Attention-deficit/hyperactivity disorder (ADHD) is one of the most prevalent neurodevelopmental disorders in childhood and persists into adulthood in 40–65% of cases. Given the polygenic and heterogeneous architecture of the disorder and the limited overlap between genetic studies, there is a growing interest in epigenetic mechanisms, such as microRNAs, that modulate gene expression and may contribute to the phenotype. We attempted to clarify the role of microRNAs in ADHD at a molecular level through the first genome-wide integrative study of microRNA and mRNA profiles in peripheral blood mononuclear cells of medication-naive individuals with ADHD and healthy controls. We identified 79 microRNAs showing aberrant expression levels in 56 ADHD cases and 69 controls, with three of them, miR-26b-5p, miR-185-5p, and miR-191-5p, being highly predictive for diagnostic status in an independent dataset of 44 ADHD cases and 46 controls. Investigation of downstream microRNA-mediated mechanisms underlying the disorder, which was focused on differentially expressed, experimentally validated target genes of the three highly predictive microRNAs, provided evidence for aberrant myo-inositol signaling in ADHD and indicated an enrichment of genes involved in neurological disease and psychological disorders. Our comprehensive study design reveals novel microRNA–mRNA expression profiles aberrant in ADHD, provides novel insights into microRNA-mediated mechanisms contributing to the disorder, and highlights promising candidate peripheral biomarkers.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


  1. 1.

    Polanczyk GV, Willcutt EG, Salum GA, Kieling C, Rohde LA. ADHD prevalence estimates across three decades: an updated systematic review and meta-regression analysis. Int J Epidemiol. 2014;43:434–42.

  2. 2.

    Simon V, Czobor P, Balint S, Meszaros A, Bitter I. Prevalence and correlates of adult attention-deficit hyperactivity disorder: meta-analysis. Br J Psychiatry. 2009;194:204–11.

  3. 3.

    Faraone SV, Larsson H. Genetics of attention deficit hyperactivity disorder. Mol Psychiatry. 2018 Jun 11. https://doi.org/10.1038/s41380-018-0070-0. [Epub ahead of print].

  4. 4.

    Bonvicini C, Faraone SV, Scassellati C. Attention-deficit hyperactivity disorder in adults: a systematic review and meta-analysis of genetic, pharmacogenetic and biochemical studies. Mol Psychiatry. 2016;21:872–84.

  5. 5.

    Alural B, Genc S, Haggarty SJ. Diagnostic and therapeutic potential of microRNAs in neuropsychiatric disorders: past, present, and future. Prog Neuropsychopharmacol Biol Psychiatry. 2017;73:87–103.

  6. 6.

    Nowak JS, Michlewski G. miRNAs in development and pathogenesis of the nervous system. Biochem Soc Trans. 2013;41:815–20.

  7. 7.

    Cipolla GA. A non-canonical landscape of the microRNA system. Front Genet. 2014;5:337.

  8. 8.

    Lewis BP, Shih IH, Jones-Rhoades MW, Bartel DP, Burge CB. Prediction of mammalian microRNA targets. Cell. 2003;115:787–98.

  9. 9.

    Anitha A, Thanseem I. microRNA and autism. Adv Exp Med Biol. 2015;888:71–83.

  10. 10.

    Garcia-Martinez I, Sanchez-Mora C, Pagerols M, Richarte V, Corrales M, Fadeuilhe C, et al. Preliminary evidence for association of genetic variants in pri-miR-34b/c and abnormal miR-34c expression with attention deficit and hyperactivity disorder. Transl Psychiatry. 2016;6:e879.

  11. 11.

    Ma J, Shang S, Wang J, Zhang T, Nie F, Song X, et al. Identification of miR-22-3p, miR-92a-3p, and miR-137 in peripheral blood as biomarker for schizophrenia. Psychiatry Res. 2018;265:70–6.

  12. 12.

    Maffioletti E, Tardito D, Gennarelli M, Bocchio-Chiavetto L. Micro spies from the brain to the periphery: new clues from studies on microRNAs in neuropsychiatric disorders. Front Cell Neurosci. 2015;8:75.

  13. 13.

    Qi T, Wu Y, Zeng J, Zhang F, Xue A, Jiang L, et al. Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood. Nat Commun. 2018;9:2282.

  14. 14.

    Chatterjee P, Roy D. Comparative analysis of RNA-Seq data from brain and blood samples of Parkinson’s disease. Biochem Biophys Res Commun. 2017;484:557–64.

  15. 15.

    Srivastav S, Walitza S, Grunblatt E. Emerging role of miRNA in attention deficit hyperactivity disorder: a systematic review. Atten Defic Hyperact Disord. 2018;10:49–63.

  16. 16.

    Kandemir H, Erdal ME, Selek S, Ay OI, Karababa IF, Kandemir SB, et al. Evaluation of several micro RNA (miRNA) levels in children and adolescents with attention deficit hyperactivity disorder. Neurosci Lett. 2014;580:158–62.

  17. 17.

    Wu LH, Peng M, Yu M, Zhao QL, Li C, Jin YT, et al. Circulating microRNA let-7d in attention-deficit/hyperactivity disorder. Neuromolecular Med. 2015;17:137–46.

  18. 18.

    Wu L, Zhao Q, Zhu X, Peng M, Jia C, Wu W, et al. A novel function of microRNA let-7d in regulation of galectin-3 expression in attention deficit hyperactivity disorder rat brain. Brain Pathol. 2010;20:1042–54.

  19. 19.

    Karakas U, Ay OI, Ay ME, Wang W, Sungur MA, Cevik K, et al. Regulating the regulators in attention-deficit/hyperactivity disorder: a genetic association study of microRNA biogenesis pathways. Omics. 2017;21:352–8.

  20. 20.

    Nemeth N, Kovacs-Nagy R, Szekely A, Sasvari-Szekely M, Ronai Z. Association of impulsivity and polymorphic microRNA-641 target sites in the SNAP-25 gene. PLoS One. 2013;8:e84207.

  21. 21.

    Sanchez-Mora C, Ramos-Quiroga JA, Garcia-Martinez I, Fernandez-Castillo N, Bosch R, Richarte V, et al. Evaluation of single nucleotide polymorphisms in the miR-183-96-182 cluster in adulthood attention-deficit and hyperactivity disorder (ADHD) and substance use disorders (SUDs). Eur Neuropsychopharmacol. 2013;23:1463–73.

  22. 22.

    Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9:357–9.

  23. 23.

    Anders S, Pyl PT, Huber W. HTSeq—a Python framework to work with high-throughput sequencing data. Bioinformatics. 2015;31:166–9.

  24. 24.

    Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139–40.

  25. 25.

    Johnson WE, Li C, Rabinovic A. Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics. 2007;8:118–27.

  26. 26.

    Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 2015;43:e47.

  27. 27.

    Lu M, Shi B, Wang J, Cao Q, Cui Q. TAM: a method for enrichment and depletion analysis of a microRNA category in a list of microRNAs. BMC Bioinformatics. 2010;11:419.

  28. 28.

    Robin X, Turck N, Hainard A, Tiberti N, Lisacek F, Sanchez JC, et al. pROC: an open-source package for R and S+to analyze and compare ROC curves. BMC Bioinformatics. 2011;12:77.

  29. 29.

    Carvalho BS, Irizarry RA. A framework for oligonucleotide microarray preprocessing. Bioinformatics. 2010;26:2363–7.

  30. 30.

    Wei corrplot: visualization of a correlation matrix. R package version 0.73.T. 2013. Available at: http://CRAN.R-project.org/package=corrplot.

  31. 31.

    Karagkouni D, Paraskevopoulou MD, Chatzopoulos S, Vlachos IS, Tastsoglou S, Kanellos I, et al. DIANA-TarBasev8: a decade-long collection of experimentally supported miRNA-gene interactions. Nucleic Acids Res. 2018;46:D239–45.

  32. 32.

    Zhao D, Lin M, Chen J, Pedrosa E, Hrabovsky A, Fourcade HM, et al. MicroRNA profiling of neurons generated using induced pluripotent stem cells derived from patients with schizophrenia and schizoaffective disorder, and 22q11.2 Del. PLoS One. 2015;10:e0132387.

  33. 33.

    Hicks SD, Middleton FA. A comparative review of microRNA expression patterns in autism spectrum disorder. Front Psychiatry. 2016;7:176.

  34. 34.

    Pattni K, Banting G. Ins(1,4,5)P3 metabolism and the family of IP3-3Kinases. Cell Signal. 2004;16:643–54.

  35. 35.

    Chiappelli J, Rowland LM, Wijtenburg SA, Muellerklein F, Tagamets M, McMahon RP, et al. Evaluation of myo-inositol as a potential biomarker for depression in schizophrenia. Neuropsychopharmacology. 2015;40:2157–64.

  36. 36.

    Yu W, Greenberg ML. Inositol depletion, GSK3 inhibition and bipolar disorder. Future Neurol. 2016;11:135–48.

  37. 37.

    Arcos-Burgos M, Londono AC, Pineda DA, Lopera F, Palacio JD, Arbelaez A, et al. Analysis of brain metabolism by proton magnetic resonance spectroscopy (1H-MRS) in attention-deficit/hyperactivity disorder suggests a generalized differential ontogenic pattern from controls. Atten Defic Hyperact Disord. 2012;4:205–12.

  38. 38.

    Ferreira PE, Palmini A, Bau CH, Grevet EH, Hoefel JR, Rohde LA, et al. Differentiating attention-deficit/hyperactivity disorder inattentive and combined types: a (1)H-magnetic resonance spectroscopy study of fronto-striato-thalamic regions. J Neural Transm. 2009;116:623–9.

  39. 39.

    Soliva JC, Moreno A, Fauquet J, Bielsa A, Carmona S, Gispert JD, et al. Cerebellar neurometabolite abnormalities in pediatric attention/deficit hyperactivity disorder: a proton MR spectroscopic study. Neurosci Lett. 2010;470:60–4.

  40. 40.

    Tafazoli S, O’Neill J, Bejjani A, Ly R, Salamon N, McCracken JT, et al. 1H MRSI of middle frontal gyrus in pediatric ADHD. J Psychiatr Res. 2013;47:505–12.

  41. 41.

    Wiguna T, Guerrero AP, Wibisono S, Sastroasmoro S. Effect of 12-week administration of 20-mg long-acting methylphenidate on Glu/Cr, NAA/Cr, Cho/Cr, and mI/Cr ratios in the prefrontal cortices of school-age children in Indonesia: a study using 1H magnetic resonance spectroscopy (MRS). Clin Neuropharmacol. 2012;35:81–5.

  42. 42.

    Hammerness P, Biederman J, Petty C, Henin A, Moore CM. Brain biochemical effects of methylphenidate treatment using proton magnetic spectroscopy in youth with attention-deficit hyperactivity disorder: a controlled pilot study. CNS Neurosci Ther. 2012;18:34–40.

  43. 43.

    Caputo V, Sinibaldi L, Fiorentino A, Parisi C, Catalanotto C, Pasini A, et al. Brain derived neurotrophic factor (BDNF) expression is regulated by microRNAs miR-26a and miR-26b allele-specific binding. PLoS One. 2011;6:e28656.

  44. 44.

    Conner AC, Kissling C, Hodges E, Hunnerkopf R, Clement RM, Dudley E, et al. Neurotrophic factor-related gene polymorphisms and adult attention deficit hyperactivity disorder (ADHD) score in a high-risk male population. Am J Med Genet B Neuropsychiatr Genet. 2008;147B:1476–80.

  45. 45.

    Forstner AJ, Basmanav FB, Mattheisen M, Bohmer AC, Hollegaard MV, Janson E, et al. Investigation of the involvement of MIR185 and its target genes in the development of schizophrenia. J Psychiatry Neurosci. 2014;39:386–96.

  46. 46.

    Smith TF, Anastopoulos AD, Garrett ME, Arias-Vasquez A, Franke B, Oades RD, et al. Angiogenic, neurotrophic, and inflammatory system SNPs moderate the association between birth weight and ADHD symptom severity. Am J Med Genet B Neuropsychiatr Genet. 2014;165B:691–704.

  47. 47.

    Jacob CP, Weber H, Retz W, Kittel-Schneider S, Heupel J, Renner T, et al. Acetylcholine-metabolizing butyrylcholinesterase (BCHE) copy number and single nucleotide polymorphisms and their role in attention-deficit/hyperactivity syndrome. J Psychiatr Res. 2013;47:1902–8.

  48. 48.

    Kweon K, Shin E-S, Park KJ, Lee J-K, Joo Y, Kim H-W. Genome-wide analysis reveals four novel loci for attention-deficit hyperactivity disorder in Korean youths. J Korean Acad Child Adolesc Psychiatry. 2008;29:62–72.

  49. 49.

    Yang L, Hong Q, Zhang M, Liu X, Pan XQ, Guo M, et al. The role of Homer 1a in increasing locomotor activity and non-selective attention, and impairing learning and memory abilities. Brain Res. 2013;1515:39–47.

  50. 50.

    Smith KM, Bauer L, Fischer M, Barkley R, Navia BA. Identification and characterization of human NR4A2 polymorphisms in attention deficit hyperactivity disorder. Am J Med Genet B Neuropsychiatr Genet. 2005;133B:57–63.

  51. 51.

    Jacobsen KK, Kleppe R, Johansson S, Zayats T, Haavik J. Epistatic and gene wide effects in YWHA and aromatic amino hydroxylase genes across ADHD and other common neuropsychiatric disorders: association with YWHAE. Am J Med Genet B Neuropsychiatr Genet. 2015;168:423–32.

  52. 52.

    Panwar B, Omenn GS, Guan Y. miRmine: a database of human miRNA expression profiles. Bioinformatics. 2017;33:1554–60.

  53. 53.

    Tylee DS, Kawaguchi DM, Glatt SJ. On the outside, looking in: a review and evaluation of the comparability of blood and brain “-omes”. Am J Med Genet B Neuropsychiatr Genet. 2013;162B:595–603.

  54. 54.

    Huan T, Chen G, Liu C, Bhattacharya A, Rong J, Chen BH, et al. Age-associated microRNA expression in human peripheral blood is associated with all-cause mortality and age-related traits. Aging Cell. 2018;17.

  55. 55.

    Hannum G, Guinney J, Zhao L, Zhang L, Hughes G, Sadda S, et al. Genome-wide methylation profiles reveal quantitative views of human aging rates. Mol Cell. 2013;49:359–67.

Download references


The authors are grateful to patients and controls who kindly participated in this research. The miRNA sequencing service was carried out at the Centre for Genomic Regulation (CRG), Barcelona, Spain. The microarrays service was carried out at High Technology Unit (UAT) at Vall d’Hebron Research Institute (VHIR), Barcelona (Spain), and the Statistics and Bioinformatics Unit (UEB) at the VHIR provided statistical support.

Author information


  1. Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d’Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Catalonia, Spain

    • Cristina Sánchez-Mora
    • , María Soler Artigas
    • , Iris Garcia-Martínez
    • , Mireia Pagerols
    • , Paula Rovira
    • , Miguel Casas
    • , Josep-Antoni Ramos-Quiroga
    •  & Marta Ribasés
  2. Department of Psychiatry, Hospital Universitari Vall d’Hebron, Barcelona, Catalonia, Spain

    • Cristina Sánchez-Mora
    • , María Soler Artigas
    • , Iris Garcia-Martínez
    • , Mireia Pagerols
    • , Paula Rovira
    • , Vanesa Richarte
    • , Montse Corrales
    • , Christian Fadeuilhe
    • , Miguel Casas
    • , Josep-Antoni Ramos-Quiroga
    •  & Marta Ribasés
  3. Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain

    • Cristina Sánchez-Mora
    • , María Soler Artigas
    • , Vanesa Richarte
    • , Montse Corrales
    • , Miguel Casas
    • , Josep-Antoni Ramos-Quiroga
    •  & Marta Ribasés
  4. Department of Psychiatry and Legal Medicine, Universitat Autònoma de Barcelona, Barcelona, Catalonia, Spain

    • Vanesa Richarte
    • , Montse Corrales
    • , Miguel Casas
    •  & Josep-Antoni Ramos-Quiroga
  5. Research Unit in Clinical and Translational Bioinformatics, Vall d’Hebron Institute of Research (VHIR), Barcelona, Spain

    • Natàlia Padilla
    •  & Xavier de la Cruz
  6. Universitat Autònoma de Barcelona, Barcelona, Spain

    • Natàlia Padilla
    •  & Xavier de la Cruz
  7. ICREA, Barcelona, Spain

    • Xavier de la Cruz
  8. Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands

    • Barbara Franke
    •  & Alejandro Arias-Vásquez
  9. Department of Psychiatry, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands

    • Barbara Franke
    •  & Alejandro Arias-Vásquez


  1. Search for Cristina Sánchez-Mora in:

  2. Search for María Soler Artigas in:

  3. Search for Iris Garcia-Martínez in:

  4. Search for Mireia Pagerols in:

  5. Search for Paula Rovira in:

  6. Search for Vanesa Richarte in:

  7. Search for Montse Corrales in:

  8. Search for Christian Fadeuilhe in:

  9. Search for Natàlia Padilla in:

  10. Search for Xavier de la Cruz in:

  11. Search for Barbara Franke in:

  12. Search for Alejandro Arias-Vásquez in:

  13. Search for Miguel Casas in:

  14. Search for Josep-Antoni Ramos-Quiroga in:

  15. Search for Marta Ribasés in:

Corresponding authors

Correspondence to Cristina Sánchez-Mora or Marta Ribasés.

Supplementary information

About this article

Publication history





Issue Date