Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Pharmacogenetics predictors of methylphenidate efficacy in childhood ADHD

Molecular Psychiatry volume 23, pages 1929–1936 (2018)Cite this article

Abstract

Stimulant medication has long been effective in treating attention-deficit/hyperactivity disorder (ADHD) and is currently the first-line pharmacological treatment for children. Both methylphenidate and amphetamine modulate extracellular catecholamine levels through interaction with dopaminergic, adrenergic and serotonergic system components; it is therefore likely that catecholaminergic molecular components influence the effects of ADHD treatment. Using meta-analysis, we sought to identify predictors of pharmacotherapy to further the clinical implementation of personalized medicine. We identified 36 studies (3647 children) linking the effectiveness of methylphenidate treatment with DNA variants. Pooled-data revealed a statistically significant association between single nucleotide polymorphisms (SNPs) rs1800544 ADRA2A (odds ratio: 1.69; confidence interval: 1.12–2.55), rs4680 COMT (odds ratio (OR): 1.40; confidence interval: 1.04–1.87), rs5569 SLC6A2 (odds ratio: 1.73; confidence interval: 1.26–2.37) and rs28386840 SLC6A2 (odds ratio: 2.93; confidence interval: 1.76–4.90), and, repeat variants variable number tandem repeat (VNTR) 4 DRD4 (odds ratio: 1.66; confidence interval: 1.16–2.37) and VNTR 10 SLC6A3 (odds ratio: 0.74; confidence interval: 0.60–0.90), whereas the following variants were not statistically significant: rs1947274 LPHN3 (odds ratio: 0.95; confidence interval: 0.71–1.26), rs5661665 LPHN3 (odds ratio: 1.07; confidence interval: 0.84–1.37) and VNTR 7 DRD4 (odds ratio: 0.68; confidence interval: 0.47–1.00). Funnel plot asymmetry among SLC6A3 studies was identified and attributed largely to small study effects. Egger’s regression test and Duval and Tweedie’s ‘trim and fill’ were used to examine and correct for publication bias. These findings have major implications for advancing our therapeutic approach to childhood ADHD treatment.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1
Figure 2
Figure 3

Similar content being viewed by others

References

  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: 434–442.

    Article  Google Scholar 

  2. American Academy of Pediatrics. ADHD: clinical practice guideline for the diagnosis, evaluation, and treatment of attention-deficit/hyperactivity disorder in children and adolescents. Pediatrics 2011; 128: 1007–1022.

    Article  Google Scholar 

  3. Hutchison SL, Ghuman JK, Ghuman HS, Karpov I, Schuster JM. Efficacy of atomoxetine in the treatment of attention-deficit hyperactivity disorder in patients with common comorbidities in children, adolescents and adults: a review. Ther Adv Psychopharmacol 2016; 6: 317–334.

    Article  CAS  Google Scholar 

  4. Safer DJ. Recent trends in stimulant usage. J Atten Disord 2015; 20: 471–477.

    Article  Google Scholar 

  5. Olfson M, Druss BG, Marcus SC. Trends in mental health care among children and adolescents. N Engl J Med 2015; 372: 2029–2038.

    Article  Google Scholar 

  6. Jensen PS, Arnold LE, Swanson JM, Vitiello B. 3-year follow-up of the NIMH MTA study. J Am Acad Child Adolesc Psychiatry 2007; 46: 989–1002.

    Article  Google Scholar 

  7. Jensen PS, Hinshaw SP, Swanson JM. Findings from the NIMH Multimodal Treatment Study of ADHD (MTA): implications and applications for primary care providers. J Dev Behav Pediatr 2001; 22: 60–73.

    Article  CAS  Google Scholar 

  8. Faraone SV, Biederman J, Spencer TJ, Aleardi M. Comparing the efficacy of medications for ADHD using meta-analysis. MedGenMed 2006; 8: 4.

    PubMed  PubMed Central  Google Scholar 

  9. Katzman MA, Sternat T. A review of OROS methylphenidate (Concerta®) in the treatment of attention-deficit/hyperactivity disorder. CNS Drugs 2014; 28: 1005–1033.

    Article  CAS  Google Scholar 

  10. Faraone SV, Buitelaar J. Comparing the efficacy of stimulants for ADHD in children and adolescents using meta-analysis. Eur Child Adolesc Psychiatry 2010; 19: 353–364.

    Article  Google Scholar 

  11. Efron D, Jarman F, Barker M. Side effects of methylphenidate and dexamphetamine in children with attention deficit hyperactivity disorder: a double-blind, crossover trial. Pediatrics 1997; 100: 662–666.

    Article  CAS  Google Scholar 

  12. Cortese S, Faraone SV, Konofal E. Sleep in children with attention-deficit/hyperactivity disorder: meta-analysis of subjective and objective studies. J Am Acad Child Adolesc Psychiatry 2009; 48: 894–908.

    PubMed  Google Scholar 

  13. Owens JA. A clinical overview of sleep and attention-deficit/hyperactivity disorder in children and adolescents. J Can Acad Child Adolesc Psychiatry 2009; 18: 92–102.

    PubMed  PubMed Central  Google Scholar 

  14. Faraone SV, Asherson P, Banaschewski T, Biederman J, Buitelaar JK, Ramos-Quiroga JA et al. Attention-deficit/hyperactivity disorder. Nat Rev Dis Primers 2015; 1: 15020–15023.

    Article  Google Scholar 

  15. van Wyk GW, Hazell PL, Kohn MR, Granger RE, Walton RJ. How oppositionality, inattention, and hyperactivity affect response to atomoxetine versus methylphenidate: a pooled meta-analysis. J Atten Disord 2012; 16: 314–324.

    Article  Google Scholar 

  16. Aron AR, Dowson JH, Sahakian BJ, Robbins TW. Methylphenidate improves response inhibition in adults with attention-deficit/hyperactivity disorder. Biol Psychiatry 2003; 54: 1465–1468.

    Article  CAS  Google Scholar 

  17. Pliszka SR. The use of psychostimulants in the pediatric patient. Pediatr Clin North Am 1998; 45: 1085–1098.

    Article  CAS  Google Scholar 

  18. Ari ME, Cetin II, Ekici F, Kocabas A, Eminoglu S, Guney E et al. Assessment of cardiovascular risks due to methylphenidate in six months of treatment in children with Attention Deficit and Hyperactivity Disorder. Bull Clin Psychopharmacol 2014; 24: 248–252.

    Article  Google Scholar 

  19. Storebø OJ, Ramstad E, Krogh HB, Nilausen TD, Skoog M, Holmskov M et al. Methylphenidate for children and adolescents with attention deficit hyperactivity disorder (ADHD). Cochrane Database Syst Rev 2015; 11: CD009885.

    Google Scholar 

  20. Polanczyk G, Caspi A, Houts R, Kollins SH, Rohde LA, Moffitt TE. Implications of extending the ADHD age-of-onset criterion to age 12: results from a prospectively studied birth cohort. J Am Acad Child Adolesc Psychiatry 2010; 49: 210–216.

    PubMed  Google Scholar 

  21. Sachidanandam R, Weissman D, Schmidt SC, Kakol JM, Stein LD, Marth G et al. A map of human genome sequence variation containing 1.42 million single nucleotide polymorphisms. Nature 2001; 409: 928–933.

    Article  CAS  Google Scholar 

  22. Sun Z, Murry DJ, Sanghani SP, Davis WI, Kedishvili NY, Zou Q et al. Methylphenidate is stereoselectively hydrolyzed by human carboxylesterase CES1A1. J Pharmacol Exp Ther 2004; 310: 469–476.

    Article  CAS  Google Scholar 

  23. Hungund BL, Perel JM, Hurwic MJ, Sverd J, Winsberg BG. Pharmacokinetics of methylphenidate in hyperkinetic children. Br J Clin Pharmac 1979; 8: 571–576.

    Article  CAS  Google Scholar 

  24. Srinivas NR, Hubbard JW, Quinn D, Korchinski ED, Midha KK. Extensive and enantioselective presystemic metabolism of dl-threo-methylphenidate in humans. Prog Neuropsychopharmacol Biol Psychiatry 1991; 15: 213–220.

    Article  CAS  Google Scholar 

  25. Shader RL, Harmatz JS, Oesterheld JR, Parmelee DX, Sallee FR, Greenblatt DJ. Population pharmacokinetics of methylphenidate in children with attention-deficit hyperactivity disorder. Pharmacology 1999; 39: 775–785.

    CAS  Google Scholar 

  26. Hosokawa M, Endo T, Fujisawa M, Hara S, Iwata N, Sato Y et al. Interindividual variation in carboxylesterase levels in human liver microsomes. Drug Metab Dispos 1995; 23: 1022–1027.

    CAS  PubMed  Google Scholar 

  27. Zhu H-J, Patrick KS, Yuan H-J, Wang J-S, Donovan JL, DeVane CL et al. Two CES1 gene mutations lead to dysfunctional carboxylesterase 1 activity in man: clinical significance and molecular basis. Am J Hum Genet 2008; 82: 1241–1248.

    Article  CAS  Google Scholar 

  28. Walter Soria N, Belaus A, Galván C, Ana Pasquali M, Velez P, del Carmen Montes C et al. A simple allele-specific polymerase chain reaction method to detect the Gly143Glu polymorphism in the human carboxylesterase 1 gene: importance of genotyping for pharmacogenetic treatment. Genet Test Mol Biomarkers 2010; 14: 749–751.

    Article  Google Scholar 

  29. Nemoda Z, Angyal N, Tarnok Z, Gadoros J, Sasvari-Szekely M. Carboxylesterase 1 gene polymorphism and methylphenidate response in ADHD. Neuropharmacology 2009; 57: 731–733.

    Article  CAS  Google Scholar 

  30. Bruxel EM, Salatino-Oliveira A, Genro JP, Zeni CP, Polanczyk GV, Chazan R et al. Association of a carboxylesterase 1 polymorphism with appetite reduction in children and adolescents with attention-deficit/hyperactivity disorder treated with methylphenidate. Pharmacogenomics J 2013; 13: 476–480.

    Article  CAS  Google Scholar 

  31. Fleckenstein AE, Volz TJ, Riddle EL, Gibb JW, Hanson GR. New insights into the mechanism of action of amphetamines. Annu Rev Pharmacol Toxicol 2007; 47: 681–698.

    Article  CAS  Google Scholar 

  32. Berman SM, Kuczenski R, McCracken JT, London ED. Potential adverse effects of amphetamine treatment on brain and behavior: a review. Mol Psychiatry 2009; 14: 123–142.

    Article  CAS  Google Scholar 

  33. Daberkow DP, Brown HD, Bunner KD, Kraniotis SA, Doellman MA, Ragozzino ME et al. Amphetamine paradoxically augments exocytotic dopamine release and phasic dopamine signals. J Pharmacol Exp Ther 2013; 33: 452–463.

    CAS  Google Scholar 

  34. Volkow ND, Wang G, Fowler JS, Logan J, Gerasimov M, Maynard L et al. Therapeutic doses of oral methylphenidate significantly increase extracellular dopamine in the human brain. J Neurosci 2001; 59: 243.

    Google Scholar 

  35. Swanson JM, Volkow ND. Pharmacokinetic and pharmacodynamic properties of stimulants: implications for the design of new treatments for ADHD. Behav Brain Res 2002; 130: 73–78.

    Article  CAS  Google Scholar 

  36. Volkow ND, Fowler JS, Wang G, Ding Y, Gatley SJ. Mechanism of action of methylphenidate: insights from PET imaging studies. J Atten Disord 2002; 6: S31–S43.

    Article  Google Scholar 

  37. Borenstein M, Hedges LV, Higgins JPT, Rothstein HR. Criticisms of meta‐analysis. In: Sharples K (ed). Introduction to Meta-Analysis. John Wiley & Sons, Ltd: Chichester, UK, 2009, pp 377–387.

  38. Winsberg BG, Comings DE. Association of the dopamine transporter gene (DAT1) with poor methylphenidate response. J Am Acad Child Adolesc Psychiatry 1999; 38: 1474–1477.

    Article  CAS  Google Scholar 

  39. Seeger G, Schloss P, Schmidt MH. Marker gene polymorphisms in hyperkinetic disorder-predictors of clinical response to treatment with methylphenidate? Neurosci Lett 2001; 313: 45–48.

    Article  CAS  Google Scholar 

  40. Tharoor H, Lobos EA, Todd RD, Reiersen AM. Association of dopamine, serotonin, and nicotinic gene polymorphisms with methylphenidate response in ADHD. Am J Med Genet B Neuropsychiatr Genet 2008; 147: 527–530.

    Article  Google Scholar 

  41. Kirley A, Lowe N, Hawi Z, Mullins C, Daly G, Waldman I et al. Association of the 480 bp DAT1 allele with methylphenidate response in a sample of Irish children with ADHD. Am J Med Genet B Neuropsychiatr Genet 2008; 121: 50–54.

    Google Scholar 

  42. McGough J, McCracken J, Swanson J, Riddle M, Kollins S, Greenhill L et al. Pharmacogenetics of methylphenidate response in preschoolers with ADHD. J Am Acad Child Adolesc Psychiatry 2006; 45: 1314–1322.

    Article  Google Scholar 

  43. Song J, Kim SW, Hong HJ, Lee MG, Lee BW, Choi TK et al. Association of SNAP-25, SLC6A2, and LPHN3 with OROS methylphenidate treatment response in attention-deficit/hyperactivity disorder. Clin Neuropharmacol 2014; 37: 136–141.

    Article  CAS  Google Scholar 

  44. Kim BN, Cummins TD, Kim JW, Bellgrove MA, Hong SB, Song SH et al. Val/Val genotype of brain-derived neurotrophic factor (BDNF) Val66Met polymorphism is associated with a better response to OROS-MPH in Korean ADHD children. Int J Neuropsychopharmacol 2011; 14: 1399–1410.

    Article  CAS  Google Scholar 

  45. Kim JI, Kim J-W, Park J-E, Park S, Hong S-B, Han D-H et al. Association of the GRIN2B rs2284411 polymorphism with methylphenidate response in attention-deficit/hyperactivity disorder. J Psychopharmacol 2017; 31: 1070–1077.

    Article  CAS  Google Scholar 

  46. McGough JJ, McCracken JT, Loo SK, Manganiello M, Leung MC, Tietjens JR et al. A candidate gene analysis of methylphenidate response in attention-deficit/hyperactivity disorder. J Am Acad Child Adolesc Psychiatry 2009; 48: 1155–1164.

    Article  Google Scholar 

  47. Sutton AJ, Duval SJ, Tweedie RL, Abrams KR, Jones DR. Empirical assessment of effect of publication bias on meta-analyses. BMJ 2000; 320: 1574–1577.

    Article  CAS  Google Scholar 

  48. Duval S, Tweedie R. Trim and fill: A simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics 2000; 56: 455–463.

    Article  CAS  Google Scholar 

  49. Hong S-B, Kim J-W, Cho S-C, Shin M-S, Kim B-N, Yoo H-J. Dopaminergic and noradrenergic gene polymorphisms and response to methylphenidate in Korean children with attention-deficit/hyperactivity disorder: is there an interaction? J Child Adolesc Psychopharmacol 2012; 22: 343–352.

    Article  CAS  Google Scholar 

  50. Kim J-W, Sharma V, Ryan ND. Predicting methylphenidate response in ADHD using machine learning approaches. Int J Neuropsychopharmacol 2015; 18: pyv052.

    Article  Google Scholar 

  51. Park S, Kim JW, Kim BN, Hong SB, Shin MS, Yoo HJ et al. No significant association between the alpha-2A-adrenergic receptor gene and treatment response in combined or inattentive subtypes of attention-deficit hyperactivity disorder. Pharmacopsychiatry 2013; 46: 169–174.

    Article  CAS  Google Scholar 

  52. Sengupta S, Grizenko N, Schmitz N, Schwartz G, Bellingham J, Polotskaia A et al. COMT Val108/158Met polymorphism and the modulation of task-oriented behavior in children with ADHD. Neuropsychopharmacology 2008; 33: 3069–3077.

    Article  CAS  Google Scholar 

  53. van der Meulen EM, Bakker SC, Pauls DL, Oteman N, Kruitwagen CLJJ, Pearson PL et al. High sibling correlation on methylphenidate response but no association with DAT1-10R homozygosity in Dutch sibpairs with ADHD. J Child Psychol Psychiatry 2005; 46: 1074–1080.

    Article  Google Scholar 

  54. Zeni CP, Guimarães AP, Polanczyk GV, Genro JP, Roman T, Hutz MH et al. No significant association between response to methylphenidate and genes of the dopaminergic and serotonergic systems in a sample of Brazilian children with attention-deficit/hyperactivity disorder. Am J Med Genet B Neuropsychiatr Genet 2007; 144B: 391–394.

    Article  Google Scholar 

  55. Pasini A, Sinibaldi L, Paloscia C, Douzgou S, Pitzianti MB, Romeo E et al. Neurocognitive effects of methylphenidate on ADHD children with different DAT genotypes: a longitudinal open label trial. Eur J Paediatr Neurol 2013; 17: 407–414.

    Article  CAS  Google Scholar 

  56. Gizer IR, Ficks C, Waldman ID. Candidate gene studies of ADHD: a meta-analytic review. Hum Genet 2009; 126: 51–90.

    Article  CAS  Google Scholar 

  57. Hawi Z, Cummins TDR, Tong J, Johnson B, Lau R, Samarrai W et al. The molecular genetic architecture of attention deficit hyperactivity disorder. Mol Psychiatry 2015; 20: 289–297.

    Article  CAS  Google Scholar 

  58. Faraone SV, Perlis RH, Doyle AE, Smoller JW, Goralnick JJ, Holmgren MA et al. Molecular genetics of attention-deficit/hyperactivity disorder. Biol Psychiatry 2005; 57: 1313–1323.

    Article  CAS  Google Scholar 

  59. Kim C-H, Hahn MK, Joung Y, Anderson SL, Steele AH, Mazei-Robinson MS et al. A polymorphism in the norepinephrine transporter gene alters promoter activity and is associated with attention-deficit hyperactivity disorder. Proc Natl Acad Sci USA 2006; 103: 19164–19169.

    Article  CAS  Google Scholar 

  60. Arnsten AFT, Li BM. Neurobiology of executive functions: catecholamine influences on prefrontal cortical functions. Biol Psychiatry 2005; 57: 1377–1384.

    Article  CAS  Google Scholar 

  61. Andrews GD, Lavin A. Methylphenidate increases cortical excitability via activation of alpha-2 noradrenergic receptors. Neuropsychopharmacology 2006; 31: 594–601.

    Article  CAS  Google Scholar 

  62. Schacht JP. COMT val158met moderation of dopaminergic drug effects on cognitive function: a critical review. Pharmacogenomics J 2016; 16: 430–438.

    Article  CAS  Google Scholar 

  63. Lotta T, Vidgren J, Tilgmann C, Ulmanen I, Melen K, Julkunen I et al. Kinetics of human soluble and membrane-bound catechol O-methyltransferase: a revised mechanism and description of the thermolabile variant of the enzyme. Biochemistry 1995; 34: 4202–4210.

    Article  CAS  Google Scholar 

  64. Stein MA, McGough JJ. The pharmacogenomic era: promise for personalizing attention deficit hyperactivity disorder therapy. Child Adolesc Psychiatr Clin N Am 2008; 17: 475–490.

    Article  Google Scholar 

  65. Kidd KK, Pakstis AJ, Yun L. An historical perspective on ‘The world-wide distribution of allele frequencies at the human dopamine D4 receptor locus’. Hum Genet 2014; 133: 431–433.

    Article  Google Scholar 

  66. Schoots O, Van Tol HHM. The human dopamine D4 receptor repeat sequences modulate expression. Pharmacogenomics J 2003; 3: 343–348.

    Article  CAS  Google Scholar 

  67. Opmeer EM, Kortekaas R, Aleman A. Depression and the role of genes involved in dopamine metabolism and signalling. Prog Neurobiol 2010; 92: 112–133.

    Article  CAS  Google Scholar 

  68. Faraone SV, Spencer TJ, Madras BK, Zhang-James Y, Biederman J. Functional effects of dopamine transporter gene genotypes on in vivo dopamine transporter functioning: a meta-analysis. Mol Psychiatry 2014; 19: 880–889.

    Article  CAS  Google Scholar 

  69. Coghill DR, Banaschewski T, Lecendreux M, Soutullo C, Zuddas A, Adeyi B et al. Post hoc analyses of the impact of previous medication on the efficacy of lisdexamfetamine dimesylate in the treatment of attention-deficit/hyperactivity disorder in a randomized, controlled trial. Neuropsychiatr Dis Treat 2014; 10: 2039–2047.

    CAS  PubMed  PubMed Central  Google Scholar 

  70. Sterne JA, Egger M, Smith GD. Systematic reviews in health care: investigating and dealing with publication and other biases in meta-analysis. BMJ 2001; 323: 101–105.

    Article  CAS  Google Scholar 

  71. Akutagava-Martins GC, Salatino-Oliveira A, Kieling CC, Rohde LA, Hutz MH. Genetics of attention-deficit/hyperactivity disorder: current findings and future directions. Expert Rev Neurother 2013; 13: 435–445.

    Article  CAS  Google Scholar 

  72. Pagerols M, Richarte V, Sánchez-Mora C, Garcia-Martínez I, Corrales M, Corominas M et al. Pharmacogenetics of methylphenidate response and tolerability in attention-deficit/hyperactivity disorder. Pharmacogenomics J 2017; 17: 98–104.

    Article  CAS  Google Scholar 

  73. Wolraich ML, Wibbelsman CJ, Brown TE, Evans SW, Gotlieb EM, Knight JR. Attention-deficit/hyperactivity disorder among adolescents: a review of the diagnosis, treatment, and clinical implications. Pediatrics 2005; 115: 1734–1746.

    Article  Google Scholar 

  74. Charach A, Ickowicz A, Schachar R. Stimulant treatment over five years: adherence, effectiveness, and adverse effects. J Am Acad Child Adolesc Psychiatry 2004; 43: 559–567.

    Article  Google Scholar 

  75. Wigal T, Greenhill L, Chuang S, McGough J, Vitiello B, Skrobala A et al. Safety and tolerability of methylphenidate in preschool children with ADHD. J Am Acad Child Adolesc Psychiatry 2006; 45: 1294–1303.

    Article  Google Scholar 

  76. Fagerness J, Fonseca E, Hess GP, Scott R, Gardner KR, Koffler M et al. Pharmacogenetic-guided psychiatric intervention associated with increased adherence and cost savings. Am J Manag Care 2014; 20: e146–e156.

    PubMed  Google Scholar 

  77. Stahl SM. Psychiatric pharmacogenomics: how to integrate into clinical practice. CNS Spectr 2017; 22: 1–4.

    Article  Google Scholar 

Download references

Acknowledgments

SVF is supported by the K.G. Jebsen Centre for Research on Neuropsychiatric Disorders, University of Bergen, Bergen, Norway, the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no. 602805, the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 667302 and NIMH grants 5R01MH101519 and U01 MH109536-01.

Author information

Authors and Affiliations

  1. Department of Neurosciences and Physiology, SUNY Upstate Medical University, Syracuse, NY, USA

    N M Myer & J R Boland

  2. Department of Neurosciences and Physiology, SUNY Upstate Medical University, Syracuse, NY, USA

    S V Faraone

Authors
  1. N M Myer
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. J R Boland
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. S V Faraone
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to N M Myer.

Ethics declarations

Conflict of Interest

NMM and JRB were employed by Genomind during the research and authorship of this manuscript. In the past year, SVF received income, potential income, travel expenses, continuing education support and/or research support from Lundbeck, KenPharm, Rhodes, Arbor, Ironshore, Shire, Akili Interactive Labs, CogCubed, Alcobra, VAYA, Sunovion, Genomind and NeuroLifeSciences. With his institution, he has US patent US20130217707 A1 for the use of sodium-hydrogen exchange inhibitors in the treatment of ADHD.

Electronic supplementary material

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Myer, N.M., Boland, J.R. & Faraone, S.V. Pharmacogenetics predictors of methylphenidate efficacy in childhood ADHD. Mol Psychiatry 23, 1929–1936 (2018). https://doi.org/10.1038/mp.2017.234

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/mp.2017.234

This article is cited by

Search

Advanced search

Quick links