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A Customized Quantitative PCR MicroRNA Panel Provides a Technically Robust Context for Studying Neurodegenerative Disease Biomarkers and Indicates a High Correlation Between Cerebrospinal Fluid and Choroid Plexus MicroRNA Expression

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Abstract

MicroRNA (miRNA) expression varies in association with different tissue types and in diseases. Having been found in body fluids including blood and cerebrospinal fluid (CSF), miRNAs constitute potential biomarkers. CSF miRNAs have been proposed as biomarkers for neurodegenerative diseases; however, there is a lack of consensus about the best candidate miRNA biomarkers and there has been variability in results from different research centers, perhaps due to technical factors. Here, we sought to optimize technical parameters for CSF miRNA studies. We examined different RNA isolation methods and performed miRNA expression profiling with TaqMan® miRNA Arrays. More specifically, we developed a customized CSF-miRNA low-density array (TLDA) panel that contains 47 targets: miRNAs shown previously to be relevant to neurodegenerative disease, miRNAs that are abundant in CSF, data normalizers, and controls for potential blood and tissue contamination. The advantages of using this CSF-miRNA TLDA panel include specificity, sensitivity, fast processing and data analysis, and cost effectiveness. We optimized technical parameters for this assay. Further, the TLDA panel can be tailored to other specific purposes. We tested whether the profile of miRNAs in the CSF resembled miRNAs isolated from brain tissue (hippocampus or cerebellum), blood, or the choroid plexus. We found that the CSF miRNA expression profile most closely resembles that of choroid plexus tissue, underscoring the potential importance of choroid plexus-derived signaling through CSF miRNAs. In summary, the TLDA miRNA array panel will enable evaluation and discovery of CSF miRNA biomarkers and can potentially be utilized in clinical diagnosis and disease stage monitoring.

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References

  1. Lukiw WJ (2007) Micro-RNA speciation in fetal, adult and Alzheimer’s disease hippocampus. Neuroreport 18:297–300. doi:10.1097/WNR.0b013e3280148e8b

    Article  CAS  PubMed  Google Scholar 

  2. Hebert SS, Horre K, Nicolai L, Papadopoulou AS, Mandemakers W, Silahtaroglu AN, Kauppinen S, Delacourte A et al (2008) Loss of microRNA cluster miR-29a/b-1 in sporadic Alzheimer’s disease correlates with increased BACE1/beta-secretase expression. Proc Natl Acad Sci U S A 105:6415–6420. doi:10.1073/pnas.0710263105

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Wang WX, Rajeev BW, Stromberg AJ, Ren N, Tang G, Huang Q, Rigoutsos I, Nelson PT (2008) The expression of microRNA miR-107 decreases early in Alzheimer’s disease and may accelerate disease progression through regulation of beta-site amyloid precursor protein-cleaving enzyme 1. J Neurosci 28:1213–1223. doi:10.1523/JNEUROSCI.5065-07.2008

    Article  PubMed  PubMed Central  Google Scholar 

  4. Nelson PT, Wang WX, Rajeev BW (2008) MicroRNAs (miRNAs) in neurodegenerative diseases. Brain Pathol 18:130–138. doi:10.1111/j.1750-3639.2007.00120.x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Weber JA, Baxter DH, Zhang S, Huang DY, Huang KH, Lee MJ, Galas DJ, Wang K (2010) The microRNA spectrum in 12 body fluids. Clin Chem 56:1733–1741. doi:10.1373/clinchem.2010.147405

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Mraz M, Malinova K, Mayer J, Pospisilova S (2009) MicroRNA isolation and stability in stored RNA samples. Biochem Biophys Res Commun 390:1–4. doi:10.1016/j.bbrc.2009.09.061

    Article  CAS  PubMed  Google Scholar 

  7. Etheridge A, Lee I, Hood L, Galas D, Wang K (2011) Extracellular microRNA: a new source of biomarkers. Mutat Res 717:85–90. doi:10.1016/j.mrfmmm.2011.03.004

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Hebert SS, Nelson PT (2012) Studying microRNAs in the brain: technical lessons learned from the first ten years. Exp Neurol 235:397–401. doi:10.1016/j.expneurol.2011.12.004

    Article  CAS  PubMed  Google Scholar 

  9. Nelson PT, Wang WX, Wilfred BR, Tang G (2008) Technical variables in high-throughput miRNA expression profiling: much work remains to be done. Biochim Biophys Acta 1779:758–765. doi:10.1016/j.bbagrm.2008.03.012

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Moldovan L, Batte KE, Trgovcich J, Wisler J, Marsh CB, Piper M (2014) Methodological challenges in utilizing miRNAs as circulating biomarkers. J Cell Mol Med 18:371–390. doi:10.1111/jcmm.12236

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Duttagupta R, Jiang R, Gollub J, Getts RC, Jones KW (2011) Impact of cellular miRNAs on circulating miRNA biomarker signatures. PLoS One 6:e20769. doi:10.1371/journal.pone.0020769

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Fourier A, Portelius E, Zetterberg H, Blennow K, Quadrio I, Perret-Liaudet A (2015) Pre-analytical and analytical factors influencing Alzheimer’s disease cerebrospinal fluid biomarker variability. Clin Chim Acta 449:9–15. doi:10.1016/j.cca.2015.05.024

    Article  CAS  PubMed  Google Scholar 

  13. Burgos KL, Javaherian A, Bomprezzi R, Ghaffari L, Rhodes S, Courtright A, Tembe W, Kim S et al (2013) Identification of extracellular miRNA in human cerebrospinal fluid by next-generation sequencing. RNA 19:712–722. doi:10.1261/rna.036863.112

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Bekris LM, Lutz F, Montine TJ, Yu CE, Tsuang D, Peskind ER, Leverenz JB (2013) MicroRNA in Alzheimer’s disease: an exploratory study in brain, cerebrospinal fluid and plasma. Biomarkers 18:455–466. doi:10.3109/1354750X.2013.814073

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Baraniskin A, Kuhnhenn J, Schlegel U, Chan A, Deckert M, Gold R, Maghnouj A, Zollner H et al (2011) Identification of microRNAs in the cerebrospinal fluid as marker for primary diffuse large B-cell lymphoma of the central nervous system. Blood 117:3140–3146. doi:10.1182/blood-2010-09-308684

    Article  CAS  PubMed  Google Scholar 

  16. Muller M, Kuiperij HB, Claassen JA, Kusters B, Verbeek MM (2014) MicroRNAs in Alzheimer’s disease: differential expression in hippocampus and cell-free cerebrospinal fluid. Neurobiol Aging 35:152–158. doi:10.1016/j.neurobiolaging.2013.07.005

    Article  CAS  PubMed  Google Scholar 

  17. Haghikia A, Haghikia A, Hellwig K, Baraniskin A, Holzmann A, Decard BF, Thum T, Gold R (2012) Regulated microRNAs in the CSF of patients with multiple sclerosis: a case-control study. Neurology 79:2166–2170. doi:10.1212/WNL.0b013e3182759621

    Article  CAS  PubMed  Google Scholar 

  18. Cogswell JP, Ward J, Taylor IA, Waters M, Shi Y, Cannon B, Kelnar K, Kemppainen J et al (2008) Identification of miRNA changes in Alzheimer’s disease brain and CSF yields putative biomarkers and insights into disease pathways. J Alzheimers Dis 14:27–41

    Article  CAS  PubMed  Google Scholar 

  19. Denk J, Boelmans K, Siegismund C, Lassner D, Arlt S, Jahn H (2015) MicroRNA profiling of CSF reveals potential biomarkers to detect Alzheimer’s disease. PLoS One 10:e0126423. doi:10.1371/journal.pone.0126423

    Article  PubMed  PubMed Central  Google Scholar 

  20. Nelson PT, Jicha GA, Schmitt FA, Liu H, Davis DG, Mendiondo MS, Abner EL, Markesbery WR (2007) Clinicopathologic correlations in a large Alzheimer disease center autopsy cohort: neuritic plaques and neurofibrillary tangles “do count” when staging disease severity. J Neuropathol Exp Neurol 66:1136–1146. doi:10.1097/nen.0b013e31815c5efb

    Article  PubMed  PubMed Central  Google Scholar 

  21. Schmitt FA, Nelson PT, Abner E, Scheff S, Jicha GA, Smith C, Cooper G, Mendiondo M et al (2012) University of Kentucky Sanders-Brown healthy brain aging volunteers: donor characteristics, procedures and neuropathology. Curr Alzheimer Res 9:724–733

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Wang WX, Wilfred BR, Baldwin DA, Isett RB, Ren N, Stromberg A, Nelson PT (2008) Focus on RNA isolation: obtaining RNA for microRNA (miRNA) expression profiling analyses of neural tissue. Biochim Biophys Acta 1779:749–757. doi:10.1016/j.bbagrm.2008.01.005

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Wang WX, Wilfred BR, Madathil SK, Tang G, Hu Y, Dimayuga J, Stromberg AJ, Huang Q et al (2010) miR-107 regulates granulin/progranulin with implications for traumatic brain injury and neurodegenerative disease. Am J Pathol 177:334–345. doi:10.2353/ajpath.2010.091202

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Wang WX, Danaher RJ, Miller CS, Berger JR, Nubia VG, Wilfred BS, Neltner JH, Norris CM et al (2014) Expression of miR-15/107 family microRNAs in human tissues and cultured rat brain cells. Genomics Proteomics Bioinformatics 12:19–30. doi:10.1016/j.gpb.2013.10.003

    Article  PubMed  PubMed Central  Google Scholar 

  25. Bustin SA, Benes V, Garson JA, Hellemans J, Huggett J, Kubista M, Mueller R, Nolan T et al (2009) The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments. Clin Chem 55:611–622. doi:10.1373/clinchem.2008.112797

    Article  CAS  PubMed  Google Scholar 

  26. Mestdagh P, Van Vlierberghe P, De Weer A, Muth D, Westermann F, Speleman F, Vandesompele J (2009) A novel and universal method for microRNA RT-qPCR data normalization. Genome Biol 10:R64. doi:10.1186/gb-2009-10-6-r64

    Article  PubMed  PubMed Central  Google Scholar 

  27. Zou GY (2007) Toward using confidence intervals to compare correlations. Psychol Methods 12:399–413. doi:10.1037/1082-989X.12.4.399

    Article  PubMed  Google Scholar 

  28. Mestdagh P, Feys T, Bernard N, Guenther S, Chen C, Speleman F, Vandesompele J (2008) High-throughput stem-loop RT-qPCR miRNA expression profiling using minute amounts of input RNA. Nucleic Acids Res 36:e143. doi:10.1093/nar/gkn725

    Article  PubMed  PubMed Central  Google Scholar 

  29. Nelson PT, Baldwin DA, Scearce LM, Oberholtzer JC, Tobias JW, Mourelatos Z (2004) Microarray-based, high-throughput gene expression profiling of microRNAs. Nat Methods 1:155–161. doi:10.1038/nmeth717

    Article  CAS  PubMed  Google Scholar 

  30. Mestdagh P, Hartmann N, Baeriswyl L, Andreasen D, Bernard N, Chen C, Cheo D, D’Andrade P et al (2014) Evaluation of quantitative miRNA expression platforms in the microRNA quality control (miRQC) study. Nat Methods 11:809–815. doi:10.1038/nmeth.3014

    Article  CAS  PubMed  Google Scholar 

  31. Chugh P, Dittmer DP (2012) Potential pitfalls in microRNA profiling. Wiley Interdiscip Rev RNA 3:601–616. doi:10.1002/wrna.1120

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

Sincere thanks to the research subjects, clinicians, and staff at the UK-ADC. Funding was provided through NIH grants P30 AG028383, R01 AG 042419, and R21 NS085830.

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Correspondence to Wang-Xia Wang or Peter T. Nelson.

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Wang, WX., Fardo, D.W., Jicha, G.A. et al. A Customized Quantitative PCR MicroRNA Panel Provides a Technically Robust Context for Studying Neurodegenerative Disease Biomarkers and Indicates a High Correlation Between Cerebrospinal Fluid and Choroid Plexus MicroRNA Expression. Mol Neurobiol 54, 8191–8202 (2017). https://doi.org/10.1007/s12035-016-0316-2

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  • DOI: https://doi.org/10.1007/s12035-016-0316-2

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