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Ann Neurol. 2019 Jun;85(6):835-851. doi: 10.1002/ana.25490.

Meta-analyses identify differentially expressed micrornas in Parkinson's disease.

Author information

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.
Institute for Medical Biometry and Statistics, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany.
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.
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.



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.


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.


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.


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.


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