Hostname: page-component-f554764f5-68cz6 Total loading time: 0 Render date: 2025-04-14T04:57:22.143Z Has data issue: false hasContentIssue false
  • English
  • Français

Neurocognition in individuals at high familial risk of mood disorders with or without subsequent onset of depression

Published online by Cambridge University Press:  20 July 2015

M. Papmeyer ,
J. E. Sussmann ,
J. Hall ,
J. McKirdy ,
A. Peel ,
A. Macdonald ,
S. M. Lawrie ,
H. C. Whalley  and
A. M. McIntosh
M. Papmeyer*
Affiliation:
Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
J. E. Sussmann
Affiliation:
Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
J. Hall
Affiliation:
Neuroscience and Mental Health Research Institute, Cardiff University School of Medicine, Cardiff, UK
J. McKirdy
Affiliation:
Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
A. Peel
Affiliation:
Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
A. Macdonald
Affiliation:
Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
S. M. Lawrie
Affiliation:
Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
H. C. Whalley
Affiliation:
Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
A. M. McIntosh
Affiliation:
Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
*
*Address for correspondence: M. Papmeyer, Ph.D., University of Edinburgh, Royal Edinburgh Hospital, Morningside Park, Edinburgh EH10 5HF, UK. (Email: [email protected])
Get access Rights & Permissions [Opens in a new window]

Abstract

Background

Neurocognitive performance deficits have been observed in mood disorder patients and their unaffected relatives and may therefore qualify as endophenotypes. However, the precise time course of neurocognitive deficits has not been studied so that it is unknown whether neurocognitive abnormalities reflect the early effects of familial vulnerability to mood disorders or if they emerge at illness onset.

Method

A neuropsychological test battery was administered at baseline and after a 2-year follow-up interval in 111 initially unaffected young adults at high familial risk of mood disorders and 93 healthy controls (HC). During the follow-up period, 20 high-risk subjects developed major depressive disorder (HR-MDD), with the remainder remaining well (HR-well). Linear mixed-effects models were used to investigate differences and longitudinal changes in the domains of attentional processing, working memory, verbal learning and memory, and cognitive flexibility.

Results

Reduced long delay verbal memory and extradimensional set-shifting performance across both time points were found in the HR-well group relative to controls. The HR-MDD group displayed decreased extradimensional set-shifting abilities across both time points as compared with the HC group only. There were no significant performance differences between the two high-risk groups.

Conclusions

Reduced verbal memory and cognitive flexibility are familial trait markers for vulnerability to mood disorders in individuals with a close family history of bipolar disorder. Both neurocognitive performance deficits appear to be relatively stable over a 2-year time period and do not appear to be linked to the onset of MDD. These findings support their use as stable quantitative endophenotypes for mood disorders.

Keywords

Bipolar disorderendophenotypesmajor depressive disorderneuropsychologylongitudinal studies
Type
Original Articles
Information
Psychological Medicine , Volume 45 , Issue 15 , November 2015 , pp. 3317 - 3327
Copyright
Copyright © Cambridge University Press 2015 

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.)

Article purchase

Temporarily unavailable

References

Andreasen, NC, O'Leary, DS, Arndt, S, Cizadlo, T, Hurtig, R, Rezai, K, Watkins, GL, Ponto, LL, Hichwa, RD (1995). Short-term and long-term verbal memory: a positron emission tomography study. Proceedings of the National Academy of Sciences of the United States of America 92, 5111–5115.CrossRefGoogle ScholarPubMed
Arts, B, Jabben, N, Krabbendam, L, van Os, J (2008). Meta-analyses of cognitive functioning in euthymic bipolar patients and their first-degree relatives. Psychological Medicine 38, 771–785.CrossRefGoogle ScholarPubMed
Balanza-Martinez, V, Rubio, C, Selva-Vera, G, Martinez-Aran, A, Sanchez-Moreno, J, Salazar-Fraile, J, Vieta, E, Tabares-Seisdedos, R (2008). Neurocognitive endophenotypes (endophenocognitypes) from studies of relatives of bipolar disorder subjects: a systematic review. Neuroscience and Biobehavioral Reviews 32, 1426–1438.CrossRefGoogle ScholarPubMed
Bartels, C, Wegrzyn, M, Wiedl, A, Ackermann, V, Ehrenreich, H (2010). Practice effects in healthy adults: a longitudinal study on frequent repetitive cognitive testing. BMC Neuroscience 11, 118.Google Scholar
Benjamini, Y, Hochberg, Y (1995). Controlling the false discovery rate – a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society Series B-Methodological 57, 289–300.Google Scholar
Bora, E, Yucel, M, Pantelis, C (2009). Cognitive endophenotypes of bipolar disorder: a meta-analysis of neuropsychological deficits in euthymic patients and their first-degree relatives. Journal of Affective Disorders 113, 1–20.Google Scholar
Bourne, C, Aydemir, O, Balanza-Martinez, V, Bora, E, Brissos, S, Cavanagh, JT, Clark, L, Cubukcuoglu, Z, Dias, VV, Dittmann, S, Ferrier, IN, Fleck, DE, Frangou, S, Gallagher, P, Jones, L, Kieseppa, T, Martinez-Aran, A, Melle, I, Moore, PB, Mur, M, Pfennig, A, Raust, A, Senturk, V, Simonsen, C, Smith, DJ, Bio, DS, Soeiro-de-Souza, MG, Stoddart, SD, Sundet, K, Szoke, A, Thompson, JM, Torrent, C, Zalla, T, Craddock, N, Andreassen, OA, Leboyer, M, Vieta, E, Bauer, M, Worhunsky, PD, Tzagarakis, C, Rogers, RD, Geddes, JR, Goodwin, GM (2013). Neuropsychological testing of cognitive impairment in euthymic bipolar disorder: an individual patient data meta-analysis. Acta Psychiatrica Scandinavica 128, 149–162.Google Scholar
Chamberlain, SR, Fineberg, NA, Menzies, LA, Blackwell, AD, Bullmore, ET, Robbins, TW, Sahakian, BJ (2007). Impaired cognitive flexibility and motor inhibition in unaffected first-degree relatives of patients with obsessive–compulsive disorder. American Journal of Psychiatry 164, 335–338.Google Scholar
Craddock, N (2006). Genetics of mood disorders. Psychiatry 5, 170–174.Google Scholar
Cross-Disorder Group of the Psychiatric Genomics Consortium (2013). Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis. Lancet 381, 1371–1379.Google Scholar
Delis, DC, Kramer, JH, Kaplan, E, Ober, BA (2000). California Verbal Learning Test: Second Edition. Psychological Corporation: San Antonio, TX.Google Scholar
Dias, R, Robbins, TW, Roberts, AC (1996). Dissociation in prefrontal cortex of affective and attentional shifts. Nature 380, 69–72.Google Scholar
Duffy, A (2010). From predisposition to illness: genetically sensitive intermediate pathways to mood disorders. British Journal of Psychiatry 197, 341–342.CrossRefGoogle ScholarPubMed
Dupont, S, Samson, Y, Le Bihan, D, Baulac, M (2002). Anatomy of verbal memory: a functional MRI study. Surgical and Radiologic Anatomy 24, 57–63.Google Scholar
Elgamal, S, Denburg, S, Marriott, M, MacQueen, G (2010). Clinical factors that predict cognitive function in patients with major depression. Canadian Journal of Psychiatry 55, 653–661.Google Scholar
First, MB, Spitzer, RL, Gibbon, M, Williams, JBW (1996). Structured Clinical Interview for DSM-IV Axis I Disorders, Clinical Version (SCID-CV) . American Psychiatric Press: Washington, DC.Google Scholar
Glahn, DC, Almasy, L, Barguil, M, Hare, E, Peralta, JM, Kent, JW Jr, Dassori, A, Contreras, J, Pacheco, A, Lanzagorta, N, Nicolini, H, Raventos, H, Escamilla, MA (2010). Neurocognitive endophenotypes for bipolar disorder identified in multiplex multigenerational families. Archives of General Psychiatry 67, 168–177.CrossRefGoogle ScholarPubMed
Glahn, DC, Bearden, CE, Niendam, TA, Escamilla, MA (2004). The feasibility of neuropsychological endophenotypes in the search for genes associated with bipolar affective disorder. Bipolar Disorders 6, 171–182.Google Scholar
Glahn, DC, Curran, JE, Winkler, AM, Carless, MA, Kent, JW Jr, Charlesworth, JC, Johnson, MP, Goring, HH, Cole, SA, Dyer, TD, Moses, EK, Olvera, RL, Kochunov, P, Duggirala, R, Fox, PT, Almasy, L, Blangero, J (2012). High dimensional endophenotype ranking in the search for major depression risk genes. Biological Psychiatry 71, 6–14.Google Scholar
Gottesman, II, Gould, TD (2003). The endophenotype concept in psychiatry: etymology and strategic intentions. American Journal of Psychiatry 160, 636–645.Google Scholar
Hamilton, M (1960). A rating scale for depression. Journal of Neurology, Neurosurgery and Psychiatry 23, 56–62.Google Scholar
Hampshire, A, Owen, AM (2006). Fractionating attentional control using event-related fMRI. Cerebral Cortex 16, 1679–1689.Google Scholar
Henson, RN, Burgess, N, Frith, CD (2000). Recoding, storage, rehearsal and grouping in verbal short-term memory: an fMRI study. Neuropsychologia 38, 426–440.Google Scholar
Hillegers, MH, Reichart, CG, Wals, M, Verhulst, FC, Ormel, J, Nolen, WA (2005). Five-year prospective outcome of psychopathology in the adolescent offspring of bipolar parents. Bipolar Disorders 7, 344–350.Google Scholar
Johnson, SC, Saykin, AJ, Flashman, LA, McAllister, TW, Sparling, MB (2001). Brain activation on fMRI and verbal memory ability: functional neuroanatomic correlates of CVLT performance. Journal of the International Neuropsychological Society 7, 55–62.Google Scholar
Kessler, RC, Berglund, P, Demler, O, Jin, R, Merikangas, KR, Walters, EE (2005). Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication. Archives of General Psychiatry 62, 593–602.Google Scholar
Lee, RS, Hermens, DF, Porter, MA, Redoblado-Hodge, MA (2012). A meta-analysis of cognitive deficits in first-episode major depressive disorder. Journal of Affective Disorders 140, 113–124.CrossRefGoogle ScholarPubMed
Lee, RS, Hermens, DF, Scott, J, Redoblado-Hodge, MA, Naismith, SL, Lagopoulos, J, Griffiths, KR, Porter, MA, Hickie, IB (2014). A meta-analysis of neuropsychological functioning in first-episode bipolar disorders. Journal of Psychiatric Research 57, 1–11.Google Scholar
McGuffin, P, Farmer, A, Harvey, I (1991). A polydiagnostic application of operational criteria in studies of psychotic illness. Development and reliability of the OPCRIT system. Archives of General Psychiatry 48, 764–770.CrossRefGoogle ScholarPubMed
McGuffin, P, Rijsdijk, F, Andrew, M, Sham, P, Katz, R, Cardno, A (2003). The heritability of bipolar affective disorder and the genetic relationship to unipolar depression. Archives of General Psychiatry 60, 497–502.Google Scholar
Merikangas, KR, Jin, R, He, JP, Kessler, RC, Lee, S, Sampson, NA, Viana, MC, Andrade, LH, Hu, C, Karam, EG, Ladea, M, Medina-Mora, ME, Ono, Y, Posada-Villa, J, Sagar, R, Wells, JE, Zarkov, Z (2011). Prevalence and correlates of bipolar spectrum disorder in the world mental health survey initiative. Archives of General Psychiatry 68, 241–251.CrossRefGoogle ScholarPubMed
Nelson, H (1982). The National Adult Reading Test Manual. NFER-Nelson: Windsor.Google Scholar
Phillips, ML, Drevets, WC, Rauch, SL, Lane, R (2003 a). Neurobiology of emotion perception I: the neural basis of normal emotion perception. Biological Psychiatry 54, 504–514.Google Scholar
Phillips, ML, Drevets, WC, Rauch, SL, Lane, R (2003 b). Neurobiology of emotion perception II: implications for major psychiatric disorders. Biological Psychiatry 54, 515–528.Google Scholar
Roberts, AC, Robbins, TW, Everitt, BJ (1988). The effects of intradimensional and extradimensional shifts on visual discrimination learning in humans and non-human primates. Quarterly Journal of Experimental Psychology Section B – Comparative and Physiological Psychology 40, 321–341.Google Scholar
Schulze, TG, Akula, N, Breuer, R, Steele, J, Nalls, MA, Singleton, AB, Degenhardt, FA, Nöthen, MM, Cichon, S, Rietschel, M; Bipolar Genome Study, McMahon, FJ (2014). Molecular genetic overlap in bipolar disorder, schizophrenia, and major depressive disorder. World Journal of Biological Psychiatry 15, 200–208.Google Scholar
Smoller, JW, Finn, CT (2003). Family, twin, and adoption studies of bipolar disorder. American Journal of Medical Genetics Part C: Seminars in Medical Genetics 123C, 48–58.Google Scholar
Snyder, HR (2013). Major depressive disorder is associated with broad impairments on neuropsychological measures of executive function: a meta-analysis and review. Psychological Bulletin 139, 81–132.Google Scholar
Sprooten, E, Sussmann, JE, Clugston, A, Peel, A, McKirdy, J, Moorhead, TW, Anderson, S, Shand, AJ, Giles, S, Bastin, ME, Hall, J, Johnstone, EC, Lawrie, SM, McIntosh, AM (2011). White matter integrity in individuals at high genetic risk of bipolar disorder. Biological Psychiatry 70, 350–356.Google Scholar
Strakowski, SM, Delbello, MP, Adler, CM (2005). The functional neuroanatomy of bipolar disorder: a review of neuroimaging findings. Molecular Psychiatry 10, 105–116.Google Scholar
Wechsler, D (1955). Wechsler Adult Intelligence Scale (Manual) . Psychological Corporation: New York.Google Scholar
Whalley, HC, Sussmann, JE, Chakirova, G, Mukerjee, P, Peel, A, McKirdy, J, Hall, J, Johnstone, EC, Lawrie, SM, McIntosh, AM (2011). The neural basis of familial risk and temperamental variation in individuals at high risk of bipolar disorder. Biological Psychiatry 70, 343–349.Google Scholar
Young, RC, Biggs, JT, Ziegler, VE, Meyer, DA (2000). Young Mania Rating Scale. In Handbook of Psychiatric Measures (ed. American Psychiatric Association), pp. 540–542. American Psychiatric Association: Washington, DC.Google Scholar
Supplementary material: File

Papmeyer supplementary material

Tables S1-S4

Download Papmeyer supplementary material(File)
File 133.1 KB