Hostname: page-component-586b7cd67f-tf8b9 Total loading time: 0 Render date: 2024-11-22T12:28:26.988Z Has data issue: false hasContentIssue false
  • English
  • Français

Polygenic risk for schizophrenia, transition and cortical gyrification: a high-risk study

Published online by Cambridge University Press:  25 October 2017

E. Neilson ,
C. Bois ,
T.-K. Clarke ,
L. Hall ,
E. C. Johnstone ,
D. G. C. Owens ,
H. C. Whalley ,
A. M. McIntosh  and
S. M. Lawrie
E. Neilson*
Affiliation:
Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Kennedy Tower, Edinburgh, UK
C. Bois
Affiliation:
Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Kennedy Tower, Edinburgh, UK
T.-K. Clarke
Affiliation:
Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Kennedy Tower, Edinburgh, UK
L. Hall
Affiliation:
International Centre for Life, Institute of Genetic Medicine, Newcastle University, Central Parkway, Newcastle upon Tyne, UK
E. C. Johnstone
Affiliation:
Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Kennedy Tower, Edinburgh, UK
D. G. C. Owens
Affiliation:
Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Kennedy Tower, Edinburgh, UK
H. C. Whalley
Affiliation:
Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Kennedy Tower, Edinburgh, UK
A. M. McIntosh
Affiliation:
Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Kennedy Tower, Edinburgh, UK
S. M. Lawrie
Affiliation:
Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Kennedy Tower, Edinburgh, UK
*
Author for correspondence: E Neilson, E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Background

Schizophrenia is a highly heritable disorder, linked to several structural abnormalities of the brain. More specifically, previous findings have suggested that increased gyrification in frontal and temporal regions are implicated in the pathogenesis of schizophrenia.

Methods

The current study included participants at high familial risk of schizophrenia who remained well (n = 31), who developed sub-diagnostic symptoms (n = 28) and who developed schizophrenia (n = 9) as well as healthy controls (HC) (n = 16). We first tested whether individuals at high familial risk of schizophrenia carried an increased burden of trait-associated alleles using polygenic risk score analysis. We then assessed the extent to which polygenic risk was associated with gyral folding in the frontal and temporal lobes.

Results

We found that individuals at high familial risk of schizophrenia who developed schizophrenia carried a significantly greater burden of risk-conferring variants for the disorder compared to those at high risk (HR) who developed sub-diagnostic symptoms or remained well and HC. Furthermore, within the HR cohort, there was a significant and positive association between schizophrenia polygenic risk score and bilateral frontal gyrification.

Conclusions

These results suggest that polygenic risk for schizophrenia impacts upon early neurodevelopment to confer greater gyral folding in adulthood and an increased risk of developing the disorder.

Keywords

Familial high riskpolygenic risk scoresstructural MRI
Type
Original Articles
Information
Psychological Medicine , Volume 48 , Issue 9 , July 2018 , pp. 1532 - 1539
Copyright
Copyright © Cambridge University Press 2017 

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

Bois, C et al. (2015) Structural magnetic resonance imaging markers of susceptibility and transition to schizophrenia: a review of familial and clinical high risk population studies. Journal of Psychopharmacology 29, 144–154.Google Scholar
Bonnici, HM et al. (2007) Pre-frontal lobe gyrification index in schizophrenia, mental retardation and comorbid groups: an automated study. NeuroImage 35, 648–654.Google Scholar
Boos, HB et al. (2007) Brain volumes in relatives of patients with schizophrenia: a meta-analysis. Archives of General Psychiatry 64, 297–304.Google Scholar
Cooper, D et al. (2014) Multimodal voxel-based meta-analysis of structural and functional magnetic resonance imaging studies in those at elevated genetic risk of developing schizophrenia. Psychiatry Research 221, 69–77.Google Scholar
Dudbridge, F (2013) Power and predictive accuracy of polygenic risk scores. PLoS Genetics 9, e1003348.Google Scholar
ENIGMA2 Genetics Support Team (2012) ENIGMA2 1KGP Cookbook (v3). The Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium. Viewed 27th July 2017 (http://enigma.ini.usc.edu/wp-content/uploads/2012/07/ENIGMA2_1KGP_cookbook_v3.pdf).Google Scholar
Falkai, P et al. (2007) Disturbed frontal gyrification within families affected with schizophrenia. Journal of Psychiatric Research 41, 805–813.Google Scholar
Fischl, B and Dale, AM (2000) Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proceedings of the National Academy of Sciences 97, 11050–5.Google Scholar
Fischl, B, Liu, A and Dale, AM (2001) Automated manifold surgery: constructing geometrically accurate and topologically correct models of the human cerebral cortex. IEEE Transactions of Medical Imaging 20, 70–80.Google Scholar
Fischl, B, Sereno, MI and Dale, AM (1999) Cortical surface-based analysis. II: Inflation, flattening, and a surface-based coordinate system. NeuroImage 9, 195–207.Google Scholar
Fornito, A et al. (2012) Schizophrenia, neuroimaging and connectomics. NeuroImage 62, 2296–2314.CrossRefGoogle ScholarPubMed
Fraguas, D et al. (2014) Duration of untreated psychosis predicts functional and clinical outcome in children and adolescents with first-episode psychosis: a 2-year longitudinal study. Schizophrenia Research 152, 130–138.Google Scholar
Fusar-Poli, P et al. (2011) Neuroanatomy of vulnerability to psychosis: a voxel-based meta-analysis. Neuroscience & Biobehavioural Reviews 35, 1175–1185.Google Scholar
Genovese, CR, Lazar, NA and Nichols, T (2002) Thresholding of statistical maps in functional neuroimaging using the false discovery rate. NeuroImage 15, 870–878.Google Scholar
Gorjanc, G, Henderson, DA and Kinghorn, B, Percy, A (2007) GeneticsPed: Pedigree and Genetic Relationship Functions. R package version 1.22.0 (http://rgenetics.org).Google Scholar
Haijma, SV et al. (2013) Brain volumes in schizophrenia: a meta-analysis in over 18 000 subjects. Schizophrenia Bulletin 39, 1129–1138.Google Scholar
Harris, JM et al. (2007) Increased prefrontal gyrification in a large high-risk cohort characterizes those who develop schizophrenia and reflects abnormal prefrontal development. Biological Psychiatry 62, 722–729.Google Scholar
Harris, JM et al. (2004) Gyrification in first-episode schizophrenia: a morphometric study. Biological Psychiatry 55, 141–147.Google Scholar
Harrison, PJ and Weinberger, DR (2005) Schizophrenia genes, gene expression, and neuropathology: on the matter of their convergence. Molecular Psychiatry 10, 40–68.Google Scholar
Heinssen, RK and Insel, TR (2015) Preventing the onset of psychosis: not quite there yet. Schizophrenia Bulletin 41, 28–29.CrossRefGoogle Scholar
Hodges, A et al. (1999) People at risk of schizophrenia. Sample characteristics of the first 100 cases in the Edinburgh High-Risk Study. British Journal of Psychiatry 174, 547–553.Google Scholar
Johnstone, EC et al. (2000) Edinburgh high risk study – findings after four years: demographic, attainment and psychopathological issues. Schizophrenia Research 46, 1–15.Google Scholar
Johnstone, EC et al. (2005) Predicting schizophrenia: findings from the Edinburgh High-Risk Study. British Journal of Psychiatry 186, 18–25.Google Scholar
Lawrie, SM and Abukmeil, SS (1998) Brain abnormality in schizophrenia. A systematic and quantitative review of volumetric magnetic resonance imaging studies. British Journal of Psychiatry 172, 110–120.Google Scholar
Lee, SH et al. (2012) Estimating the proportion of variation in susceptibility to schizophrenia captured by common SNPs. Nature Genetics 44, 247–250.Google Scholar
Liu, B et al. (2016) Polygenic risk for schizophrenia influences cortical gyrification in 2 independent general populations. Schizophrenia Bulletin 43, 673–680.Google Scholar
Mancini-Marïe, A et al. (2015) Sex, age, symptoms and illness duration and their relation with gyrification index in schizophrenia. Clinical Schizophrenia & Related Psychoses https://doi.org/10.3371/CSRP.MAYO.070415.Google ScholarPubMed
McIntosh, AM et al. (2013) Polygenic risk for schizophrenia is associated with cognitive change between childhood and old age. Biological Psychiatry 73, 938–943.Google Scholar
McIntosh, AM et al. (2016) Genetic and environmental risk for chronic pain and the contribution of risk variants for major depressive disorder: a family-based mixed-model analysis. PLoS Medicine 13, e1002090.Google Scholar
McIntosh, AM et al. (2009) Prefrontal gyral folding and its cognitive correlates in bipolar disorder and schizophrenia. Acta Psychiatrica Scandinavica 119, 192–198.Google Scholar
McIntosh, AM et al. (2011) Longitudinal volume reductions in people at high genetic risk of schizophrenia as they develop psychosis. Biological Psychiatry 69, 953–958.Google Scholar
Nanda, P et al. (2014) Local gyrification index in probands with psychotic disorders and their first-degree relatives. Biological Psychiatry 76, 447–455.Google Scholar
Palaniyappan, L et al. (2011) Folding of the prefrontal cortex in schizophrenia: regional differences in gyrification. Biological Psychiatry 69, 974–979.CrossRefGoogle ScholarPubMed
Purcell, S et al. (2007) PLINK: a tool set for whole-genome association and population-based linkage analyses. American Journal of Human Genetics 81, 559–575.Google Scholar
Purcell, SM et al. (2009) Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature 460, 748–752.Google Scholar
Sallet, PC et al. (2003) Reduced cortical folding in schizophrenia: an MRI morphometric study. American Journal of Psychiatry 160, 1606–1613.Google ScholarPubMed
Sasabayashi, D et al. (2017) Increased occipital gyrification and development of psychotic disorders in individuals with an at-risk mental state: a multicenter study. Biological Psychiatry http://dx.doi.org/10.1016/j.biopsych.2017.05.018.Google Scholar
Schaer, M et al. (2008) A surface-based approach to quantify local cortical gyrification. IEEE Transactions on Medical Imaging 27, 161–170.Google Scholar
Schizophrenia Working Group of the Psychiatric Genomics Consortium (2014) Biological insights from 108 schizophrenia-associated genetic loci. Nature 511, 421–427.Google Scholar
Ségonne, F, Pacheco, J and Fischl, B (2007) Geometrically accurate topology-correction of cortical surfaces using nonseparating loops. IEEE Transactions on Medical Imaging 26, 518–529.Google Scholar
Sled, JG, Zijdenbos, AP and Evans, AC (1998) A nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE Transactions on Medical Imaging 17, 87–97.CrossRefGoogle ScholarPubMed
Vassos, E et al. (2017) An examination of polygenic score risk prediction in individuals with first-episode psychosis. Biological Psychiatry 81, 470–477.Google Scholar
Vogeley, K et al. (2000) Disturbed gyrification of the prefrontal region in male schizophrenic patients: a morphometric postmortem study. American Journal of Psychiatry 157, 34–39.Google Scholar
Whalley, HC et al. (2015) Impact of cross-disorder polygenic risk on frontal brain activation with specific effect of schizophrenia risk. Schizophrenia Research 161, 484–489.Google Scholar
White, T et al. (2003) Gyrification abnormalities in childhood- and adolescent-onset schizophrenia. Biological Psychiatry 54, 418–426.Google Scholar
White, T and Hilgetag, CC (2011) Gyrification and neural connectivity in schizophrenia. Development and Psychopathology 23, 339–352.Google Scholar
White, T and Gottesman, I (2012) Brain connectivity and gyrification as endophenotypes for schizophrenia: weight of the evidence. Current Topics in Medicinal Chemistry 12, 2393–2403.Google Scholar
Wing, JK, Cooper, JE and Sartorius, N (1974) The Description Classification of Psychiatric Symptoms: An Instruction Manual for the PSE and CATEGO System. Cambridge University: London.Google Scholar
Zilles, K et al. (1988) The human pattern of gyrification in the cerebral cortex. Anatomy and Embryology 179, 173–179.Google Scholar
Supplementary material: File

Neilson et al supplementary material

Neilson et al supplementary material 1

Download Neilson et al supplementary material(File)
File 28.9 KB