Hostname: page-component-76fb5796d-2lccl Total loading time: 0 Render date: 2024-04-27T02:53:56.329Z Has data issue: false hasContentIssue false
  • English
  • Français

Investigating genetic overlaps of the genetic factor differentiating schizophrenia from bipolar disorder with cognitive function and hippocampal volume

Published online by Cambridge University Press:  26 January 2022

Kazutaka Ohi Open the ORCID record for Kazutaka Ohi [Opens in a new window] ,
Yukimasa Muto ,
Kentaro Takai ,
Shunsuke Sugiyama  and
Toshiki Shioiri
Kazutaka Ohi*
Affiliation:
Department of Psychiatry, Gifu University Graduate School of Medicine, Japan; and Department of General Internal Medicine, Kanazawa Medical University, Japan
Yukimasa Muto
Affiliation:
Department of Psychiatry, Gifu University Graduate School of Medicine, Japan
Kentaro Takai
Affiliation:
Department of Psychiatry, Gifu University Graduate School of Medicine, Japan
Shunsuke Sugiyama
Affiliation:
Department of Psychiatry, Gifu University Graduate School of Medicine, Japan
Toshiki Shioiri
Affiliation:
Department of Psychiatry, Gifu University Graduate School of Medicine, Japan
*
Correspondence: Kazutaka Ohi. Email: k_ohi@gifu-u.ac.jp
Rights & Permissions [Opens in a new window]

Abstract

Schizophrenia and bipolar disorder display clinical similarities and dissimilarities. We investigated whether the genetic factor differentiating schizophrenia from bipolar disorder is genetically associated with cognitive phenotypes and hippocampal volumes. We revealed genetic overlaps of the genetic differentiating factor with low general cognitive ability, low childhood IQ, low educational attainment and reduced hippocampal volumes. The genetic correlations with low general cognitive ability and reduced hippocampal volumes were associated with risk of schizophrenia, whereas the genetic correlations with high childhood IQ and educational attainment were associated with risks of bipolar disorder. These findings suggest these disorders have disorder-specific genetic factors related to clinical phenotypes.

Keywords

Genetic correlationschizophreniabipolar disordercognitive functionhippocampus
Type
Short report
Information
BJPsych Open , Volume 8 , Issue 1 , January 2022 , e33
Check for updates
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press on behalf of the Royal College of Psychiatrists

Schizophrenia and bipolar disorder are highly heritable disorders with clinical similarities and a complex, overlapping polygenic architecture.Reference Ohi, Nishizawa, Shimada, Kataoka, Hasegawa and Shioiri1,Reference Anttila, Bulik-Sullivan, Finucane, Walters, Bras and Duncan2 In contrast, a large-scale genome-wide association study (GWAS) identified two genome-wide significant loci differentiating schizophrenia from bipolar disorder.Reference Ruderfer, Ripke, McQuillin, Boocock, Stahl and Pavlides3 Although schizophrenia displays cognitive dysfunctions and reduced hippocampal volumes,Reference Weinberg, Lenroot, Jacomb, Allen, Bruggemann and Wells4 there are somewhat limited data on these impairments in bipolar disorder. Genetic overlaps of risk for schizophrenia with cognitive impairments and reduced hippocampal volumes have been reported.Reference Anttila, Bulik-Sullivan, Finucane, Walters, Bras and Duncan2,Reference Ohi, Shimada, Kataoka, Yasuyama, Kawasaki and Shioiri5,Reference Ohi, Sumiyoshi, Fujino, Yasuda, Yamamori and Fujimoto6 These findings suggest that the two disorders would be distinct diagnoses, with disorder-specific genetic factors related to clinical phenotypes. However, it remains unknown whether a genetic factor differentiating schizophrenia from bipolar disorder can explain the dissimilarities in cognitive functions and hippocampal volumes. Here, we explored whether the genetic factor differentiating component is genetically associated with psychiatric disorders, cognitive phenotypes and hippocampal volumes.

Method

To calculate genetic correlations attributable to genome-wide single nucleotide polymorphisms (SNPs) (polygenicity; many small genetic effects) between the genetic factor differentiating schizophrenia from bipolar disorder and psychiatric disorders, cognitive phenotypes and hippocampal volumes, we obtained GWAS summary statistics for the following: schizophrenia versus bipolar disorder,Reference Ruderfer, Ripke, McQuillin, Boocock, Stahl and Pavlides3 Psychiatric Genomics Consortium 2 (PGC2) for schizophrenia,Reference Ripke, Neale, Corvin, Walters, Farh and Holmans7 PGC2 for bipolar disorder,Reference Stahl, Breen, Forstner, McQuillin, Ripke and Trubetskoy8 major depression disorder (MDD), autism spectrum disorder (ASD), attention-deficit hyperactivity disorder (ADHD), general cognitive ability,Reference Davies, Lam, Harris, Trampush, Luciano and Hill12 childhood IQ, educational attainment and hippocampal volume.Reference Hibar, Stein, Renteria, Arias-Vasquez, Desrivieres and Jahanshad15 These data were extracted from the PGC (https://www.med.unc.edu/pgc/results-and-downloads), the Centre for Cognitive Ageing and Cognitive Epidemiology at the University of Edinburgh (http://www.ccace.ed.ac.uk/node/335), the Social Science Genetic Association Consortium (https://www.thessgac.org/data) and the Enhancing Neuroimaging Genetics through Meta-analysis (ENIGMA2; http://enigma.ini.usc.edu/research/download-enigma-gwas-results/) (Table 1).

Table 1 Demographic information of each genome-wide association study

a. Controls or pseudocontrols from family trio samples.

b. Schizophrenia.

c. Bipolar disorder.

Linkage disequilibrium score regression (LDSC) analysis can estimate the genetic SNP correlations (rg) from GWASs.Reference Ohi, Shimada, Kataoka, Yasuyama, Kawasaki and Shioiri5,Reference Bulik-Sullivan, Loh, Finucane, Ripke, Yang and Patterson16,Reference Ohi, Otowa, Shimada, Sasaki and Tanii17 For each GWAS, an LDSC was carried out by regressing the GWAS test statistics (χ2) onto each SNP's linkage disequilibrium score. Genetic correlations were calculated by LDSC. This study was approved by each local ethical committee of the relevant institutions. Informed consent was obtained from all participants and/or their families in each study cohort. The detailed information in each GWAS and LDSC analysis have been described previously, and are briefly summarised in the Supplementary Material available at https://doi.org/10.1192/bjo.2021.1086.

Results

As expected, the genetic component differentiating schizophrenia from bipolar disorder was positively correlated with the risk of schizophrenia (rg ± s.e. = 0.53 ± 0.03, P = 1.21 × 10−82), and negatively correlated with the risk of bipolar disorder (rg ± s.e. = −0.28 ± 0.04, P = 5.04 × 10−13) (Fig. 1(a)). Among other psychiatric disorders, there was positive genetic correlation between the differentiating genetic factor and ASD (rg ± s.e. = 0.16 ± 0.05, P = 2.90 × 10−3). There were no significant genetic correlations of the differentiating factor with MDD or ADHD (P > 0.05). The genetic factor differentiating schizophrenia from bipolar disorder was genetically negatively correlated with all examined cognitive phenotypes and hippocampal volumes (Fig. 1(a); general cognitive function (rg ± s.e. = −0.23 ± 0.04, P = 6.80 × 10−11), childhood IQ (rg ± s.e. = −0.21 ± 0.08, P = 7.30 × 10−3), educational attainment (rg ± s.e. = −0.13 ± 0.03, P = 2.66 × 10−5) and hippocampal volume (rg ± s.e. = −0.22 ± 0.10, P = 0.031)). As shown in genetic correlations across phenotypes (Fig. 1(b)), genetic correlations of the genetic differentiating factor with general cognitive function and hippocampal volume would be derived from genetic correlations of schizophrenia with these phenotypes. In contrast, genetic correlations of the genetic differentiating feature with childhood IQ and educational attainment would be derived from genetic correlations of bipolar disorder and/or ASD with these phenotypes.

Fig. 1 (a) Genetic correlations (rg) of genetic factor differentiating schizophrenia from bipolar disorder with psychiatric disorders, cognitive functions and hippocampal volumes. Error bars show s.e. of the rg. (b) Genetic correlations (rg) across genome-wide association study results. The colour scale represents the rg values. Genetic correlations were estimated with linkage disequilibrium score regression. *P < 0.05, **P < 0.01, ***P < 0.001.

Discussion

We revealed genetic overlaps of the genetic variants differentiating schizophrenia from bipolar disorder with risk of ASD, low general cognitive ability, low childhood IQ, low educational attainment and reduced hippocampal volumes. These genetic overlaps may be attributed to genetic risks for schizophrenia or bipolar disorder, or both. We further found that the genetic correlations of the genetic factor differentiating schizophrenia from bipolar disorder with low general cognitive ability and reduced hippocampal volumes are associated with risk of schizophrenia, and the genetic correlations of the genetic factor differentiating bipolar disorder from schizophrenia with high childhood IQ and educational attainment are associated with risks of bipolar disorder and/or ASD. The disorder-specific genetic liability could contribute to the clinical dissimilarities between schizophrenia and bipolar disorder. Current schizophrenia diagnoses may aggregate at least two subtypes:Reference Bansal, Mitjans, Burik, Linner, Okbay and Rietveld18 patients who resemble high intelligence and bipolar disorder (similarities), and patients who show cognitive impairments that are independent of bipolar disorder (dissimilarities). However, it remained unclear whether low intelligence causes schizophrenia or schizophrenia causes intelligence decline. Using summary data-based Mendelian randomisation,Reference Verbanck, Chen, Neale and Do19 we recently demonstrated that low intelligence was bidirectionally associated with a high risk of schizophrenia, whereas the schizophrenia-specific genetic factors might be mainly affected by impairment in premorbid intelligence.Reference Ohi, Takai, Kuramitsu, Sugiyama, Soda and Kitaichi20 Future study is required to reveal causal association between reduced hippocampal volumes and risk of schizophrenia.

Interestingly, there were no significant correlations between the genetic factor differentiating schizophrenia from bipolar disorder and MDD or ADHD. Comparing genetic correlations between schizophrenia and MDD with those between bipolar disorder and MDD, and genetic correlations between schizophrenia and ADHD with those between bipolar disorder and ADHD, both schizophrenia and bipolar disorder correlations with MDD and ADHD were similar.Reference Anttila, Bulik-Sullivan, Finucane, Walters, Bras and Duncan2 The absence of MDD or ADHD correlations with the differentiating factor might reflect similar degrees of these genetic correlations with schizophrenia and bipolar disorder.

Our findings suggest that cognitive impairments and reduced hippocampal volumes could genetically distinguish schizophrenia from bipolar disorder, and may be useful for improving diagnosis and treatment.

Supplementary material

Supplementary material is available online at https://doi.org/10.1192/bjo.2021.1086.

Data availability

The data that support the findings of this study are available from the corresponding author, K.O., on reasonable request.

Acknowledgements

We would like to thank all individuals who participated in this study.

Author contributions

K.O. supervised the entire project, collected the data, wrote the manuscript and was critically involved in the design, analysis and interpretation of the data. All authors were responsible for performing the literature review. All authors were intellectually contributed to data interpretation and approved the final manuscript for publication.

Funding

This work was supported by Grants-in-Aid for Scientific Research (C) (19K08081) from the Japan Society for the Promotion of Science (JSPS) and SENSHIN Medical Research Foundation.

Declaration of interest

None.

References

Ohi, K, Nishizawa, D, Shimada, T, Kataoka, Y, Hasegawa, J, Shioiri, T, et al. Polygenetic risk scores for major psychiatric disorders among schizophrenia patients, their first-degree relatives, and healthy participants. Int J Neuropsychopharmacol 2020; 23: 157–64.CrossRefGoogle ScholarPubMed
Anttila, V, Bulik-Sullivan, B, Finucane, HK, Walters, RK, Bras, J, Duncan, L, et al. Analysis of shared heritability in common disorders of the brain. Science 2018; 360(6395): eaap8757.Google ScholarPubMed
Ruderfer, D, Ripke, S, McQuillin, A, Boocock, J, Stahl, E, Pavlides, J, et al. Genomic dissection of bipolar disorder and schizophrenia, including 28 subphenotypes. Cell 2018; 173: 1705–15.e16.CrossRefGoogle Scholar
Weinberg, D, Lenroot, R, Jacomb, I, Allen, K, Bruggemann, J, Wells, R, et al. Cognitive subtypes of schizophrenia characterized by differential brain volumetric reductions and cognitive decline. JAMA Psychiatry 2016; 73: 1251–59.CrossRefGoogle ScholarPubMed
Ohi, K, Shimada, T, Kataoka, Y, Yasuyama, T, Kawasaki, Y, Shioiri, T, et al. Genetic correlations between subcortical brain volumes and psychiatric disorders. Br J Psychiatry 2020; 216: 280–3.CrossRefGoogle ScholarPubMed
Ohi, K, Sumiyoshi, C, Fujino, H, Yasuda, Y, Yamamori, H, Fujimoto, M, et al. Genetic overlap between general cognitive function and schizophrenia: a review of cognitive GWASs. Int J Mol Sci 2018; 19: 3822.CrossRefGoogle ScholarPubMed
Ripke, S, Neale, BM, Corvin, A, Walters, JT, Farh, KH, Holmans, PA, et al. Biological insights from 108 schizophrenia-associated genetic loci. Nature 2014; 511: 421–7.Google Scholar
Stahl, EA, Breen, G, Forstner, AJ, McQuillin, A, Ripke, S, Trubetskoy, V, et al. Genome-wide association study identifies 30 loci associated with bipolar disorder. Nat Genet 2019; 51: 793–803.CrossRefGoogle ScholarPubMed
Wray, NR, Ripke, S, Mattheisen, M, Trzaskowski, M, Byrne, EM, Abdellaoui, A, et al. Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression. Nat Genet 2018; 50(5): 668–81.CrossRefGoogle ScholarPubMed
Grove, J, Ripke, S, Als, TD, Mattheisen, M, Walters, RK, Won, H. Identification of common genetic risk variants for autism spectrum disorder. Nat Genet 2019; 51(3): 431–44.CrossRefGoogle ScholarPubMed
Demontis, D, Walters, RK, Martin, J, Mattheisen, M, Als, TD, Agerbo, E, et al. Discovery of the first genome-wide significant risk loci for attention deficit/hyperactivity disorder. Nat Genet 2019; 51: 63–75.CrossRefGoogle ScholarPubMed
Davies, G, Lam, M, Harris, SE, Trampush, JW, Luciano, M, Hill, WD, et al. Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function. Nat Commun 2018; 9: 2098.CrossRefGoogle ScholarPubMed
Benyamin, B, Pourcain, B, Davis, OS, Davies, G, Hansell, NK, Brion, M-JA, et al. Childhood intelligence is heritable, highly polygenic and associated with FNBP1L. Mol Psychiatry 2014; 19(2): 253–8.CrossRefGoogle ScholarPubMed
Lee, JJ, Wedow, R, Okbay, A, Kong, E, Maghzian, O, Zacher, M. Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals. Nat Genet 2018; 50(8): 1112–21.CrossRefGoogle ScholarPubMed
Hibar, DP, Stein, JL, Renteria, ME, Arias-Vasquez, A, Desrivieres, S, Jahanshad, N, et al. Common genetic variants influence human subcortical brain structures. Nature 2015; 520: 224–9.CrossRefGoogle ScholarPubMed
Bulik-Sullivan, BK, Loh, PR, Finucane, HK, Ripke, S, Yang, J, Patterson, N, et al. LD score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat Genet 2015; 47: 291–5.CrossRefGoogle ScholarPubMed
Ohi, K, Otowa, T, Shimada, M, Sasaki, T, Tanii, H. Shared genetic etiology between anxiety disorders and psychiatric and related intermediate phenotypes. Psychol Med 2020; 50: 692–704.CrossRefGoogle ScholarPubMed
Bansal, V, Mitjans, M, Burik, CAP, Linner, RK, Okbay, A, Rietveld, CA, et al. Genome-wide association study results for educational attainment aid in identifying genetic heterogeneity of schizophrenia. Nat Commun 2018; 9: 3078.CrossRefGoogle ScholarPubMed
Verbanck, M, Chen, CY, Neale, B, Do, R. Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases. Nat Genet 2018; 50: 693–8.CrossRefGoogle ScholarPubMed
Ohi, K, Takai, K, Kuramitsu, A, Sugiyama, S, Soda, M, Kitaichi, K, et al. Causal associations of intelligence with schizophrenia and bipolar disorder: a Mendelian randomization analysis. Eur Psychiatry 2021; 64: e61.CrossRefGoogle ScholarPubMed
Figure 0

Table 1 Demographic information of each genome-wide association study

Figure 1

Fig. 1 (a) Genetic correlations (rg) of genetic factor differentiating schizophrenia from bipolar disorder with psychiatric disorders, cognitive functions and hippocampal volumes. Error bars show s.e. of the rg. (b) Genetic correlations (rg) across genome-wide association study results. The colour scale represents the rg values. Genetic correlations were estimated with linkage disequilibrium score regression. *P < 0.05, **P < 0.01, ***P < 0.001.

Supplementary material: File

Ohi et al. supplementary material

Ohi et al. supplementary material

Download Ohi et al. supplementary material(File)
File 243.4 KB
Submit a response

eLetters

No eLetters have been published for this article.