analysis. On these, we performed 160 meta-analyses on miRNAs quantified in brain (n = 125), blood (n = 31), or CSF (n = 4). Twenty-one meta-analyses were performed using effect sizes. We identified 13 significantly (Bonferroni-adjusted α = 3.13 × 10-4) differentially expressed miRNAs in brain (n = 3) and blood (n = 10) with consistent effect directions across studies. The most compelling findings were with hsa-miR-132-3p (p = 6.37 × 10-5), hsa-miR-497-5p (p = 1.35 × 10-4), and hsa-miR-133b (p = 1.90 × 10-4) in brain and with hsa-miR-221-3p (p = 4.49 × 10-35), hsa-miR-214-3p (p = 2.00 × 10-34), and hsa-miR-29c-3p (p = 3.00 × 10-12) in blood. No significant signals were found in CSF. Analyses of genome-wide association study data for target genes of brain miRNAs showed significant association (α = 9.40 × 10-5) of genetic variants in nine loci.

INTERPRETATION

We identified several miRNAs that showed highly significant differential expression in PD. Future studies may assess the possible role of the identified brain miRNAs in pathogenesis and disease progression as well as the potential of the top blood miRNAs as biomarkers for diagnosis, progression, or prediction of PD. ANN NEUROL 2019;85:835-851.

Authors+Show Affiliations

Genetic and Molecular Epidemiology Group, Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics & Cardiogenetics, University of Lübeck, Lübeck, Germany.Ageing Epidemiology Research Unit, School of Public Health, Imperial College, London, United Kingdom.Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), Institutes of Neurogenetics & Cardiogenetics, University of Lübeck, Lübeck, Germany.Ageing Epidemiology Research Unit, School of Public Health, Imperial College, London, United Kingdom.Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), Institutes of Neurogenetics & Cardiogenetics, University of Lübeck, Lübeck, Germany.Institute for Medical Biometry and Statistics, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany.Institute for Medical Biometry and Statistics, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany.Ageing Epidemiology Research Unit, School of Public Health, Imperial College, London, United Kingdom.Departments of Medicine, Health Research and Policy, Biomedical Data Science, and Statistics, and Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, California, CA.Ageing Epidemiology Research Unit, School of Public Health, Imperial College, London, United Kingdom. Department of Psychiatry and Psychotherapy, Ludwig-Maximilians-Universität München, Munich, Germany. German Center for Neurodegenerative Diseases (DZNE) Munich, Munich, Germany. West London Mental Health NHS Trust, London, United Kingdom.Ageing Epidemiology Research Unit, School of Public Health, Imperial College, London, United Kingdom. Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), Institutes of Neurogenetics & Cardiogenetics, University of Lübeck, Lübeck, Germany.Genetic and Molecular Epidemiology Group, Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics & Cardiogenetics, University of Lübeck, Lübeck, Germany. Ageing Epidemiology Research Unit, School of Public Health, Imperial College, London, United Kingdom.

Pub Type(s)

Journal Article
Meta-Analysis
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

30990912

Citation

Schulz, Jessica, et al. "Meta-analyses Identify Differentially Expressed Micrornas in Parkinson's Disease." Annals of Neurology, vol. 85, no. 6, 2019, pp. 835-851.
Schulz J, Takousis P, Wohlers I, et al. Meta-analyses identify differentially expressed micrornas in Parkinson's disease. Ann Neurol. 2019;85(6):835-851.
Schulz, J., Takousis, P., Wohlers, I., Itua, I. O. G., Dobricic, V., Rücker, G., Binder, H., Middleton, L., Ioannidis, J. P. A., Perneczky, R., Bertram, L., & Lill, C. M. (2019). Meta-analyses identify differentially expressed micrornas in Parkinson's disease. Annals of Neurology, 85(6), 835-851. https://doi.org/10.1002/ana.25490
Schulz J, et al. Meta-analyses Identify Differentially Expressed Micrornas in Parkinson's Disease. Ann Neurol. 2019;85(6):835-851. PubMed PMID: 30990912.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Meta-analyses identify differentially expressed micrornas in Parkinson's disease. AU - Schulz,Jessica, AU - Takousis,Petros, AU - Wohlers,Inken, AU - Itua,Ivie O G, AU - Dobricic,Valerija, AU - Rücker,Gerta, AU - Binder,Harald, AU - Middleton,Lefkos, AU - Ioannidis,John P A, AU - Perneczky,Robert, AU - Bertram,Lars, AU - Lill,Christina M, PY - 2018/02/17/received PY - 2019/04/14/revised PY - 2019/04/15/accepted PY - 2019/4/17/pubmed PY - 2020/3/31/medline PY - 2019/4/17/entrez SP - 835 EP - 851 JF - Annals of neurology JO - Ann Neurol VL - 85 IS - 6 N2 - OBJECTIVE: MicroRNA (miRNA)-mediated (dys)regulation of gene expression has been implicated in Parkinson's disease (PD), although results of miRNA expression studies remain inconclusive. We aimed to identify miRNAs that show consistent differential expression across all published expression studies in PD. METHODS: We performed a systematic literature search on miRNA expression studies in PD and extracted data from eligible publications. After stratification for brain, blood, and cerebrospinal fluid (CSF)-derived specimen, we performed meta-analyses across miRNAs assessed in three or more independent data sets. Meta-analyses were performed using effect-size- and p-value-based methods, as applicable. RESULTS: After screening 599 publications, we identified 47 data sets eligible for meta-analysis. On these, we performed 160 meta-analyses on miRNAs quantified in brain (n = 125), blood (n = 31), or CSF (n = 4). Twenty-one meta-analyses were performed using effect sizes. We identified 13 significantly (Bonferroni-adjusted α = 3.13 × 10-4) differentially expressed miRNAs in brain (n = 3) and blood (n = 10) with consistent effect directions across studies. The most compelling findings were with hsa-miR-132-3p (p = 6.37 × 10-5), hsa-miR-497-5p (p = 1.35 × 10-4), and hsa-miR-133b (p = 1.90 × 10-4) in brain and with hsa-miR-221-3p (p = 4.49 × 10-35), hsa-miR-214-3p (p = 2.00 × 10-34), and hsa-miR-29c-3p (p = 3.00 × 10-12) in blood. No significant signals were found in CSF. Analyses of genome-wide association study data for target genes of brain miRNAs showed significant association (α = 9.40 × 10-5) of genetic variants in nine loci. INTERPRETATION: We identified several miRNAs that showed highly significant differential expression in PD. Future studies may assess the possible role of the identified brain miRNAs in pathogenesis and disease progression as well as the potential of the top blood miRNAs as biomarkers for diagnosis, progression, or prediction of PD. ANN NEUROL 2019;85:835-851. SN - 1531-8249 UR - https://www.unboundmedicine.com/medline/citation/30990912/Meta_analyses_identify_differentially_expressed_micrornas_in_Parkinson's_disease_ DB - PRIME DP - Unbound Medicine ER -