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Cortical surface area alterations shaped by genetic load for neuroticism

Abstract

Neuroticism has been shown to act as an important risk factor for major depressive disorder (MDD). Genetic and neuroimaging research has independently revealed biological correlates of neurotic personality including cortical alterations in brain regions of high relevance for affective disorders. Here we investigated the influence of a polygenic score for neuroticism (PGS) on cortical brain structure in a joint discovery sample of n = 746 healthy controls (HC) and n = 268 MDD patients. Findings were validated in an independent replication sample (n = 341 HC and n = 263 MDD). Subgroup analyses stratified for case-control status and analyses of associations between neurotic phenotype and cortical measures were carried out. PGS for neuroticism was significantly associated with a decreased cortical surface area of the inferior parietal cortex, the precuneus, the rostral cingulate cortex and the inferior frontal gyrus in the discovery sample. Similar associations between PGS and surface area of the inferior parietal cortex and the precuneus were demonstrated in the replication sample. Subgroup analyses revealed negative associations in the latter regions between PGS and surface area in both HC and MDD subjects. Neurotic phenotype was negatively correlated with surface area in similar cortical regions including the inferior parietal cortex and the precuneus. No significant associations between PGS and cortical thickness were detected. The morphometric overlap of associations between both PGS and neurotic phenotype in similar cortical regions closely related to internally focused cognition points to the potential relevance of genetically shaped cortical alterations in the development of neuroticism.

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References

  1. Lahey BB. Public health significance of neuroticism. Am Psychol. 2009;64:241–56.

    Article  Google Scholar 

  2. Kendler KS, Gatz M, Gardner CO, Pedersen NL. Personality and Major Depression. Arch Gen Psychiatry. 2006;63:1113.

    Article  Google Scholar 

  3. Navrady LB, Adams MJ, Chan SWY, Ritchie SJ, McIntosh AM, McIntosh AM. Genetic risk of major depressive disorder: the moderating and mediating effects of neuroticism and psychological resilience on clinical and self-reported depression. Psychol Med. 2018;48:1890–1899.

  4. de Moor MHM, van den Berg SM, Verweij KJH, Krueger RF, Luciano M, Arias Vasquez A, et al. Meta-analysis of genome-wide association studies for neuroticism, and the polygenic association with major depressive disorder. JAMA Psychiatry. 2015;72:642.

    Article  Google Scholar 

  5. Smith DJ, Escott-Price V, Davies G, Bailey MES, Colodro-Conde L, Ward J, et al. Genome-wide analysis of over 106000 individuals identifies 9 neuroticism-associated loci. Mol Psychiatry. 2016;21:749–57.

    Article  CAS  Google Scholar 

  6. Okbay A, Baselmans BML, De Neve J-E, Turley P, Nivard MG, Fontana MA, et al. Genetic variants associated with subjective well-being, depressive symptoms and neuroticism identified through genome-wide analyses. Nat Genet. 2016;48:624–33.

    Article  CAS  Google Scholar 

  7. Gale CR, Hagenaars SP, Davies G, Hill WD, Liewald DCM, Cullen B, et al. Pleiotropy between neuroticism and physical and mental health: findings from 108038 men and women in UK Biobank. Transl Psychiatry. 2016;6:e791–e791.

    Article  CAS  Google Scholar 

  8. Docherty AR, Moscati A, Peterson R, Edwards AC, Adkins DE, Bacanu SA, et al. SNP-based heritability estimates of the personality dimensions and polygenic prediction of both neuroticism and major depression: findings from CONVERGE. Transl Psychiatry. 2016;6:e926–e926.

    Article  CAS  Google Scholar 

  9. Middeldorp CM, de Moor MHM, McGrath LM, Gordon SD, Blackwood DH, Costa PT, et al. The genetic association between personality and major depression or bipolar disorder. A polygenic score analysis using genome-wide association data. Transl Psychiatry. 2011;1:e50.

    Article  Google Scholar 

  10. Takahashi H, Craig AM. Protein tyrosine phosphatases PTPδ, PTPσ, and LAR: presynaptic hubs for synapse organization. Trends Neurosci. 2013;36:522–34.

    Article  CAS  Google Scholar 

  11. Fournier JC, Chase HW, Greenberg T, Etkin A, Almeida JR, Stiffler R, et al. Neuroticism and individual differences in neural function in unmedicated major depression: findings from the EMBARC Study. Biol Psychiatry Cogn Neurosci Neuroimaging. 2017;2:138–48.

    PubMed  Google Scholar 

  12. Deng Y, Li S, Zhou R, Walter M. Motivation but not valence modulates neuroticism-dependent cingulate cortex and insula activity. Hum Brain Mapp. 2018;39:1664–72. https://doi.org/10.1002/hbm.23942

    Article  PubMed  PubMed Central  Google Scholar 

  13. Servaas MN, van der Velde J, Costafreda SG, Horton P, Ormel J, Riese H, et al. Neuroticism and the brain: a quantitative meta-analysis of neuroimaging studies investigating emotion processing. Neurosci Biobehav Rev. 2013;37:1518–29.

    Article  Google Scholar 

  14. Schultz CC, Warziniak H, Koch K, Schachtzabel C, Güllmar D, Reichenbach JR, et al. High levels of neuroticism are associated with decreased cortical folding of the dorsolateral prefrontal cortex. Eur Arch Psychiatry Clin Neurosci. 2017;267:579–84.

    Article  Google Scholar 

  15. Kapogiannis D, Sutin A, Davatzikos C, Costa P, Resnick S. The five factors of personality and regional cortical variability in the baltimore longitudinal study of aging. Hum Brain Mapp. 2013;34:2829–40.

    Article  Google Scholar 

  16. Lu F, Huo Y, Li M, Chen H, Liu F, Wang Y, et al. Relationship between personality and gray matter volume in healthy young adults: a voxel-based morphometric study. PLoS ONE. 2014;9:e88763.

    Article  Google Scholar 

  17. Riccelli R, Toschi N, Nigro S, Terracciano A, Passamonti L. Surface-based morphometry reveals the neuroanatomical basis of the five-factor model of personality. Soc Cogn Affect Neurosci. 2017;12:nsw175.

    Article  Google Scholar 

  18. Price JL, Drevets WC. Neural circuits underlying the pathophysiology of mood disorders. Trends Cogn Sci. 2012;16:61–71.

    Article  Google Scholar 

  19. Rive MM, van Rooijen G, Veltman DJ, Phillips ML, Schene AH, Ruhé HG. Neural correlates of dysfunctional emotion regulation in major depressive disorder. A systematic review of neuroimaging studies. Neurosci Biobehav Rev. 2013;37:2529–53.

    Article  Google Scholar 

  20. Phillips ML, Drevets WC, Rauch SL, Lane R. Neurobiology of emotion perception II: implications for major psychiatric disorders. Biol Psychiatry. 2003;54:515–28.

    Article  Google Scholar 

  21. Chang M, Womer FY, Edmiston EK, Bai C, Zhou Q, Jiang X, et al. Neurobiological commonalities and distinctions among three major psychiatric diagnostic categories: A Structural MRI Study. Schizophr Bull. 2018;44:65–74.

    Article  Google Scholar 

  22. Wittchen H-U, Wunderlich U, Gruschwitz S, Zaudig M. SKID-I. Strukturiertes Klinisches Interview für DSM-IV. Hogrefe: Göttingen, 1997.

  23. Beck AT, Steer RA. Beck Depression Inventory: manual. The Psychological Corporation, Harcourt Brace Jovanovich.: San Antonio, 1987.

  24. Costa PT, McCrae RR Revised NEO Personality Inventory (NEO-PI-RTM) and NEO Five Factor Inventory (NEO-FFI): Professional manual. Psychological Assessment Resources: Odessa, FL, 1992.

  25. Dannlowski U, Grabe HJ, Wittfeld K, Klaus J, Konrad C, Grotegerd D, et al. Multimodal imaging of a tescalcin (TESC)-regulating polymorphism (rs7294919)-specific effects on hippocampal gray matter structure. Mol Psychiatry. 2015;20:398–404.

    Article  CAS  Google Scholar 

  26. Opel N, Redlich R, Kaehler C, Grotegerd D, Dohm K, Heindel W, et al. Prefrontal gray matter volume mediates genetic risks for obesity. Mol Psychiatry. 2017;22:703–10.

    Article  CAS  Google Scholar 

  27. Vogelbacher C, Möbius TWD, Sommer J, Schuster V, Dannlowski U, Kircher T, et al. The Marburg-Münster Affective Disorders Cohort Study (MACS): a quality assurance protocol for MR neuroimaging data. Neuroimage. 2018;172:450–60.

    Article  Google Scholar 

  28. Desikan RS, Ségonne F, Fischl B, Quinn BT, Dickerson BC, Blacker D, et al. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage. 2006;31:968–80.

    Article  Google Scholar 

  29. Krug A, Dietsche B, Zöllner R, Yüksel D, Nöthen MM, Forstner AJ et al. Polygenic risk for schizophrenia affects working memory and its neural correlates in healthy subjects. Schizophr Res. 2018; 0. https://doi.org/10.1016/j.schres.2018.01.013.

  30. Chang CC, Chow CC, Tellier LC, Vattikuti S, Purcell SM, Lee JJ. Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience. 2015;4:7.

    Article  Google Scholar 

  31. Benjamini Hochberg. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B. 1995;57:289–300.

    Google Scholar 

  32. Schmaal L, Hibar DP, Sämann PG, Hall GB, Baune BT, Jahanshad N, et al. Cortical abnormalities in adults and adolescents with major depression based on brain scans from 20 cohorts worldwide in the ENIGMA Major Depressive Disorder Working Group. Mol Psychiatry. 2017;22:900–9.

    Article  CAS  Google Scholar 

  33. Karsten J, Penninx BWJH, Riese H, Ormel J, Nolen WA, Hartman CA. The state effect of depressive and anxiety disorders on big five personality traits. J Psychiatr Res. 2012;46:644–50.

    Article  Google Scholar 

  34. Panizzon MS, Fennema-Notestine C, Eyler LT, Jernigan TL, Prom-Wormley E, Neale M, et al. Distinct genetic influences on cortical surface area and cortical thickness. Cereb Cortex. 2009;19:2728–35.

    Article  Google Scholar 

  35. Eyler LT, Chen C-H, Panizzon MS, Fennema-Notestine C, Neale MC, Jak A, et al. A comparison of heritability maps of cortical surface area and thickness and the influence of adjustment for whole brain measures: a magnetic resonance imaging twin study. Twin Res Hum Genet. 2012;15:304–14.

    Article  Google Scholar 

  36. Winkler AM, Kochunov P, Blangero J, Almasy L, Zilles K, Fox PT, et al. Cortical thickness or grey matter volume? The importance of selecting the phenotype for imaging genetics studies. Neuroimage. 2010;53:1135–46.

    Article  Google Scholar 

  37. Buckner RL, Andrews-Hanna JR, Schacter DL. The Brain’s Default Network. Ann N Y Acad Sci. 2008;1124:1–38.

    Article  Google Scholar 

  38. Driver J, Noesselt T. Multisensory interplay reveals crossmodal influences on ‘Sensory-Specific’ brain regions, neural responses, and judgments. Neuron. 2008;57:11–23.

    Article  CAS  Google Scholar 

  39. Perkins AM, Arnone D, Smallwood J, Mobbs D. Thinking too much: self-generated thought as the engine of neuroticism. Trends Cogn Sci. 2015;19:492–8.

    Article  Google Scholar 

  40. Zhang S, Li C-SR. Functional clustering of the human inferior parietal lobule by whole-brain connectivity mapping of resting-state functional magnetic resonance imaging signals. Brain Connect. 2014;4:53–69.

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Margulies DS, Vincent JL, Kelly C, Lohmann G, Uddin LQ, Biswal BB, et al. Precuneus shares intrinsic functional architecture in humans and monkeys. Proc Natl Acad Sci USA. 2009;106:20069–74.

    Article  CAS  Google Scholar 

  42. Kircher TT, Senior C, Phillips ML, Benson PJ, Bullmore ET, Brammer M, et al. Towards a functional neuroanatomy of self processing: effects of faces and words. Brain Res Cogn Brain Res. 2000;10:133–44.

    Article  CAS  Google Scholar 

  43. Opel N, Zwanzger P, Redlich R, Grotegerd D, Dohm K, Arolt V, et al. Differing brain structural correlates of familial and environmental risk for major depressive disorder revealed by a combined VBM/pattern recognition approach. Psychol Med. 2016;46:277–90.

    Article  CAS  Google Scholar 

  44. Dannlowski U, Stuhrmann A, Beutelmann V, Zwanzger P, Lenzen T, Grotegerd D, et al. Limbic scars: long-term consequences of childhood maltreatment revealed by functional and structural magnetic resonance imaging. Biol Psychiatry. 2012;71:286–93.

    Article  Google Scholar 

  45. Redlich R, Almeida JJR, Grotegerd D, Opel N, Kugel H, Heindel W, et al. Brain morphometric biomarkers distinguishing unipolar and bipolar depression. JAMA Psychiatry. 2014;71:1222.

    Article  Google Scholar 

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Acknowledgements

This work was funded by the German Research Foundation (DFG, grant FOR2107 DA1151/5–1 and DA1151/5–2 to UD; SFB-TRR58, Projects C09 and Z02 to UD; FOR2107 KR3822/7–2, KO4291/3–1, and KR3822/5–1 to AK; JA1890/7–1 and JA1890/7–2 to AJ; NE2254/1-2 to IN; RI908/11-2 to MR; NO246/10-2 to MMN; HA7070/2-2 to TH; KI588/14-1 and KI588/14-2 to TK) and the Interdisciplinary Center for Clinical Research (IZKF) of the medical faculty of Münster (grant Dan3/012/17 to UD) and the Deanery of the Medical Faculty of the University of Münster.

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Correspondence to Udo Dannlowski.

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Opel, N., Amare, A.T., Redlich, R. et al. Cortical surface area alterations shaped by genetic load for neuroticism. Mol Psychiatry 25, 3422–3431 (2020). https://doi.org/10.1038/s41380-018-0236-9

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