Brain Structure and Function

, Volume 221, Issue 6, pp 3013–3025 | Cite as

Anxiety is related to indices of cortical maturation in typically developing children and adolescents

  • Erik Newman
  • Wesley K. Thompson
  • Hauke Bartsch
  • Donald J. HaglerJr.
  • Chi-Hua Chen
  • Timothy T. Brown
  • Joshua M. Kuperman
  • Connor McCabe
  • Yoonho Chung
  • Ondrej Libiger
  • Natacha Akshoomoff
  • Cinnamon S. Bloss
  • B. J. Casey
  • Linda Chang
  • Thomas M. Ernst
  • Jean A. Frazier
  • Jeffrey R. Gruen
  • David N. Kennedy
  • Sarah S. Murray
  • Elizabeth R. Sowell
  • Nicholas Schork
  • Tal Kenet
  • Walter E. Kaufmann
  • Stewart Mostofsky
  • David G. Amaral
  • Anders M. Dale
  • Terry L. Jernigan
Original Article

Abstract

Anxiety is a risk factor for many adverse neuropsychiatric and socioeconomic outcomes, and has been linked to functional and structural changes in the ventromedial prefrontal cortex (VMPFC). However, the nature of these differences, as well as how they develop in children and adolescents, remains poorly understood. More effective interventions to minimize the negative consequences of anxiety require better understanding of its neurobiology in children. Recent research suggests that structural imaging studies may benefit from clearly delineating between cortical surface area and thickness when examining these associations, as these distinct cortical phenotypes are influenced by different cellular mechanisms and genetic factors. The present study examined relationships between cortical surface area and thickness of the VMPFC and a self-report measure of anxiety (SCARED-R) in 287 youths aged 7–20 years from the Pediatric Imaging, Neurocognition, and Genetics (PING) study. Age and gender interactions were examined for significant associations in order to test for developmental differences. Cortical surface area and thickness were also examined simultaneously to determine whether they contribute independently to the prediction of anxiety. Anxiety was negatively associated with relative cortical surface area of the VMPFC as well as with global cortical thickness, but these associations diminished with age. The two cortical phenotypes contributed additively to the prediction of anxiety. These findings suggest that higher anxiety in children may be characterized by both delayed expansion of the VMPFC and an altered trajectory of global cortical thinning. Further longitudinal studies will be needed to confirm these findings.

Keywords

Anxiety Brain development Cortical surface area Cortical thickness Magnetic resonance imaging Ventromedial prefrontal cortex 

Notes

Acknowledgments

This work was supported by the National Institute On Drug Abuse (grant number RC2 DA029475), the Eunice Kennedy Shriver National Institute Of Child Health & Human Development (Grant Number R01 HD061414), and the National Institute of General Medical Sciences (Grant Number R01 GM104400) of the National Institutes of Health. The content presented herein is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. These data are freely available on the PING portal: http://pingstudy.ucsd.edu.

Data reported herein represent a subset of the data collected in the PING study. PING is a multisite initiative consisting of six infrastructure cores and 10 data collection sites. The following is a description of key personnel in the infrastructure cores: Coordinating Core, Core PI and Co-PI of PING Terry L. Jernigan, Ph.D., and Connor McCabe, B.S., UC San Diego; Assessment Core, Core PI and Co-PI of PING Linda Chang, M.D., U Hawaii, Natacha Akshoomoff, Ph.D., UC San Diego, Erik Newman, Ph.D., UC San Diego; MRI Post-processing Core, Core PI and Co-PI of PING Anders M. Dale, Ph.D., UC San Diego; MRI Acquisition Core, Core PI and Co-PI of PING Thomas Ernst, Ph.D., U Hawaii, Core Co-PI Anders M. Dale, Ph.D., UC San Diego, Peter Van Zijl, Ph.D., KKI, Joshua Kuperman, Ph.D., UC San Diego; Genetics Core, Core PI and Co-PI of PING Sarah Murray, Ph.D., Cinnamon Bloss, Ph.D., and Nicholas J. Schork, Ph.D., Scripps Translational Science Institute; Informatics and Biostatistics, Mark Appelbaum, Ph.D., Anthony Gamst, Ph.D., Wesley Thompson, Ph.D., and Hauke Bartsch, Ph.D., UC San Diego. The following is a description of the key personnel at the data collection sites: University of California, San Diego, Site PI Terry L. Jernigan, Ph.D., Anders M. Dale, Ph.D., Natacha Akshoomoff, Ph.D.; University of Hawaii, Site PI Linda Chang, M.D., Thomas Ernst, Ph.D., Brian Keating, Ph.D.; University of California, Davis, Site PI David Amaral, Ph.D.; University of California, Los Angeles, Site PI Elizabeth Sowell, Ph.D.; Kennedy Krieger Institute, Johns Hopkins University, Site PIs Walter Kaufmann, M.D. and Stewart Mostofsky, M.D., Peter Van Zijl, Ph.D.; Sackler Institute, Weill Cornell Medical College, Site PI B.J. Casey, Ph.D., Erika J. Ruberry, B.A., Alisa Powers, B.A.; Massachusetts General Hospital, Harvard University, Site PIs Bruce Rosen, M.D., Ph.D. and Tal Kenet, Ph.D.; University of Massachusetts, Site PIs Jean Frazier, M.D. and David Kennedy, Ph.D.; Yale University, Site PI Jeffrey Gruen, M.D.

Compliance with ethical standards

Conflicts of interest

Jean A. Frazier has received research support from GlaxoSmithKline, Pfizer, Inc., Neuren, Roche, and Seaside Therapeutics, NICHD, NIMH, NINDS and has served on a Data Safety Monitoring Board for Forest Pharmaceuticals. Anders M. Dale is a founder of and holds equity interest in CorTechs Labs, La Jolla, CA and serves on its scientific advisory board. The terms of this arrangement have been reviewed and approved by UC San Diego, in accordance with its conflict of interest policies. All other authors reported no biomedical financial interests or potential conflicts of interest.

Research involving human participants

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Supplementary material

429_2015_1085_MOESM1_ESM.docx (272 kb)
Supplementary material 1 (DOCX 271 kb)

References

  1. Aben I, Denollet J, Lousberg R et al (2002) Personality and vulnerability to depression in stroke patients: a 1-year prospective follow-up study. Stroke 33:2391–2395CrossRefPubMedGoogle Scholar
  2. Akshoomoff N, Newman E, Thompson WK et al (2014) The NIH Toolbox Cognition Battery: results from a large normative developmental sample (PING). Neuropsychology 28:1–10CrossRefPubMedGoogle Scholar
  3. Armstrong KA, Khawaja NG (2002) Gender differences in anxiety: an investigation of the symptoms, cognitions, and sensitivity towards anxiety in a nonclinical population. Behav Cognit Psychother 30:227–231CrossRefGoogle Scholar
  4. Bartsch H, Thompson WK, Jernigan TL, Dale AM (2014) A web-portal for interactive data exploration, visualization, and hypothesis testing. Front Neuroinform 8:25. doi: 10.3389/fninf.2014.00025 CrossRefPubMedPubMedCentralGoogle Scholar
  5. Biederman J, Rosenbaum JF, Bolduc-Murphy EA et al (1993) A 3-year follow-up of children with and without behavioral inhibition. J Am Acad Child Adolesc Psychiatry 32:814–821CrossRefPubMedGoogle Scholar
  6. Blackmon K, Barr WB, Carlson C et al (2011) Structural evidence for involvement of a left amygdala-orbitofrontal network in subclinical anxiety. Psychiatry Res 194:296–303CrossRefPubMedPubMedCentralGoogle Scholar
  7. Bodden DHM, Bögels SM, Muris P (2009) The diagnostic utility of the Screen for Child Anxiety Related Emotional Disorders-71 (SCARED-71). Behav Res Ther 47:418–425CrossRefPubMedGoogle Scholar
  8. Bonaguidi F, Trivella MG, Carpeggiani C et al (1994) Personality and acute myocardial infarction: distinctive traits. G Ital Cardiol 24:745–753PubMedGoogle Scholar
  9. Brown TT, Jernigan TL (2012) Brain development during the preschool years. Neuropsychol Rev 22:313–333CrossRefPubMedPubMedCentralGoogle Scholar
  10. Brown TT, Kuperman JM, Chung Y et al (2012) Neuroanatomical assessment of biological maturity. Curr Biol 22:1693–1698CrossRefPubMedPubMedCentralGoogle Scholar
  11. Casey BJ, Oliveri ME, Insel T (2014) A neurodevelopmental perspective on the Research Domain Criteria (RDoC) framework. Biol Psychiatry 76:350–353CrossRefPubMedGoogle Scholar
  12. Cavanna AE, Trimble MR (2006) The precuneus: a review of its functional anatomy and behavioural correlates. Brain 129:564–583CrossRefPubMedGoogle Scholar
  13. Chen C-H, Gutierrez ED, Thompson W et al (2012) Hierarchical genetic organization of human cortical surface area. Science 335:1634–1636CrossRefPubMedPubMedCentralGoogle Scholar
  14. Costa PT, McCrae RR (1992) Revised NEO Personality Inventory (NEO PI-R) and NEO Five-Factor Inventory (NEO-FFI). Psychological Assessment Resources, OdessaGoogle Scholar
  15. De Bellis MD, Keshavan MS, Shifflett H et al (2002) Superior temporal gyrus volumes in pediatric generalized anxiety disorder. Biol Psychiatry 51:553–562CrossRefPubMedGoogle Scholar
  16. Deckersbach T, Dougherty DD, Rauch SL (2006) Functional imaging of mood and anxiety disorders. J Neuroimaging 16:1–10CrossRefPubMedGoogle Scholar
  17. Duarte A, Henson RN, Graham KS (2011) Stimulus content and the neural correlates of source memory. Brain Res 1373:110–123CrossRefPubMedPubMedCentralGoogle Scholar
  18. Ducharme S, Albaugh MD, Hudziak JJ et al (2014) Anxious/depressed symptoms are linked to right ventromedial prefrontal cortical thickness maturation in healthy children and young adults. Cereb Cortex 24:2941–2950CrossRefPubMedGoogle Scholar
  19. Gee DG, Gabard-Durnam LJ, Flannery J et al (2013) Early developmental emergence of human amygdala–prefrontal connectivity after maternal deprivation. Proc Natl Acad Sci 110:15638–15643CrossRefPubMedPubMedCentralGoogle Scholar
  20. Guyer AE, Monk CS, McClure-Tone EB et al (2008) A developmental examination of amygdala response to facial expressions. J Cogn Neurosci 20:1565–1582CrossRefPubMedPubMedCentralGoogle Scholar
  21. Hare TA, Tottenham N, Galvan A et al (2008) Biological substrates of emotional reactivity and regulation in adolescence during an emotional go-nogo task. Biol Psychiatry 63:927–934CrossRefPubMedPubMedCentralGoogle Scholar
  22. Hartley CA, Fischl B, Phelps EA (2011) Brain structure correlates of individual differences in the acquisition and inhibition of conditioned fear. Cereb Cortex 21:1954–1962CrossRefPubMedPubMedCentralGoogle Scholar
  23. Indovina I, Robbins TW, Núñez-Elizalde AO et al (2011) Fear-conditioning mechanisms associated with trait vulnerability to anxiety in humans. Neuron 69:563–571CrossRefPubMedPubMedCentralGoogle Scholar
  24. Insel T, Cuthbert B, Garvey M et al (2010) Research Domain Criteria (RDoC): toward a new classification framework for research on mental disorders. Am J Psychiatry 167:748–751CrossRefPubMedGoogle Scholar
  25. Jernigan TL, Gamst AC, Fennema-Notestine C, Ostergaard AL (2003) More “mapping” in brain mapping: statistical comparison of effects. Hum Brain Mapp 19:90–95CrossRefPubMedGoogle Scholar
  26. Kagan J, Snidman N (1991) Temperamental factors in human development. Am Psychol 46:856–862CrossRefPubMedGoogle Scholar
  27. Kent JM, Rauch SL (2003) Neurocircuitry of anxiety disorders. Curr Psychiatry Rep 5:266–273CrossRefPubMedGoogle Scholar
  28. Kim JH, Richardson R (2010) New findings on extinction of conditioned fear early in development: theoretical and clinical implications. Biol Psychiatry 67:297–303CrossRefPubMedGoogle Scholar
  29. Kim JH, Hamlin AS, Richardson R (2009) Fear extinction across development: the involvement of the medial prefrontal cortex as assessed by temporary inactivation and immunohistochemistry. J Neurosci 29:10802–10808CrossRefPubMedGoogle Scholar
  30. Kuhn D (2000) Metacognitive development. Cur Dir Psychol Sci 9:178–181CrossRefGoogle Scholar
  31. Kühn S, Schubert F, Gallinat J (2011) Structural correlates of trait anxiety: reduced thickness in medial orbitofrontal cortex accompanied by volume increase in nucleus accumbens. J Affect Disord 134:315–319CrossRefPubMedGoogle Scholar
  32. Lundstrom BN, Ingvar M, Petersson KM (2005) The role of precuneus and left inferior frontal cortex during source memory episodic retrieval. Neuroimage 27:824–834CrossRefPubMedGoogle Scholar
  33. McCarron P, Gunnell D, Harrison GL et al (2003) Temperament in young adulthood and later mortality: prospective observational study. J Epidemiol Community Health 57:888–892CrossRefPubMedPubMedCentralGoogle Scholar
  34. McCarty CA, Huggins W, Aiello AE et al (2014) PhenX RISING: real world implementation and sharing of PhenX measures. BMC Med Genomics 7:16. doi: 10.1186/1755-8794-7-16 CrossRefPubMedPubMedCentralGoogle Scholar
  35. McCurdy LY, Maniscalco B, Metcalfe J et al (2013) Anatomical coupling between distinct metacognitive systems for memory and visual perception. J Neurosci 33:1897–1906CrossRefPubMedPubMedCentralGoogle Scholar
  36. Milad MR, Rauch SL (2007) The Role of the orbitofrontal cortex in anxiety disorders. Ann N Y Acad Sci 1121:546–561CrossRefPubMedGoogle Scholar
  37. Milad MR, Quinn BT, Pitman RK et al (2005) Thickness of ventromedial prefrontal cortex in humans is correlated with extinction memory. Proc Natl Acad Sci USA 102:10706–10711CrossRefPubMedPubMedCentralGoogle Scholar
  38. Milham MP, Nugent AC, Drevets WC et al (2005) Selective reduction in amygdala volume in pediatric anxiety disorders: a voxel-based morphometry investigation. Biol Psychiatry 57:961–966CrossRefPubMedGoogle Scholar
  39. Muris P, Merckelbach H, Mayer B et al (1998) The Screen for Child Anxiety Related Emotional Disorders (SCARED) and traditional childhood anxiety measures. J Behav Ther Exp Psychiatry 29:327–339CrossRefPubMedGoogle Scholar
  40. Muris P, Merckelbach H, van Brakel A, Mayer AB (1999) The revised version of the screen for child anxiety related emotional disorders (SCARED-R): further evidence for its reliability and validity. Anxiety Stress Coping 12:411–425CrossRefPubMedGoogle Scholar
  41. Myers-Schulz B, Koenigs M (2012) Functional anatomy of ventromedial prefrontal cortex: implications for mood and anxiety disorders. Mol Psychiatry 17:132–141CrossRefPubMedGoogle Scholar
  42. Panizzon MS, Fennema-Notestine C, Eyler LT et al (2009) Distinct genetic influences on cortical surface area and cortical thickness. Cereb Cortex 19:2728–2735CrossRefPubMedPubMedCentralGoogle Scholar
  43. Rothbart MK, Ahadi SA, Hershey KL, Fisher P (2001) Investigations of temperament at three to seven years: the Children’s Behavior Questionnaire. Child Dev 72:1394–1408CrossRefPubMedGoogle Scholar
  44. Sehlmeyer C, Dannlowski U (2011) Neural correlates of trait anxiety in fear extinction. Psychol Med 41:789–798CrossRefPubMedGoogle Scholar
  45. Shin LM, Liberzon I (2010) The neurocircuitry of fear, stress, and anxiety disorders. Neuropsychopharmacology 35:169–191CrossRefPubMedGoogle Scholar
  46. Spielberger CD (1973) State trait anxiety inventory for children. Consulting Psychologists Press, Palo AltoGoogle Scholar
  47. Spielberger R, Gorsuch R, Lushene R et al (1983) Manual for the state-trait anxiety inventory. Consulting Psychologists Press, Palo AltoGoogle Scholar
  48. Stein MB, Jang KL, Livesey DJ (1999) Heritability of anxiety sensitivity: a twin study. Am J Psychiatry 156:246–251PubMedGoogle Scholar
  49. Strawn JR, Wehry AM, DelBello MP et al (2012) Establishing the neurobiologic basis of treatment in children and adolescents with generalized anxiety disorder. Depress Anxiety 29:328–339CrossRefPubMedGoogle Scholar
  50. Vreeke LJ, Muris P, Mayer B et al (2012) The assessment of an inhibited, anxiety-prone temperament in a Dutch multi-ethnic population of preschool children. Eur Child Adolesc Psychiatry 21:623–633CrossRefPubMedPubMedCentralGoogle Scholar
  51. Wells A (2005) The metacognitive model of GAD: assessment of meta-worry and relationship with DSM-IV generalized anxiety disorder. Cogn Therapy Res 29:107–121CrossRefGoogle Scholar
  52. Woodward LJ, Fergusson DM (2001) Life course outcomes of young people with anxiety disorders in adolescence. J Am Acad Child Adolesc Psychiatry 40:1086–1093CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Erik Newman
    • 1
    • 2
  • Wesley K. Thompson
    • 2
    • 3
  • Hauke Bartsch
    • 4
  • Donald J. HaglerJr.
    • 4
    • 5
  • Chi-Hua Chen
    • 2
    • 4
  • Timothy T. Brown
    • 4
    • 6
  • Joshua M. Kuperman
    • 4
    • 5
  • Connor McCabe
    • 1
    • 7
  • Yoonho Chung
    • 1
    • 4
    • 8
  • Ondrej Libiger
    • 9
  • Natacha Akshoomoff
    • 1
    • 2
  • Cinnamon S. Bloss
    • 9
  • B. J. Casey
    • 10
  • Linda Chang
    • 11
  • Thomas M. Ernst
    • 11
  • Jean A. Frazier
    • 12
  • Jeffrey R. Gruen
    • 13
    • 14
  • David N. Kennedy
    • 12
  • Sarah S. Murray
    • 15
  • Elizabeth R. Sowell
    • 16
    • 17
  • Nicholas Schork
    • 9
  • Tal Kenet
    • 18
  • Walter E. Kaufmann
    • 19
  • Stewart Mostofsky
    • 20
  • David G. Amaral
    • 21
  • Anders M. Dale
    • 4
    • 5
    • 6
    • 22
  • Terry L. Jernigan
    • 1
    • 2
    • 5
    • 22
  1. 1.Center for Human DevelopmentUniversity of California, San DiegoLa JollaUSA
  2. 2.Department of PsychiatryUniversity of California, San DiegoLa JollaUSA
  3. 3.Stein Institute for Research on AgingUniversity of California, San DiegoLa JollaUSA
  4. 4.Multimodal Imaging LaboratoryUniversity of California, San DiegoLa JollaUSA
  5. 5.Department of RadiologyUniversity of California, San DiegoLa JollaUSA
  6. 6.Department of NeurosciencesUniversity of California, San DiegoLa JollaUSA
  7. 7.Department of PsychologyUniversity of WashingtonSeattleUSA
  8. 8.Department of PsychologyYale UniversityNew HavenUSA
  9. 9.Scripps Genomic MedicineScripps Translational Science Institute and Scripps HealthLa JollaUSA
  10. 10.Sackler Institute for Developmental PsychobiologyWeil Cornell Medical CollegeNew YorkUSA
  11. 11.Department of MedicineUniversity of Hawaii and Queen’s Medical CenterHonoluluUSA
  12. 12.Department of PsychiatryUniversity of Massachusetts Medical SchoolBostonUSA
  13. 13.Department of PediatricsYale University School of MedicineNew HavenUSA
  14. 14.Department of GeneticsYale University School of MedicineNew HavenUSA
  15. 15.Department of PathologyUniversity of California, San DiegoLa JollaUSA
  16. 16.Department of PediatricsUniversity of Southern CaliforniaLos AngelesUSA
  17. 17.Children’s HospitalLos AngelesUSA
  18. 18.Department of Neurology and Athinoula A. Martinos Center for Biomedical ImagingMassachusetts General HospitalCharlestownUSA
  19. 19.Boston Children’s Hospital and Harvard Medical SchoolBostonUSA
  20. 20.Kennedy Krieger Institute and Johns Hopkins University School of MedicineBaltimoreUSA
  21. 21.Department of Psychiatry and Behavioral SciencesUniversity of California, DavisDavisUSA
  22. 22.Department of Cognitive ScienceUniversity of California, San DiegoLa JollaUSA

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