Cited by 22

The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

Common signatures of differential microRNA expression in Parkinson’s and Alzheimer’s disease brains

Dobricic, Valerija, Schilling, Marcel, Farkas, Ildiko, Gveric, Djordje O, Ohlei, Olena, Schulz, Jessica, Middleton, Lefkos, Gentleman, Steve M, Parkkinen, Laura, Bertram, Lars, Lill, Christina M·2022·Brain Communications

Published version of a preprint

Abstract

Dysregulation of microRNA gene expression has been implicated in many neurodegenerative diseases, including Parkinson’s disease. However, the individual dysregulated microRNAs remain largely unknown. Previous meta-analyses have highlighted several microRNAs being differentially expressed in post-mortem Parkinson’s disease and Alzheimer's disease brains versus controls, but they were based on small sample sizes. In this study, we quantified the expression of the most compelling Parkinson’s and Alzheimer’s disease microRNAs from these meta-analyses (‘candidate miRNAs’) in one of the largest Parkinson’s/Alzheimer’s disease case–control post-mortem brain collections available (n = 451), thereby quadruplicating previously investigated sample sizes. Parkinson’s disease candidate microRNA hsa-miR-132-3p was differentially expressed in our Parkinson’s (P = 4.89E−06) and Alzheimer’s disease samples (P = 3.20E−24) compared with controls. Alzheimer’s disease candidate microRNAs hsa-miR-132-5p (P = 4.52E−06) and hsa-miR-129-5p (P = 0.0379) were differentially expressed in our Parkinson’s disease samples. Combining these novel data with previously published data substantially improved the statistical support (α = 3.85E−03) of the corresponding meta-analyses, clearly implicating these microRNAs in both Parkinson’s and Alzheimer’s disease. Furthermore, hsa-miR-132-3p/-5p (but not hsa-miR-129-5p) showed association with α-synuclein neuropathological Braak staging (P = 3.51E−03/P = 0.0117), suggesting that hsa-miR-132-3p/-5p play a role in α-synuclein aggregation beyond the early disease phase. Our study represents the largest independent assessment of recently highlighted candidate microRNAs in Parkinson’s and Alzheimer’s disease brains, to date. Our results implicate hsa-miR-132-3p/-5p and hsa-miR-129-5p to be differentially expressed in both Parkinson’s and Alzheimer’s disease, pinpointing shared pathogenic mechanisms across these neurodegenerative diseases. Intriguingly, based on publicly available high-throughput sequencing of RNA isolated by cross-linking immunoprecipitation data, hsa-miR-132 may interact with SNCA messenger RNA in the human brain, possibly pinpointing novel therapeutic approaches in fighting Parkinson’s disease.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1093/braincomms/fcac274

Cites

5 of 5 references verified0 citation errors · 0 not checkable

Statistics

Figures

Graphical Abstract
Graphical Abstract CC BY · PubMed Central
Figure 1 Overview of the study design. PD, Parkinson’s disease; AD, Alzheimer’s disease.
Figure 1 Overview of the study design. PD, Parkinson’s disease; AD, Alzheimer’s disease.CC BY · PubMed Central
Figure 2 Expression of candidate miRNAs in brain samples of Parkinson’s disease and Alzheimer’s disease patients versus controls and dependent on the neuropathological α-synuclein and tau Braak staging. This box and whisker plots display the relative quantity of Parkinson’s disease candidate miRNAs in post-mortem brain samples of the STG of 214 Parkinson’s disease patients versus 47 controls (A), the relative quantity of Parkinson’s disease candidate miRNAs in post-mortem brain samples of 99 Alzheimer’s disease patients versus 91 controls (B), and the relative quantity of Alzheimer’s disease candidate miRNAs in post-mortem brain samples of the STG of 214 Parkinson’s disease patients versus 47 controls (C). Differential gene expression was analysed using a GLM adjusting for RIN, age at death, PMIs and sex. The relative quantity of miRNA expression was calculated using the ΔΔCt method; diamonds represent the mean expression (cases relative to controls) based on the ΔΔCt method (relativequantity=2^(−(dCtcases–dCtcontrols))). Horizontal lines represent median values of the corresponding sample-specific values (individual dCt values normalized to the mean of the control samples), boxes represent IQRs and whiskers extend to the maximum observed value within 1.5 × the IQR; values outside this range but below the dashed line are depicted as dots. Outliers exceeding the dashed line are not shown (for scaling purposes) but counted and indicated by the numbers in the triangles. The box notches indicate the corresponding 95% confidence intervals (CIs). *Nominally statistically significant difference (α = 0.05). (D) This plot displays the gene expression of hsa-miR-132-3p and hsa-miR-132-5p normalized to endogenous control assay (dCt) dependent on α-synuclein and tau Braak staging in post-mortem brain samples of 213 Parkinson’s disease patients utilizing a GLM adjusting for RIN, age at death, PMIs and sex. Horizontal lines indicate the mean of the group.
Figure 2 Expression of candidate miRNAs in brain samples of Parkinson’s disease and Alzheimer’s disease patients versus controls and dependent on the neuropathological α-synuclein and tau Braak staging. This box and whisker plots display the relative quantity of Parkinson’s disease candidate miRNAs in post-mortem brain samples of the STG of 214 Parkinson’s disease patients versus 47 controls (A), the relative quantity of Parkinson’s disease candidate miRNAs in post-mortem brain samples of 99 Alzheimer’s disease patients versus 91 controls (B), and the relative quantity of Alzheimer’s disease candidate miRNAs in post-mortem brain samples of the STG of 214 Parkinson’s disease patients versus 47 controls (C). Differential gene expression was analysed using a GLM adjusting for RIN, age at death, PMIs and sex. The relative quantity of miRNA expression was calculated using the ΔΔCt method; diamonds represent the mean expression (cases relative to controls) based on the ΔΔCt method (relativequantity=2^(−(dCtcases–dCtcontrols))). Horizontal lines represent median values of the corresponding sample-specific values (individual dCt values normalized to the mean of the control samples), boxes represent IQRs and whiskers extend to the maximum observed value within 1.5 × the IQR; values outside this range but below the dashed line are depicted as dots. Outliers exceeding the dashed line are not shown (for scaling purposes) but counted and indicated by the numbers in the triangles. The box notches indicate the corresponding 95% confidence intervals (CIs). *Nominally statistically significant difference (α = 0.05). (D) This plot displays the gene expression of hsa-miR-132-3p and hsa-miR-132-5p normalized to endogenous control assay (dCt) dependent on α-synuclein and tau Braak staging in post-mortem brain samples of 213 Parkinson’s disease patients utilizing a GLM adjusting for RIN, age at death, PMIs and sex. Horizontal lines indicate the mean of the group.CC BY · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Research works printed but not linked: 26

  1. de Lau, 2006, Epidemiology of Parkinson’s disease, Lancet Neurol, 5, 525, 10.1016/S1474-4422(06)70471-9 · DOI · Paper page
  2. Lill, 2016, Genetics of Parkinson’s disease, Mol Cell Probes, 30, 386, 10.1016/j.mcp.2016.11.001 · DOI
  3. Nalls, 2019, Identification of novel risk loci, causal insights, and heritable risk for Parkinson’s disease: A meta-analysis of genome-wide association studies, Lancet Neurol, 18, 1091, 10.1016/S1474-4422(19)30320-5 · DOI · Paper page
  4. Noyce, 2012, Meta-analysis of early nonmotor features and risk factors for Parkinson disease, Ann Neurol, 72, 893, 10.1002/ana.23687 · DOI
  5. Labbe, 2016, Epigenetic regulation in Parkinson ‘s disease, Acta Neuropathol, 132, 515, 10.1007/s00401-016-1590-9 · DOI
  6. Bartel, 2018, Metazoan microRNAs, Cell, 173, 20, 10.1016/j.cell.2018.03.006 · DOI · Paper page
  7. Kuo, 2021, The role of noncoding RNAs in Parkinson’s disease: Biomarkers and associations with pathogenic pathways, J Biomed Sci, 28, 78, 10.1186/s12929-021-00775-x · DOI
  8. Evans, 2021, Parkinson’s disease and microRNAs—Lessons from model organisms and human studies, Exp Gerontol, 155, 111585, 10.1016/j.exger.2021.111585 · DOI
  9. Schulz, 2019, Meta-analyses identify differentially expressed microRNAs in Parkinson’s disease, Ann Neurol, 85, 835, 10.1002/ana.25490 · DOI
  10. Takousis, 2019, Differential expression of microRNAs in Alzheimer’s disease brain, blood, and cerebrospinal fluid, Alzheimers Dement, 15, 1468, 10.1016/j.jalz.2019.06.4952 · DOI · Paper page
  11. Dobricic, 2022, Differential microRNA expression analyses across two brain regions in Alzheimer’s disease, Transl Psychiatry, 12, 352, 10.1038/s41398-022-02108-4 · DOI · Paper page
  12. Guimarães, 2017, Pattern of reduced functional connectivity and structural abnormalities in Parkinson’s disease: An exploratory study, Front Neurol, 7, 1
  13. Haroutunian, 2009, Transcriptional vulnerability of brain regions in Alzheimer’s disease and dementia, Neurobiol Aging, 30, 561, 10.1016/j.neurobiolaging.2007.07.021 · DOI
  14. Alafuzoff, 2009, Staging/typing of Lewy body related alpha-synuclein pathology: A study of the BrainNet Europe Consortium, Acta Neuropathol, 117, 635, 10.1007/s00401-009-0523-2 · DOI
  15. Roth, 1986, CAMDEX. A standardised instrument for the diagnosis of mental disorder in the elderly with special reference to the early detection of dementia, Br J Psychiatry, 149, 698, 10.1192/bjp.149.6.698 · DOI · Paper page
  16. Mirra, 1991, The Consortium to Establish a Registry for Alzheimer’s Disease (CERAD). Part II. Standardization of the neuropathologic assessment of Alzheimer’s disease, Neurology, 41, 479, 10.1212/WNL.41.4.479 · DOI · Paper page
  17. Hyman, 2012, National Institute on Aging-Alzheimer’s Association guidelines for the neuropathologic assessment of Alzheimer’s disease, Alzheimers Dement, 8, 1, 10.1016/j.jalz.2011.10.007 · DOI · Paper page
  18. Bellenguez, 2022, New insights into the genetic etiology of Alzheimer’s disease and related dementias, Nat Genet, 54, 412, 10.1038/s41588-022-01024-z · DOI · Paper page
  19. Xing, 2020, Down regulation of miR-218, miR-124, and miR-144 relates to Parkinson’s disease via activating NF-κB signaling, Kaohsiung J Med Sci, 36, 786, 10.1002/kjm2.12241 · DOI
  20. Schulze, 2018, Sporadic Parkinson’s disease derived neuronal cells show disease-specific mRNA and small RNA signatures with abundant deregulation of piRNAs, Acta Neuropathol Commun, 6, 58, 10.1186/s40478-018-0561-x · DOI
  21. Wanet, 2012, MiR-212/132 expression and functions: Within and beyond the neuronal compartment, Nucleic Acids Res, 40, 4742, 10.1093/nar/gks151 · DOI
  22. Gillardon, 2008, MicroRNA and proteome expression profiling in early-symptomatic α-synuclein(A30P)-transgenic mice, Proteomics Clin Appl, 2, 697, 10.1002/prca.200780025 · DOI
  23. Hernandez-Rapp, 2015, Memory formation and retention are affected in adult miR-132/212 knockout mice, Behav Brain Res, 287, 15, 10.1016/j.bbr.2015.03.032 · DOI · Paper page
  24. Hernandez-Rapp, 2016, MicroRNA-132/212 deficiency enhances Aβ production and senile plaque deposition in Alzheimer’s disease triple transgenic mice, Sci Rep, 6, 30953, 10.1038/srep30953 · DOI
  25. El Fatimy, 2018, MicroRNA-132 provides neuroprotection for tauopathies via multiple signaling pathways, Acta Neuropathol, 136, 537, 10.1007/s00401-018-1880-5 · DOI · Paper page
  26. Zeng, 2019, MicroRNA-129-5p alleviates nerve injury and inflammatory response of Alzheimer’s disease via downregulating SOX6, Cell Cycle, 18, 3095, 10.1080/15384101.2019.1669388 · DOI

Cited by

Sorted by citations

See all 22

Metadata

Authors
Dobricic, V., Schilling, M., Farkas, I., Gveric, D. O., Ohlei, O., Schulz, J., Middleton, L., Gentleman, S. M., Parkkinen, L., Bertram, L., & Lill, C. M.
Affiliations
  • Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck , 23562 Lübeck , Germany
  • Multiple Sclerosis and Parkinson’s Tissue Bank, Imperial College London , London W12 0NN , UK
  • Ageing and Epidemiology Unit (AGE), School of Public Health, Imperial College London , London W6 8RF , UK
  • Department of Brain Sciences, Hammersmith Hospital campus, Imperial College London , London W12 0HS , UK
  • Nuffield Department of Clinical Neurosciences, Oxford Parkinson’s Disease Centre, University of Oxford , Oxford OX3 9DU , UK
Venue
Brain Communications
Published
2022-10-28
Volume
4
Issue
6
ISSN
2632-1297
Cited by
22
References
5
Language
en
Funders
  • Deutsche Forschungsgemeinschaft (#391523883)
  • Cure Alzheimer’s Fund
  • Brain Bank
  • Imperial College London
  • Parkinson’s UK (258197, SC037554)
  • The Oxford Brain Bank
  • Medical Research Council
  • Brains for Dementia Research
  • Alzheimer Society and Alzheimer Research UK
  • NIHR Oxford Biomedical Research Centre
  • Michael J. Fox Foundation

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review