Hostname: page-component-8448b6f56d-xtgtn Total loading time: 0 Render date: 2024-04-24T17:24:47.348Z Has data issue: false hasContentIssue false
  • English
  • Français

Abnormalities in left inferior frontal gyral thickness and parahippocampal gyral volume in young people at high genetic risk for bipolar disorder

Published online by Cambridge University Press:  12 April 2016

G. Roberts ,
R. Lenroot ,
A. Frankland ,
P. K. Yeung ,
N. Gale ,
A. Wright ,
P. Lau ,
F. Levy ,
W. Wen  and
P. B. Mitchell
G. Roberts
Affiliation:
School of Psychiatry, University of New South Wales, Sydney, Australia Black Dog Institute, Prince of Wales Hospital, Sydney, Australia
R. Lenroot
Affiliation:
School of Psychiatry, University of New South Wales, Sydney, Australia Neuroscience Research Australia, Sydney, Australia
A. Frankland
Affiliation:
School of Psychiatry, University of New South Wales, Sydney, Australia Black Dog Institute, Prince of Wales Hospital, Sydney, Australia
P. K. Yeung
Affiliation:
Neuroscience Research Australia, Sydney, Australia
N. Gale
Affiliation:
School of Psychiatry, University of New South Wales, Sydney, Australia Black Dog Institute, Prince of Wales Hospital, Sydney, Australia
A. Wright
Affiliation:
School of Psychiatry, University of New South Wales, Sydney, Australia Black Dog Institute, Prince of Wales Hospital, Sydney, Australia
P. Lau
Affiliation:
School of Psychiatry, University of New South Wales, Sydney, Australia Black Dog Institute, Prince of Wales Hospital, Sydney, Australia
F. Levy
Affiliation:
School of Psychiatry, University of New South Wales, Sydney, Australia Prince of Wales Hospital, Sydney, Australia
W. Wen
Affiliation:
School of Psychiatry, University of New South Wales, Sydney, Australia
P. B. Mitchell*
Affiliation:
School of Psychiatry, University of New South Wales, Sydney, Australia Black Dog Institute, Prince of Wales Hospital, Sydney, Australia Prince of Wales Hospital, Sydney, Australia
*
*Address for correspondence: P. B. Mitchell, School of Psychiatry, University of New South Wales, Sydney, Australia. (Email: phil.mitchell@unsw.edu.au)
Get access Rights & Permissions [Opens in a new window]

Abstract

Background

Fronto-limbic structural brain abnormalities have been reported in patients with bipolar disorder (BD), but findings in individuals at increased genetic risk of developing BD have been inconsistent. We conducted a study in adolescents and young adults (12–30 years) comparing measures of fronto-limbic cortical and subcortical brain structure between individuals at increased familial risk of BD (at risk; AR), subjects with BD and controls (CON). We separately examined cortical volume, thickness and surface area as these have distinct neurodevelopmental origins and thus may reflect differential effects of genetic risk.

Method

We compared fronto-limbic measures of grey and white matter volume, cortical thickness and surface area in 72 unaffected-risk individuals with at least one first-degree relative with bipolar disorder (AR), 38 BD subjects and 72 participants with no family history of mental illness (CON).

Results

The AR group had significantly reduced cortical thickness in the left pars orbitalis of the inferior frontal gyrus (IFG) compared with the CON group, and significantly increased left parahippocampal gyral volume compared with those with BD.

Conclusions

The finding of reduced cortical thickness of the left pars orbitalis in AR subjects is consistent with other evidence supporting the IFG as a key region associated with genetic liability for BD. The greater volume of the left parahippocampal gyrus in those at high risk is in line with some prior reports of regional increases in grey matter volume in at-risk subjects. Assessing multiple complementary morphometric measures may assist in the better understanding of abnormal developmental processes in BD.

Keywords

Bipolar disordercortical surface areagenetic riskgyral volumeinferior frontal gyrus
Type
Original Articles
Information
Psychological Medicine , Volume 46 , Issue 10 , July 2016 , pp. 2083 - 2096
Copyright
Copyright © Cambridge University Press 2016 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Alemán-Gómez, Y, Janssen, J, Schnack, H, Balaban, E, Pina-Camacho, L, Alfaro-Almagro, F, Castro-Fornieles, J, Otero, S, Baeza, I, Moreno, D (2013). The human cerebral cortex flattens during adolescence. Journal of Neuroscience 33, 15004–15010.CrossRefGoogle ScholarPubMed
Ashburner, J, Csernansk, JG, Davatzikos, C, Fox, NC, Frisoni, GB, Thompson, PM (2003). Computer-assisted imaging to assess brain structure in healthy and diseased brains. Lancet Neurology 2, 79–88.CrossRefGoogle ScholarPubMed
Badre, D, Wagner, AD (2007). Left ventrolateral prefrontal cortex and the cognitive control of memory. Neuropsychologia 45, 2883–2901.CrossRefGoogle ScholarPubMed
Benjamini, Y, Hochberg, Y (2000). On the adaptive control of the false discovery rate in multiple testing with independent statistics. Journal of Educational and Behavioral Statistics 25, 60–83.CrossRefGoogle Scholar
Birmaher, B, Axelson, D, Monk, K, Kalas, C, Goldstein, B, Hickey, MB, Obreja, M, Ehmann, M, Iyengar, S, Shamseddeen, W, Kupfer, D, Brent, D (2009). Lifetime psychiatric disorders in school-aged offspring of parents with bipolar disorder: the Pittsburgh Bipolar Offspring Study. Archives of General Psychiatry 66, 287–296.Google Scholar
Brambilla, P, Harenski, K, Nicoletti, M, Sassi, RB, Mallinger, AG, Frank, E, Kupfer, DJ, Keshavan, MS, Soares, JC (2003). MRI investigation of temporal lobe structures in bipolar patients. Journal of Psychiatric Research 37, 287–295.Google Scholar
Breakspear, M, Roberts, G, Green, MJ, Nguyen, VT, Frankland, A, Levy, F, Lenroot, R, Mitchell, PB (2015). Network dysfunction of emotional and cognitive processes in those at genetic risk of bipolar disorder. Brain 138, 3427–3439.Google Scholar
Brotman, MA, Deveney, CM, Thomas, LA, Hinton, KE, Yi, JY, Pine, DS, Leibenluft, E (2014). Parametric modulation of neural activity during face emotion processing in unaffected youth at familial risk for bipolar disorder. Bipolar Disorders 16, 756–763.Google Scholar
Chang, K, Karchemskiy, A, Barnea-Goraly, N, Garrett, A, Simeonova, DI, Reiss, A (2005). Reduced amygdalar gray matter volume in familial pediatric bipolar disorder. Journal of the American Academy of Child and Adolescent Psychiatry 44, 565–573.CrossRefGoogle ScholarPubMed
Chen, BK, Sassi, R, Axelson, D, Hatch, JP, Sanches, M, Nicoletti, M, Brambilla, P, Keshavan, MS, Ryan, ND, Birmaher, B (2004). Cross-sectional study of abnormal amygdala development in adolescents and young adults with bipolar disorder. Biological Psychiatry 56, 399–405.CrossRefGoogle Scholar
Chen, CH, Suckling, J, Lennox, BR, Ooi, C, Bullmore, ET (2011). A quantitative meta-analysis of fMRI studies in bipolar disorder. Bipolar Disorders 13, 1–15.CrossRefGoogle ScholarPubMed
Connor, SE, Ng, V, McDonald, C, Schulze, K, Morgan, K, Dazzan, P, Murray, RM (2004). A study of hippocampal shape anomaly in schizophrenia and in families multiply affected by schizophrenia or bipolar disorder. Neuroradiology 46, 523–534.Google Scholar
Dale, AM, Fischl, B, Sereno, MI (1999). Cortical surface-based analysis: segmentation and surface reconstruction. NeuroImage 9, 179–194.CrossRefGoogle ScholarPubMed
Desikan, RS, Ségonne, F, Fischl, B, Quinn, BT, Dickerson, BC, Blacker, D, Buckner, RL, Dale, AM, Maguire, RP, Hyman, BT (2006). An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. NeuroImage 31, 968–980.Google Scholar
Dickstein, DP, Milham, MP, Nugent, AC, Drevets, WC, Charney, DS, Pine, DS, Leibenluft, E (2005). Frontotemporal alterations in pediatric bipolar disorder: results of a voxel-based morphometry study. Archives of General Psychiatry 62, 734–741.Google Scholar
Elvsåshagen, T, Westlye, LT, Bøen, E, Hol, PK, Andreassen, OA, Boye, B, Malt, UF (2013). Bipolar II disorder is associated with thinning of prefrontal and temporal cortices involved in affect regulation. Bipolar Disorders 15, 855–864.Google Scholar
Fischl, B, Dale, AM (2000). Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proceedings of the National Academy of Sciences 97, 11050–11055.Google Scholar
Fischl, B, van der Kouwe, A, Destrieux, C, Halgren, E, Segonne, F, Salat, DH, Busa, E, Seidman, LJ, Goldstein, J, Kennedy, D, Caviness, V, Makris, N, Rosen, B, Dale, AM (2004). Automatically parcellating the human cerebral cortex. Cerebral Cortex 14, 11–22.CrossRefGoogle ScholarPubMed
Foland-Ross, LC, Thompson, PM, Sugar, CA, Madsen, SK, Shen, JK, Penfold, C, Ahlf, K, Rasser, PE, Fischer, J, Yang, Y (2011). Investigation of cortical thickness abnormalities in lithium-free adults with bipolar I disorder using cortical pattern matching. American Journal of Psychiatry 168, 530–539.Google Scholar
Fornito, A, Malhi, GS, Lagopoulos, J, Ivanovski, B, Wood, SJ, Saling, MM, Pantelis, C, Yücel, M (2008). Anatomical abnormalities of the anterior cingulate and paracingulate cortex in patients with bipolar I disorder. Psychiatry Research: Neuroimaging 162, 123–132.Google Scholar
Frazier, JA, Hodge, SM, Breeze, JL, Giuliano, AJ, Terry, JE, Moore, CM, Kennedy, DN, Lopez-Larson, MP, Caviness, VS, Seidman, LJ (2008). Diagnostic and sex effects on limbic volumes in early-onset bipolar disorder and schizophrenia. Schizophrenia Bulletin 34, 37–46.Google Scholar
Geller, B, Harms, MP, Wang, L, Tillman, R, DelBello, MP, Bolhofner, K, Csernansky, JG (2009). Effects of age, sex, and independent life events on amygdala and nucleus accumbens volumes in child bipolar I disorder. Biological Psychiatry 65, 432–437.CrossRefGoogle ScholarPubMed
Gogtay, N, Ordonez, A, Herman, DH, Hayashi, KM, Greenstein, D, Vaituzis, C, Lenane, M, Clasen, L, Sharp, W, Giedd, JN, Jung, D, Nugent III, TF, Toga, AW, Leibenluft, E, Thompson, PM, Rapoport, JL (2007). Dynamic mapping of cortical development before and after the onset of pediatric bipolar illness. Journal of Child Psychology and Psychiatry 48, 852–862.Google Scholar
Goodwin, FK, Jamison, KR (2007). Manic–Depressive Illness: Bipolar Disorders and Recurrent Depression. Oxford University Press: New York.Google Scholar
Greenlee, JD, Oya, H, Kawasaki, H, Volkov, IO, Kaufman, OP, Kovach, C, Howard, MA, Brugge, JF (2004). A functional connection between inferior frontal gyrus and orofacial motor cortex in human. Journal of Neurophysiology 92, 1153–1164.Google Scholar
Hajek, T, Carrey, N, Alda, M (2005). Neuroanatomical abnormalities as risk factors for bipolar disorder. Bipolar Disorders 7, 393–403.Google Scholar
Hajek, T, Cooke, C, Kopecek, M, Novak, T, Hoschl, C, Alda, M (2015). Using structural MRI to identify individuals at genetic risk for bipolar disorders: a 2-cohort, machine learning study. Journal of Psychiatry and Neuroscience 40, 316–324.Google Scholar
Hajek, T, Cullis, J, Novak, T, Kopecek, M, Blagdon, R, Propper, L, Stopkova, P, Duffy, A, Hoschl, C, Uher, R (2013). Brain structural signature of familial predisposition for bipolar disorder: replicable evidence for involvement of the right inferior frontal gyrus. Biological Psychiatry 73, 144–152.Google Scholar
Hartberg, C, Sundet, K, Rimol, L, Haukvik, U, Lange, E, Nesvåg, R, Dale, A, Melle, I, Andreassen, O, Agartz, I (2011). Brain cortical thickness and surface area correlates of neurocognitive performance in patients with schizophrenia, bipolar disorder, and healthy adults. Journal of the International Neuropsychological Society 17, 1080–1093.CrossRefGoogle ScholarPubMed
Hegarty, CE, Foland-Ross, LC, Narr, KL, Sugar, CA, McGough, JJ, Thompson, PM, Altshuler, LL (2012). ADHD comorbidity can matter when assessing cortical thickness abnormalities in patients with bipolar disorder. Bipolar Disorders 14, 843–855.Google Scholar
Houenou, J, Frommberger, J, Carde, S, Glasbrenner, M, Diener, C, Leboyer, M, Wessa, M (2011). Neuroimaging-based markers of bipolar disorder: evidence from two meta-analyses. Journal of Affective Disorders 132, 344–355.Google Scholar
Hulshoff Pol, HE, van Baal, GC, Schnack, HG, Brans, RG, van der Schot, AC, Brouwer, RM, van Haren, NE, Lepage, C, Collins, DL, Evans, AC, Boomsma, DI, Nolen, W, Kahn, RS (2012). Overlapping and segregating structural brain abnormalities in twins with schizophrenia or bipolar disorder. Archives of General Psychiatry 69, 349–359.Google Scholar
Karchemskiy, A, Garrett, A, Howe, M, Adleman, N, Simeonova, DI, Alegria, D, Reiss, A, Chang, K (2011). Amygdalar, hippocampal, and thalamic volumes in youth at high risk for development of bipolar disorder. Psychiatry Research 194, 319–325.Google Scholar
Kovacs, M (1992). Children's Depression Inventory (CDI) . Multi-Health Systems: New York.Google Scholar
Ladouceur, CD, Almeida, JR, Birmaher, B, Axelson, DA, Nau, S, Kalas, C, Monk, K, Kupfer, DJ, Phillips, ML (2008). Subcortical gray matter volume abnormalities in healthy bipolar offspring: potential neuroanatomical risk marker for bipolar disorder? Journal of the American Academy of Child and Adolescent Psychiatry 47, 532–539.CrossRefGoogle ScholarPubMed
Leckman, JF, Sholomskas, D, Thompson, WD, Belanger, A, Weissman, MM (1982). Best estimate of lifetime psychiatric diagnosis: a methodological study. Archives of General Psychiatry 39, 879–883.Google Scholar
Lim, CS, Baldessarini, RJ, Vieta, E, Yucel, M, Bora, E, Sim, K (2013). Longitudinal neuroimaging and neuropsychological changes in bipolar disorder patients: review of the evidence. Neuroscience and Biobehavioral Reviews 37, 418–435.CrossRefGoogle ScholarPubMed
López-Larson, MP, DelBello, MP, Zimmerman, ME, Schwiers, ML, Strakowski, SM (2002). Regional prefrontal gray and white matter abnormalities in bipolar disorder. Biological Psychiatry 52, 93–100.Google Scholar
Loranger, AW, Levine, PM (1978). Age at onset of bipolar affective illness. Archives of General Psychiatry 35, 1345–1348.CrossRefGoogle ScholarPubMed
Lyoo, IK, Kim, MJ, Stoll, AL, Demopulos, CM, Parow, AM, Dager, SR, Friedman, SD, Dunner, DL, Renshaw, PF (2004). Frontal lobe gray matter density decreases in bipolar I disorder. Biological Psychiatry 55, 648–651.Google Scholar
Lyoo, IK, Sung, YH, Dager, SR, Friedman, SD, Lee, JY, Kim, SJ, Kim, N, Dunner, DL, Renshaw, PF (2006). Regional cerebral cortical thinning in bipolar disorder. Bipolar Disorders 8, 65–74.Google Scholar
Matsuo, K, Kopecek, M, Nicoletti, MA, Hatch, JP, Watanabe, Y, Nery, FG, Zunta-Soares, G, Soares, JC (2012). New structural brain imaging endophenotype in bipolar disorder. Molecular Psychiatry 17, 412–420.CrossRefGoogle ScholarPubMed
Maxwell, ME (1992). Family Interview for Genetic Studies: Clinical Neurogenetics Branch. Intramural Research Program, National Institute of Mental Health: Bethesda, MD.Google Scholar
McDonald, C, Bullmore, ET, Sham, PC, Chitnis, X, Wickham, H, Bramon, E, Murray, RM (2004 a). Association of genetic risks for schizophrenia and bipolar disorder with specific and generic brain structural endophenotypes. Archives of General Psychiatry 61, 974–984.Google Scholar
McDonald, C, Zanelli, J, Rabe-Hesketh, S, Ellison-Wright, I, Sham, P, Kalidindi, S, Murray, RM, Kennedy, N (2004 b). Meta-analysis of magnetic resonance imaging brain morphometry studies in bipolar disorder. Biological Psychiatry 56, 411–417.Google Scholar
McIntosh, AM, Job, DE, Moorhead, TWJ, Harrison, LK, Lawrie, SM, Johnstone, EC (2005). White matter density in patients with schizophrenia, bipolar disorder and their unaffected relatives. Biological Psychiatry 58, 254–257.Google Scholar
Meda, SA, Pryweller, JR, Thornton-Wells, TA (2012). Regional brain differences in cortical thickness, surface area and subcortical volume in individuals with Williams syndrome. PLOS ONE 7, e31913.CrossRefGoogle ScholarPubMed
Montgomery, SA, Åsberg, M (1979). A new depression scale designed to be sensitive to change. British Journal of Psychiatry 134, 382–389.Google Scholar
Nery, FG, Monkul, ES, Lafer, B (2013). Gray matter abnormalities as brain structural vulnerability factors for bipolar disorder: a review of neuroimaging studies of individuals at high genetic risk for bipolar disorder. Australian and New Zealand Journal of Psychiatry 47, 1124–1135.Google Scholar
Noga, JT, Vladar, K, Torrey, EF (2001). A volumetric magnetic resonance imaging study of monozygotic twins discordant for bipolar disorder. Psychiatry Research 106, 25–34.CrossRefGoogle ScholarPubMed
Nurnberger, JI Jr., Blehar, MC, Kaufmann, CA, York-Cooler, C, Simpson, SG, Harkavy-Friedman, J, Severe, JB, Malaspina, D, Reich, T (1994). Diagnostic Interview for Genetic Studies: rationale, unique features, and training. Archives of General Psychiatry 51, 849–859.Google Scholar
Nurnberger, JI Jr., McInnis, M, Reich, W, Kastelic, E, Wilcox, HC, Glowinski, A, Mitchell, P, Fisher, C, Erpe, M, Gershon, ES, Berrettini, W, Laite, G, Schweitzer, R, Rhoadarmer, K, Coleman, VV, Cai, X, Azzouz, F, Liu, H, Kamali, M, Brucksch, C, Monahan, PO (2011). A high-risk study of bipolar disorder: childhood clinical phenotypes as precursors of major mood disorders. Archives of General Psychiatry 68, 1012–1020.Google Scholar
Otten, M, Meeter, M (2015). Hippocampal structure and function in individuals with bipolar disorder: a systematic review. Journal of Affective Disorders 174, 113–125.CrossRefGoogle ScholarPubMed
Papmeyer, M, Giles, S, Sussmann, JE, Kielty, S, Stewart, T, Lawrie, SM, Whalley, HC, McIntosh, AM (2015). Cortical thickness in individuals at high familial risk of mood disorders as they develop major depressive disorder. Biological Psychiatry 78, 58–66.Google Scholar
Perich, T, Lau, P, Hadzi-Pavlovic, D, Roberts, G, Frankland, A, Wright, A, Green, M, Breakspear, M, Corry, J, Radlinska, B, McCormack, C, Joslyn, C, Levy, F, Lenroot, R, Nurnberger, JI Jr., Mitchell, PB (2015). What clinical features precede the onset of bipolar disorder? Journal of Psychiatric Research 62, 71–77.Google Scholar
Phillips, ML, Ladouceur, CD, Drevets, WC (2008). A neural model of voluntary and automatic emotion regulation: implications for understanding the pathophysiology and neurodevelopment of bipolar disorder. Molecular Psychiatry 13, 833–857.Google Scholar
Phillips, ML, Swartz, HA (2014). A critical appraisal of neuroimaging studies of bipolar disorder: toward a new conceptualization of underlying neural circuitry and a road map for future research. American Journal of Psychiatry 171, 829–843.Google Scholar
Pontious, A, Kowalczyk, T, Englund, C, Hevner, RF (2007). Role of intermediate progenitor cells in cerebral cortex development. Developmental Neuroscience 30, 24–32.CrossRefGoogle Scholar
Rimol, LM, Nesvåg, R, Hagler, DJ Jr., Bergmann, Ø, Fennema-Notestine, C, Hartberg, CB, Haukvik, UK, Lange, E, Pung, CJ, Server, A (2012). Cortical volume, surface area, and thickness in schizophrenia and bipolar disorder. Biological Psychiatry 71, 552–560.Google Scholar
Roberts, G, Green, MJ, Breakspear, M, McCormack, C, Frankland, A, Wright, A, Levy, F, Lenroot, R, Chan, HN, Mitchell, PB (2013). Reduced inferior frontal gyrus activation during response inhibition to emotional stimuli in youth at high risk of bipolar disorder. Biological Psychiatry 74, 55–61.CrossRefGoogle ScholarPubMed
Sarıçiçek, A, Yalın, N, Hıdıroğlu, C, Çavuşoğlu, B, Taş, C, Ceylan, D, Zorlu, N, Ada, E, Tunca, Z, Özerdem, A (2015). Neuroanatomical correlates of genetic risk for bipolar disorder: a voxel-based morphometry study in bipolar type I patients and healthy first degree relatives. Journal of Affective Disorders 186, 110–118.CrossRefGoogle ScholarPubMed
Selvaraj, S, Arnone, D, Job, D, Stanfield, A, Farrow, TF, Nugent, AC, Scherk, H, Gruber, O, Chen, X, Sachdev, PS (2012). Grey matter differences in bipolar disorder: a meta-analysis of voxel-based morphometry studies. Bipolar Disorders 14, 135–145.Google Scholar
Singh, MK, Chang, KD (2013). Brain structural response in individuals at familial risk for bipolar disorder: a tale of two outcomes. Biological Psychiatry 73, 109–110.CrossRefGoogle ScholarPubMed
Strakowski, SM, Adler, CM, Almeida, J, Altshuler, LL, Blumberg, HP, Chang, KD, DelBello, MP, Frangou, S, McIntosh, A, Phillips, ML, Sussman, JE, Townsend, JD (2012). The functional neuroanatomy of bipolar disorder: a consensus model. Bipolar Disorders 14, 313–325.Google Scholar
Tang, Y, Hojatkashani, C, Dinov, ID, Sun, B, Fan, L, Lin, X, Qi, H, Hua, X, Liu, S, Toga, AW (2010). The construction of a Chinese MRI brain atlas: a morphometric comparison study between Chinese and Caucasian cohorts. NeuroImage 51, 33–41.Google Scholar
Vadakkumpadan, F, Tong, Y, Sun, Y (2006). Statistical analysis of morphological differences between brains. International Journal of Neuroscience 116, 407–418.Google Scholar
van Erp, TG, Thompson, PM, Kieseppa, T, Bearden, CE, Marino, AC, Hoftman, GD, Haukka, J, Partonen, T, Huttunen, M, Kaprio, J, Lonnqvist, J, Poutanen, VP, Toga, AW, Cannon, TD (2012). Hippocampal morphology in lithium and non-lithium-treated bipolar I disorder patients, non-bipolar co-twins, and control twins. Human Brain Mapping 33, 501–510.CrossRefGoogle ScholarPubMed
Venkatasubramanian, G, Zutshi, A, Jindal, S, Srikanth, SG, Kovoor, JM, Kumar, JK, Janardhan Reddy, Y (2012). Comprehensive evaluation of cortical structure abnormalities in drug-naïve, adult patients with obsessive–compulsive disorder: a surface-based morphometry study. Journal of Psychiatric Research 46, 1161–1168.Google Scholar
Walterfang, M, Wood, AG, Barton, S, Velakoulis, D, Chen, J, Reutens, DC, Kempton, MJ, Haldane, M, Pantelis, C, Frangou, S (2009). Corpus callosum size and shape alterations in individuals with bipolar disorder and their first-degree relatives. Progress in Neuro-Psychopharmacology and Biological Psychiatry 33, 1050–1057.Google Scholar
Wechsler, D (1999). Wechsler Abbreviated Scale of Intelligence. The Psychological Corporation, Harcourt Brace & Company: New York.Google Scholar
Winkler, AM, Kochunov, P, Blangero, J, Almasy, L, Zilles, K, Fox, PT, Duggirala, R, Glahn, DC (2010). Cortical thickness or grey matter volume? The importance of selecting the phenotype for imaging genetics studies. NeuroImage 53, 1135–1146.Google Scholar
Young, R, Biggs, J, Ziegler, V, Meyer, D (1978). A rating scale for mania: reliability, validity and sensitivity. British Journal of Psychiatry 133, 429–435.Google Scholar
Supplementary material: File

Roberts supplementary material

Roberts supplementary material 1

Download Roberts supplementary material(File)
File 223.2 KB