Dobricic, V. | bioRxiv Science

bioRxiv2018

Field synopsis and systematic meta-analyses of genetic association studies in isolated dystonia

Background and objectivesDystonia is a genetically complex disease with both monogenic and polygenic causes. For the latter, numerous genetic associations studies have been performed with largely inconsistent results. The aim of this study was to perform a field synopsis including systematic meta-analyses of genetic association studies in isolated dystonia\n\nMethodsFor the field synopsis we systematically screened and scrutinized the published literature using NCBIs PubMed database. For genetic variants with sufficient information in at least two independent datasets, random-effects meta-analyses were performed, including meta-analyses stratified by ethnic descent and dystonia subtypes.\n\nResultsA total of 3,575 articles were identified and scrutinized resulting in the inclusion of 42 independent publications allowing 134 meta-analyses on 45 variants across 17 genes. While our meta-analyses pinpointed several significant association signals with variants in TOR1A, DRD1, and ARSG, no single variant displayed compelling association with dystonia in the available data.\n\nConclusionsOur study provides an up-to-date summary of the status of dystonia genetic association studies. Additional large-scale studies are needed to better understand the genetic causes of isolated dystonia.

neuroscience↗

bioRxiv2018

Systematic meta-analyses identify differentially expressed microRNAs in Parkinson’s disease

ObjectiveMicroRNA-mediated (dys)regulation of gene expression has been implicated in Parkinsons disease (PD), although results of microRNA expression studies remain inconclusive. We aimed to identify microRNAs that show consistent differential expression across all published expression studies in PD.\n\nMethodsWe performed a systematic literature search on microRNA 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 microRNAs assessed in three or more independent datasets. Meta-analyses were performed using effect-size and p-value based methods, as applicable.\n\nResultsAfter screening 599 publications we identified 47 datasets eligible for meta-analysis. On these, we performed 160 meta-analyses on microRNAs quantified in brain (n=125), blood (n=31), or CSF samples (n=4). Twenty-one meta-analyses were performed using effect sizes. We identified 13 significantly (Bonferroni-adjusted =3.13x10-4) differentially expressed microRNAs 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=6.37x10-5), hsa-miR-497-5p (p=1.35x10-4), and hsa-miR-133b (p=1.90x10-4) in brain, and with hsa-miR-221-3p (p=4.49x10-35), hsa-miR-214-3p (p=2.00x10-34), and hsa-miR-29c-3p (p=3.00x10-12) in blood. No significant signals were found in CSF. Analyses of GWAS data for target genes of brain microRNAs showed significant association (=9.40x10-5) of genetic variants in nine loci.\n\nInterpretationWe identified several microRNAs 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 microRNAs as biomarkers for diagnosis, progression or prediction of PD.

genetics↗