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.

  • Original Article
  • Published:

Discovery and replication of dopamine-related gene effects on caudate volume in young and elderly populations (N=1198) using genome-wide search

Molecular Psychiatry volume 16, pages 927–937 (2011)Cite this article

Subjects

Abstract

The caudate is a subcortical brain structure implicated in many common neurological and psychiatric disorders. To identify specific genes associated with variations in caudate volume, structural magnetic resonance imaging and genome-wide genotypes were acquired from two large cohorts, the Alzheimer's Disease NeuroImaging Initiative (ADNI; N=734) and the Brisbane Adolescent/Young Adult Longitudinal Twin Study (BLTS; N=464). In a preliminary analysis of heritability, around 90% of the variation in caudate volume was due to genetic factors. We then conducted genome-wide association to find common variants that contribute to this relatively high heritability. Replicated genetic association was found for the right caudate volume at single-nucleotide polymorphism rs163030 in the ADNI discovery sample (P=2.36 × 10−6) and in the BLTS replication sample (P=0.012). This genetic variation accounted for 2.79 and 1.61% of the trait variance, respectively. The peak of association was found in and around two genes, WDR41 and PDE8B, involved in dopamine signaling and development. In addition, a previously identified mutation in PDE8B causes a rare autosomal-dominant type of striatal degeneration. Searching across both samples offers a rigorous way to screen for genes consistently influencing brain structure at different stages of life. Variants identified here may be relevant to common disorders affecting the caudate.

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

Similar content being viewed by others

References

  1. Peper JS, Brouwer RM, Boomsma DI, Kahn RS, Hulshoff Pol HE . Genetic influences on human brain structure: a review of brain imaging studies in twins. Hum Brain Mapp 2007; 28: 464–473.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Kremen WS, Prom-Wormley E, Panizzon MS, Eyler LT, Fischl B, Neale MC et al. Genetic and environmental influences on the size of specific brain regions in midlife: the VETSA MRI study. Neuroimage 2010; 49: 1213–1223.

    Article  PubMed  Google Scholar 

  3. Bertram L, McQueen MB, Mullin K, Blacker D, Tanzi RE . Systematic meta-analyses of Alzheimer disease genetic association studies: the AlzGene database. Nat Genet 2007; 39: 17–23.

    Article  CAS  PubMed  Google Scholar 

  4. Shaw P, Lerch JP, Pruessner JC, Taylor KN, Rose AB, Greenstein D et al. Cortical morphology in children and adolescents with different apolipoprotein E gene polymorphisms: an observational study. Lancet Neurol 2007; 6: 494–500.

    Article  CAS  PubMed  Google Scholar 

  5. Gottesman II, Gould TD . The endophenotype concept in psychiatry: etymology and strategic intentions. Am J Psychiatry 2003; 160: 636–645.

    Article  PubMed  Google Scholar 

  6. Harris GJ, Pearlson GD, Peyser CE, Aylward EH, Roberts J, Barta PE et al. Putamen volume reduction on magnetic resonance imaging exceeds caudate changes in mild Huntington′s disease. Ann Neurol 1992; 31: 69–75.

    Article  CAS  PubMed  Google Scholar 

  7. Rosas HD, Goodman J, Chen YI, Jenkins BG, Kennedy DN, Makris N et al. Striatal volume loss in HD as measured by MRI and the influence of CAG repeat. Neurology 2001; 57: 1025–1028.

    Article  CAS  PubMed  Google Scholar 

  8. Thomas M, Jankovic J . Neurodegenerative disease and iron storage in the brain. Curr Opin Neurol 2004; 17: 437–442.

    Article  PubMed  Google Scholar 

  9. Curtis AR, Fey C, Morris CM, Bindoff LA, Ince PG, Chinnery PF et al. Mutation in the gene encoding ferritin light polypeptide causes dominant adult-onset basal ganglia disease. Nat Genet 2001; 28: 350–354.

    Article  CAS  PubMed  Google Scholar 

  10. Appenzeller S, Schirmacher A, Halfter H, Baumer S, Pendziwiat M, Timmerman V et al. Autosomal-dominant striatal degeneration is caused by a mutation in the phosphodiesterase 8B gene. Am J Hum Genet 2010; 86: 83–87.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Kuhlenbaumer G, Ludemann P, Schirmacher A, De Vriendt E, Hunermund G, Young P et al. Autosomal dominant striatal degeneration (ADSD): clinical description and mapping to 5q13-5q14. Neurology 2004; 62: 2203–2208.

    Article  CAS  PubMed  Google Scholar 

  12. Sheline YI . Neuroimaging studies of mood disorder effects on the brain. Biol Psychiatry 2003; 54: 338–352.

    Article  PubMed  Google Scholar 

  13. Madsen SK, Ho AJ, Hua X, Saharan PS, Toga AW, Jack Jr CR et al. 3D maps localize caudate nucleus atrophy in 400 AD, MCI, and healthy elderly subjects. Neurobiol Aging 2010; 31: 1312–1325.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Castellanos FX, Giedd JN, Eckburg P, Marsh WL, Vaituzis AC, Kaysen D et al. Quantitative morphology of the caudate nucleus in attention deficit hyperactivity disorder. Am J Psychiatry 1994; 151: 1791–1796.

    Article  CAS  PubMed  Google Scholar 

  15. Goldman AL, Pezawas L, Mattay VS, Fischl B, Verchinski BA, Zoltick B et al. Heritability of brain morphology related to schizophrenia: a large-scale automated magnetic resonance imaging segmentation study. Biol Psychiatry 2008; 63: 475–483.

    Article  PubMed  Google Scholar 

  16. Wright IC, Rabe-Hesketh S, Woodruff PW, David AS, Murray RM, Bullmore ET . Meta-analysis of regional brain volumes in schizophrenia. Am J Psychiatry 2000; 157: 16–25.

    Article  CAS  PubMed  Google Scholar 

  17. Lander ES . The new genomics: global views of biology. Science 1996; 274: 536–539.

    Article  CAS  PubMed  Google Scholar 

  18. Hickie IB, Naismith SL, Ward PB, Scott EM, Mitchell PB, Schofield PR et al. Serotonin transporter gene status predicts caudate nucleus but not amygdala or hippocampal volumes in older persons with major depression. J Affect Disord 2007; 98: 137–142.

    Article  CAS  PubMed  Google Scholar 

  19. Bartres-Faz D, Junque C, Serra-Grabulosa JM, Lopez-Alomar A, Moya A, Bargallo N et al. Dopamine DRD2 Taq I polymorphism associates with caudate nucleus volume and cognitive performance in memory impaired subjects. Neuroreport 2002; 13: 1121–1125.

    Article  CAS  PubMed  Google Scholar 

  20. Durston S, Fossella JA, Casey BJ, Hulshoff Pol HE, Galvan A, Schnack HG et al. Differential effects of DRD4 and DAT1 genotype on fronto-striatal gray matter volumes in a sample of subjects with attention deficit hyperactivity disorder, their unaffected siblings, and controls. Mol Psychiatry 2005; 10: 678–685.

    Article  CAS  PubMed  Google Scholar 

  21. Glatt CE, Freimer NB . Association analysis of candidate genes for neuropsychiatric disease: the perpetual campaign. Trends Genet 2002; 18: 307–312.

    Article  CAS  PubMed  Google Scholar 

  22. Freimer N, Sabatti C . The use of pedigree, sib-pair and association studies of common diseases for genetic mapping and epidemiology. Nat Genet 2004; 36: 1045–1051.

    Article  CAS  PubMed  Google Scholar 

  23. Stein JL, Hua X, Morra JH, Lee S, Hibar DP, Ho AJ et al. Genome-wide analysis reveals novel genes influencing temporal lobe structure with relevance to neurodegeneration in Alzheimer's disease. Neuroimage 2010; 51: 542–554.

    Article  CAS  PubMed  Google Scholar 

  24. Petersen RC . Aging, mild cognitive impairment, and Alzheimer's disease. Neurol Clin 2000; 18: 789–806.

    Article  CAS  PubMed  Google Scholar 

  25. Medland SE, Nyholt DR, Painter JN, McEvoy BP, McRae AF, Zhu G et al. Common variants in the trichohyalin gene are associated with straight hair in Europeans. Am J Hum Genet 2009; 85: 750–755.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Mazziotta J, Toga A, Evans A, Fox P, Lancaster J, Zilles K et al. A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM). Philos Trans R Soc Lond B Biol Sci 2001; 356: 1293–1322.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Morra JH, Tu Z, Apostolova LG, Green AE, Avedissian C, Madsen SK et al. Validation of a fully automated 3D hippocampal segmentation method using subjects with Alzheimer's disease mild cognitive impairment, and elderly controls. Neuroimage 2008; 43: 59–68.

    Article  PubMed  Google Scholar 

  28. Looi JC, Lindberg O, Liberg B, Tatham V, Kumar R, Maller J et al. Volumetrics of the caudate nucleus: reliability and validity of a new manual tracing protocol. Psychiatry Res 2008; 163: 279–288.

    Article  PubMed  Google Scholar 

  29. Duvernoy HM . The Human Brain: Surface, Three-Dimensional Sectional Anatomy with MRI, and Blood Supply. 2nd edn. Springer-Verlag Wien: New York, 1999.

    Book  Google Scholar 

  30. Neale MC, Cardon LR . Methodology for Genetic Studies of Twins and Families. Kluwer Academic: Dordrecht, The Netherlands, 1992.

    Book  Google Scholar 

  31. Chiang MC, Barysheva M, Shattuck DW, Lee AD, Madsen SK, Avedissian C et al. Genetics of brain fiber architecture and intellectual performance. J Neurosci 2009; 29: 2212–2224.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 2007; 81: 559–575.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Yu J, Pressoir G, Briggs WH, Vroh Bi I, Yamasaki M, Doebley JF et al. A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat Genet 2006; 38: 203–208.

    Article  CAS  PubMed  Google Scholar 

  34. Kang HM, Zaitlen NA, Wade CM, Kirby A, Heckerman D, Daly MJ et al. Efficient control of population structure in model organism association mapping. Genetics 2008; 178: 1709–1723.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Boomsma D, Busjahn A, Peltonen L . Classical twin studies and beyond. Nat Rev Genet 2002; 3: 872–882.

    Article  CAS  PubMed  Google Scholar 

  36. Bacanu SA, Devlin B, Roeder K . The power of genomic control. Am J Hum Genet 2000; 66: 1933–1944.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Morey RA, Petty CM, Xu Y, Hayes JP, Wagner II HR, Lewis DV et al. A comparison of automated segmentation and manual tracing for quantifying hippocampal and amygdala volumes. Neuroimage 2009; 45: 855–866.

    Article  PubMed  Google Scholar 

  38. Morey RA, Selgrade ES, Wagner II HR, Huettel SA, Wang L, McCarthy G . Scan-rescan reliability of subcortical brain volumes derived from automated segmentation. Hum Brain Mapp 2010; 31: 1751–1762.

    PubMed  PubMed Central  Google Scholar 

  39. Ryu S, Mahler J, Acampora D, Holzschuh J, Erhardt S, Omodei D et al. Orthopedia homeodomain protein is essential for diencephalic dopaminergic neuron development. Curr Biol 2007; 17: 873–880.

    Article  CAS  PubMed  Google Scholar 

  40. Struyf J, Dobrin S, Page D . Combining gene expression, demographic and clinical data in modeling disease: a case study of bipolar disorder and schizophrenia. BMC Genomics 2008; 9: 531.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Kobayashi T, Gamanuma M, Sasaki T, Yamashita Y, Yuasa K, Kotera J et al. Molecular comparison of rat cyclic nucleotide phosphodiesterase 8 family: unique expression of PDE8B in rat brain. Gene 2003; 319: 21–31.

    Article  CAS  PubMed  Google Scholar 

  42. Nicola SM, Surmeier J, Malenka RC . Dopaminergic modulation of neuronal excitability in the striatum and nucleus accumbens. Annu Rev Neurosci 2000; 23: 185–215.

    Article  CAS  PubMed  Google Scholar 

  43. Girault JA, Greengard P . The neurobiology of dopamine signaling. Arch Neurol 2004; 61: 641–644.

    Article  PubMed  Google Scholar 

  44. Menniti FS, Faraci WS, Schmidt CJ . Phosphodiesterases in the CNS: targets for drug development. Nat Rev Drug Discov 2006; 5: 660–670.

    Article  CAS  PubMed  Google Scholar 

  45. Wong ML, Whelan F, Deloukas P, Whittaker P, Delgado M, Cantor RM et al. Phosphodiesterase genes are associated with susceptibility to major depression and antidepressant treatment response. Proc Natl Acad Sci USA 2006; 103: 15124–15129.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Perez-Torres S, Cortes R, Tolnay M, Probst A, Palacios JM, Mengod G . Alterations on phosphodiesterase type 7 and 8 isozyme mRNA expression in Alzheimer's disease brains examined by in situ hybridization. Exp Neurol 2003; 182: 322–334.

    Article  CAS  PubMed  Google Scholar 

  47. Kathiresan S, Willer CJ, Peloso GM, Demissie S, Musunuru K, Schadt EE et al. Common variants at 30 loci contribute to polygenic dyslipidemia. Nat Genet 2009; 41: 56–65.

    Article  CAS  PubMed  Google Scholar 

  48. Levey AI, Hersch SM, Rye DB, Sunahara RK, Niznik HB, Kitt CA et al. Localization of D1 and D2 dopamine receptors in brain with subtype-specific antibodies. Proc Natl Acad Sci USA 1993; 90: 8861–8865.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Mozley LH, Gur RC, Mozley PD, Gur RE . Striatal dopamine transporters and cognitive functioning in healthy men and women. Am J Psychiatry 2001; 158: 1492–1499.

    Article  CAS  PubMed  Google Scholar 

  50. Nieoullon A . Dopamine and the regulation of cognition and attention. Prog Neurobiol 2002; 67: 53–83.

    Article  CAS  PubMed  Google Scholar 

  51. Ohata S, Kinoshita S, Aoki R, Tanaka H, Wada H, Tsuruoka-Kinoshita S et al. Neuroepithelial cells require fucosylated glycans to guide the migration of vagus motor neuron progenitors in the developing zebrafish hindbrain. Development 2009; 136: 1653–1663.

    Article  CAS  PubMed  Google Scholar 

  52. Kong Y, Nan K, Yin Y . Identification and characterization of CAC1 as a novel CDK2-associated cullin. Cell Cycle 2009; 8: 3544–3553.

    Article  Google Scholar 

  53. Ling KH, Hewitt CA, Beissbarth T, Hyde L, Banerjee K, Cheah PS et al. Molecular networks involved in mouse cerebral corticogenesis and spatio-temporal regulation of Sox4 and Sox11 novel antisense transcripts revealed by transcriptome profiling. Genome Biol 2009; 10: R104.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Zoubek RE, Hannappel E . Influence of the N terminus and the actin-binding motif of thymosin beta4 on its interaction with G-actin. Ann N Y Acad Sci 2007; 1112: 435–441.

    Article  CAS  PubMed  Google Scholar 

  55. Pohjalainen T, Rinne JO, Nagren K, Lehikoinen P, Anttila K, Syvalahti EK et al. The A1 allele of the human D2 dopamine receptor gene predicts low D2 receptor availability in healthy volunteers. Mol Psychiatry 1998; 3: 256–260.

    Article  CAS  PubMed  Google Scholar 

  56. Lango Allen H, Estrada K, Lettre G, Berndt SI, Weedon MN, Rivadeneira F et al. Hundreds of variants clustered in genomic loci and biological pathways affect human height. Nature 2010; 467: 832–838.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Manolio TA, Collins FS, Cox NJ, Goldstein DB, Hindorff LA, Hunter DJ et al. Finding the missing heritability of complex diseases. Nature 2009; 461: 747–753.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Hodgkinson CA, Enoch MA, Srivastava V, Cummins-Oman JS, Ferrier C, Iarikova P et al. Genome-wide association identifies candidate genes that influence the human electroencephalogram. Proc Natl Acad Sci USA 2010; 107: 8695–8700.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Dick DM, Aliev F, Krueger RF, Edwards A, Agrawal A, Lynskey M et al. Genome-wide association study of conduct disorder symptomatology. Mol Psychiatry 2010 (in press).

  60. Stein JL, Hua X, Lee S, Ho AJ, Leow AD, Toga AW et al. Voxelwise genome-wide association study (vGWAS). Neuroimage 2010; 53: 1160–1174.

    Article  CAS  PubMed  Google Scholar 

  61. Vounou M, Nichols TE, Montana G . Discovering genetic associations with high-dimensional neuroimaging phenotypes: a sparse reduced-rank regression approach. Neuroimage 2010; 53: 1147–1159.

    Article  PubMed  Google Scholar 

  62. Gao X, Becker LC, Becker DM, Starmer JD, Province MA . Avoiding the high Bonferroni penalty in genome-wide association studies. Genet Epidemiol 2010; 34: 100–105.

    PubMed  PubMed Central  Google Scholar 

  63. Wellcome Trust Case Control Consortium. Genome-wide association study of 14 000 cases of seven common diseases and 3000 shared controls. Nature 2007; 447: 661–678.

    Article  Google Scholar 

  64. Purcell SM, Wray NR, Stone JL, Visscher PM, O'Donovan MC, Sullivan PF et al. Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature 2009; 460: 748–752.

    CAS  PubMed  Google Scholar 

  65. Giedd JN, Snell JW, Lange N, Rajapakse JC, Casey BJ, Kozuch PL et al. Quantitative magnetic resonance imaging of human brain development: ages 4-18. Cereb Cortex 1996; 6: 551–560.

    Article  CAS  PubMed  Google Scholar 

  66. Ifthikharuddin SF, Shrier DA, Numaguchi Y, Tang X, Ning R, Shibata DK et al. MR volumetric analysis of the human basal ganglia: normative data. Acad Radiol 2000; 7: 627–634.

    Article  CAS  PubMed  Google Scholar 

  67. Larisch R, Meyer W, Klimke A, Kehren F, Vosberg H, Muller-Gartner HW . Left-right asymmetry of striatal dopamine D2 receptors. Nucl Med Commun 1998; 19: 781–787.

    Article  CAS  PubMed  Google Scholar 

  68. Peterson BS, Riddle MA, Cohen DJ, Katz LD, Smith JC, Leckman JF . Human basal ganglia volume asymmetries on magnetic resonance images. Magn Reson Imag 1993; 11: 493–498.

    Article  CAS  Google Scholar 

  69. Yamashita K, Yoshiura T, Hiwatashi A, Noguchi T, Togao O, Takayama Y et al. Volumetric asymmetry and differential aging effect of the human caudate nucleus in normal individuals: a prospective MR imaging study. J Neuroimag 2009; 21: 34–37.

    Article  Google Scholar 

Download references

Acknowledgements

Data collection and sharing for this project was funded by the Alzheimer′s Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: Abbott, AstraZeneca AB, Bayer Schering Pharma AG, Bristol-Myers Squibb, Eisai Global Clinical Development, Elan Corporation, Genentech, GE Healthcare, GlaxoSmithKline, Innogenetics, Johnson and Johnson, Eli Lilly and Co., Medpace, Inc., Merck and Co., Inc., Novartis AG, Pfizer Inc., F Hoffman-La Roche, Schering-Plough, Synarc, Inc., as well as non-profit partners the Alzheimer's Association and Alzheimer's Drug Discovery Foundation, with participation from the US Food and Drug Administration. Private sector contributions to ADNI are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer's Disease Cooperative Study at the University of California, San Diego, CA, USA. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of California, Los Angeles, CA, USA. This research was also supported by NIH grants P30 AG010129, K01 AG030514, and the Dana Foundation. Algorithm development for this study was also funded by the NIA, NIBIB, NICHD, the National Library of Medicine, and the National Center for Research Resources (AG016570, EB01651, LM05639, RR019771, EB008432, EB008281 and EB007813, to PMT). The BTLS study was supported by the National Institute of Child Health and Human Development (R01 HD050735), and the National Health and Medical Research Council (NHMRC 486682), Australia. Genotyping was supported by NHMRC (389875). JLS was also funded by the ARCS foundation and the NIMH (1F31MH087061).

Author information

Author notes

  1. J L Stein, D P Hibar, S K Madsen, M Khamis, K L McMahon, G I de Zubicaray, N K Hansell, G W Montgomery, N G Martin, M J Wright, A J Saykin, C R Jack, M W Weiner, A W Toga and P M Thompson: Data used in the preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (www.loni.ucla.edu/ADNI). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators is available at http://www.loni.ucla.edu/ADNI/Collaboration/ADNI_Manuscript_Citations.pdf.

Authors and Affiliations

  1. Department of Neurology, Laboratory of Neuro Imaging, UCLA School of Medicine, Los Angeles, CA, USA

    J L Stein, D P Hibar, S K Madsen, M Khamis, A W Toga & P M Thompson

  2. Center for Magnetic Resonance, School of Psychology, University of Queensland, Brisbane, Queensland, Australia

    K L McMahon

  3. Functional Magnetic Resonance Imaging Laboratory, School of Psychology, University of Queensland, Brisbane, Queensland, Australia

    G I de Zubicaray

  4. Queensland Institute of Medical Research, Brisbane, Queensland, Australia

    N K Hansell, G W Montgomery, N G Martin & M J Wright

  5. Department of Radiology and Imaging Science, Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, IN, USA

    A J Saykin

  6. Mayo Clinic, Rochester, MN, USA

    C R Jack Jr

  7. Departments of Radiology, Medicine, and Psychiatry, UC San Francisco, San Francisco, CA, USA

    M W Weiner

  8. Department of Veterans Affairs Medical Center, San Francisco, CA, USA

    M W Weiner

Authors
  1. J L Stein
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. D P Hibar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. S K Madsen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. M Khamis
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. K L McMahon
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. G I de Zubicaray
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. N K Hansell
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. G W Montgomery
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. N G Martin
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. M J Wright
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. A J Saykin
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. C R Jack Jr
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. M W Weiner
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. A W Toga
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. P M Thompson
    View author publications

    You can also search for this author in PubMed Google Scholar

Consortia

the Alzheimer's Disease Neuroimaging Initiative

Corresponding author

Correspondence to P M Thompson.

Ethics declarations

Competing interests

The authors declare no conflict of interest.

Additional information

Supplementary Information accompanies the paper on the Molecular Psychiatry website

Supplementary information

PowerPoint slides

Rights and permissions

Reprints and permissions

About this article

Cite this article

Stein, J., Hibar, D., Madsen, S. et al. Discovery and replication of dopamine-related gene effects on caudate volume in young and elderly populations (N=1198) using genome-wide search. Mol Psychiatry 16, 927–937 (2011). https://doi.org/10.1038/mp.2011.32

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/mp.2011.32

Keywords

This article is cited by

Search

Advanced search

Quick links