Associated Genetics and Connectomic Circuitry in Schizophrenia and Bipolar Disorder

Yongbin Wei; Siemon C. de Lange; Jeanne E. Savage; Elleke Tissink; Ting Qi; Jonathan Repple; Marius Gruber; Tilo Kircher; Udo Dannlowski; Danielle Posthuma; Martijn P. van den Heuvel

doi:10.1016/j.biopsych.2022.11.006

Associated Genetics and Connectomic Circuitry in Schizophrenia and Bipolar Disorder

Yongbin Wei^*, Siemon C. de Lange, Jeanne E. Savage, Elleke Tissink, Ting Qi, Jonathan Repple, Marius Gruber, Tilo Kircher, Udo Dannlowski, Danielle Posthuma, Martijn P. van den Heuvel^*

^*Corresponding author for this work

Research output: Contribution to Journal › Article › Academic › peer-review

Abstract

BACKGROUND: Schizophrenia (SCZ) and bipolar disorder (BD) are severe psychiatric conditions that can involve symptoms of psychosis and cognitive dysfunction. The 2 conditions share symptomatology and genetic etiology and are regularly hypothesized to share underlying neuropathology. Here, we examined how genetic liability to SCZ and BD shapes normative variations in brain connectivity.

METHODS: We examined the effect of the combined genetic liability for SCZ and BD on brain connectivity from two perspectives. First, we examined the association between polygenic scores for SCZ and BD for 19,778 healthy subjects from the UK Biobank and individual variation in brain structural connectivity reconstructed by means of diffusion weighted imaging data. Second, we conducted genome-wide association studies using genotypic and imaging data from the UK Biobank, taking SCZ-/BD-involved brain circuits as phenotypes of interest.

RESULTS: Our findings showed brain circuits of superior parietal and posterior cingulate regions to be associated with polygenic liability for SCZ and BD, circuitry that overlaps with brain networks involved in disease conditions (r = 0.239, p < .001). Genome-wide association study analysis showed 9 significant genomic loci associated with SCZ-involved circuits and 14 loci associated with BD-involved circuits. Genes related to SCZ-/BD-involved circuits were significantly enriched in gene sets previously reported in genome-wide association studies for SCZ and BD.

CONCLUSIONS: Our findings suggest that polygenic liability of SCZ and BD is associated with normative individual variation in brain circuitry.

Original language	English
Pages (from-to)	174-183
Number of pages	10
Journal	Biological psychiatry
Volume	94
Issue number	2
Early online date	9 Nov 2022
DOIs	https://doi.org/10.1016/j.biopsych.2022.11.006
Publication status	Published - 15 Jul 2023

Bibliographical note

Funding Information:
This study has received fundings from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (Grant agreement ERC-COG No. 101001062 [to MPvdH] and Grant agreement ERC-ADG No. 834057 [to DP]), the National Natural Science Foundation of China (Grant No. 82202264 [to YW]), the Netherlands Organization for Scientific Research (VIDI Grant No. 452-16-015 [to MPvdH], ALW open Grant No. ALWOP.179 [to MPvdH], Gravitation project BRAINSCAPES: A Road map from Neurogenetics to Neurobiology, Grant No. 024.004.012 [to DP and MPvdH]), and the ZonMw Open Competition project REMOVE (Grant No. 09120011910032 [to SCdL]). The genetic analyses were carried out on the Genetic Cluster Computer, which is financed by the Netherlands Scientific Organization (NWO: 480-05-003), Vrije Universiteit, Amsterdam, the Netherlands, and the Dutch Brain Foundation, and is hosted by the Dutch National Computing and Networking Services SURFSARA.

Funding Information:
This study has received fundings from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (Grant agreement ERC-COG No. 101001062 [to MPvdH] and Grant agreement ERC-ADG No. 834057 [to DP]), the National Natural Science Foundation of China (Grant No. 82202264 [to YW]), the Netherlands Organization for Scientific Research (VIDI Grant No. 452-16-015 [to MPvdH], ALW open Grant No. ALWOP.179 [to MPvdH], Gravitation project BRAINSCAPES: A Road map from Neurogenetics to Neurobiology, Grant No. 024.004.012 [to DP and MPvdH]), and the ZonMw Open Competition project REMOVE (Grant No. 09120011910032 [to SCdL]). The genetic analyses were carried out on the Genetic Cluster Computer, which is financed by the Netherlands Scientific Organization (NWO: 480-05-003), Vrije Universiteit, Amsterdam, the Netherlands, and the Dutch Brain Foundation, and is hosted by the Dutch National Computing and Networking Services SURFSARA. YW performed the analyses. MPvdH and YW conceived the idea of this study. MPvdH supervised this study. SCdL and ET preprocessed MRI data. JES prepared genetic data and genetic analysis pipeline. TQ performed the mediation analysis. JR and UD provided MACS BD data. DP supervised the genetic analysis pipeline. YW wrote the paper with contributions from all co-authors. Codes are available from the corresponding author on reasonable request. Data visualization uses the Gramm toolbox (74) and the Simple Brain Plot (75) implemented in MATLAB (version R2021a; The MathWorks, Inc.). The UKB genotype data and MRI data that support the findings of this study are available in the UKB (accessed under application 16406; https://www.ukbiobank.ac.uk). The Centers for Biomedical Research Excellence dataset that supports the findings of this study is available at http://schizconnect.org. The Marburg-Münster Affective Disorders Cohort Study bipolar disorder data that support the findings of this study are available from the corresponding author on reasonable request. The authors report no biomedical financial interests or potential conflicts of interest.

Publisher Copyright:
© 2022 Society of Biological Psychiatry

Keywords

Connectivity
Genetics
GWAS
Imaging
Polygenic score

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10.1016/j.biopsych.2022.11.006

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@article{923639e3220745a4b1fc88e9ece1848c,

title = "Associated Genetics and Connectomic Circuitry in Schizophrenia and Bipolar Disorder",

abstract = "BACKGROUND: Schizophrenia (SCZ) and bipolar disorder (BD) are severe psychiatric conditions that can involve symptoms of psychosis and cognitive dysfunction. The 2 conditions share symptomatology and genetic etiology and are regularly hypothesized to share underlying neuropathology. Here, we examined how genetic liability to SCZ and BD shapes normative variations in brain connectivity.METHODS: We examined the effect of the combined genetic liability for SCZ and BD on brain connectivity from two perspectives. First, we examined the association between polygenic scores for SCZ and BD for 19,778 healthy subjects from the UK Biobank and individual variation in brain structural connectivity reconstructed by means of diffusion weighted imaging data. Second, we conducted genome-wide association studies using genotypic and imaging data from the UK Biobank, taking SCZ-/BD-involved brain circuits as phenotypes of interest.RESULTS: Our findings showed brain circuits of superior parietal and posterior cingulate regions to be associated with polygenic liability for SCZ and BD, circuitry that overlaps with brain networks involved in disease conditions (r = 0.239, p < .001). Genome-wide association study analysis showed 9 significant genomic loci associated with SCZ-involved circuits and 14 loci associated with BD-involved circuits. Genes related to SCZ-/BD-involved circuits were significantly enriched in gene sets previously reported in genome-wide association studies for SCZ and BD.CONCLUSIONS: Our findings suggest that polygenic liability of SCZ and BD is associated with normative individual variation in brain circuitry.",

keywords = "Connectivity, Genetics, GWAS, Imaging, Polygenic score",

author = "Yongbin Wei and {de Lange}, {Siemon C.} and Savage, {Jeanne E.} and Elleke Tissink and Ting Qi and Jonathan Repple and Marius Gruber and Tilo Kircher and Udo Dannlowski and Danielle Posthuma and {van den Heuvel}, {Martijn P.}",

note = "Funding Information: This study has received fundings from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (Grant agreement ERC-COG No. 101001062 [to MPvdH] and Grant agreement ERC-ADG No. 834057 [to DP]), the National Natural Science Foundation of China (Grant No. 82202264 [to YW]), the Netherlands Organization for Scientific Research (VIDI Grant No. 452-16-015 [to MPvdH], ALW open Grant No. ALWOP.179 [to MPvdH], Gravitation project BRAINSCAPES: A Road map from Neurogenetics to Neurobiology, Grant No. 024.004.012 [to DP and MPvdH]), and the ZonMw Open Competition project REMOVE (Grant No. 09120011910032 [to SCdL]). The genetic analyses were carried out on the Genetic Cluster Computer, which is financed by the Netherlands Scientific Organization (NWO: 480-05-003), Vrije Universiteit, Amsterdam, the Netherlands, and the Dutch Brain Foundation, and is hosted by the Dutch National Computing and Networking Services SURFSARA. Funding Information: This study has received fundings from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (Grant agreement ERC-COG No. 101001062 [to MPvdH] and Grant agreement ERC-ADG No. 834057 [to DP]), the National Natural Science Foundation of China (Grant No. 82202264 [to YW]), the Netherlands Organization for Scientific Research (VIDI Grant No. 452-16-015 [to MPvdH], ALW open Grant No. ALWOP.179 [to MPvdH], Gravitation project BRAINSCAPES: A Road map from Neurogenetics to Neurobiology, Grant No. 024.004.012 [to DP and MPvdH]), and the ZonMw Open Competition project REMOVE (Grant No. 09120011910032 [to SCdL]). The genetic analyses were carried out on the Genetic Cluster Computer, which is financed by the Netherlands Scientific Organization (NWO: 480-05-003), Vrije Universiteit, Amsterdam, the Netherlands, and the Dutch Brain Foundation, and is hosted by the Dutch National Computing and Networking Services SURFSARA. YW performed the analyses. MPvdH and YW conceived the idea of this study. MPvdH supervised this study. SCdL and ET preprocessed MRI data. JES prepared genetic data and genetic analysis pipeline. TQ performed the mediation analysis. JR and UD provided MACS BD data. DP supervised the genetic analysis pipeline. YW wrote the paper with contributions from all co-authors. Codes are available from the corresponding author on reasonable request. Data visualization uses the Gramm toolbox (74) and the Simple Brain Plot (75) implemented in MATLAB (version R2021a; The MathWorks, Inc.). The UKB genotype data and MRI data that support the findings of this study are available in the UKB (accessed under application 16406; https://www.ukbiobank.ac.uk). The Centers for Biomedical Research Excellence dataset that supports the findings of this study is available at http://schizconnect.org. The Marburg-M{\"u}nster Affective Disorders Cohort Study bipolar disorder data that support the findings of this study are available from the corresponding author on reasonable request. The authors report no biomedical financial interests or potential conflicts of interest. Publisher Copyright: {\textcopyright} 2022 Society of Biological Psychiatry",

year = "2023",

month = jul,

day = "15",

doi = "10.1016/j.biopsych.2022.11.006",

language = "English",

volume = "94",

pages = "174--183",

journal = "Biological psychiatry",

issn = "0006-3223",

publisher = "Elsevier USA",

number = "2",

}

TY - JOUR

T1 - Associated Genetics and Connectomic Circuitry in Schizophrenia and Bipolar Disorder

AU - Wei, Yongbin

AU - de Lange, Siemon C.

AU - Savage, Jeanne E.

AU - Tissink, Elleke

AU - Qi, Ting

AU - Repple, Jonathan

AU - Gruber, Marius

AU - Kircher, Tilo

AU - Dannlowski, Udo

AU - Posthuma, Danielle

AU - van den Heuvel, Martijn P.

N1 - Funding Information: This study has received fundings from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (Grant agreement ERC-COG No. 101001062 [to MPvdH] and Grant agreement ERC-ADG No. 834057 [to DP]), the National Natural Science Foundation of China (Grant No. 82202264 [to YW]), the Netherlands Organization for Scientific Research (VIDI Grant No. 452-16-015 [to MPvdH], ALW open Grant No. ALWOP.179 [to MPvdH], Gravitation project BRAINSCAPES: A Road map from Neurogenetics to Neurobiology, Grant No. 024.004.012 [to DP and MPvdH]), and the ZonMw Open Competition project REMOVE (Grant No. 09120011910032 [to SCdL]). The genetic analyses were carried out on the Genetic Cluster Computer, which is financed by the Netherlands Scientific Organization (NWO: 480-05-003), Vrije Universiteit, Amsterdam, the Netherlands, and the Dutch Brain Foundation, and is hosted by the Dutch National Computing and Networking Services SURFSARA. Funding Information: This study has received fundings from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (Grant agreement ERC-COG No. 101001062 [to MPvdH] and Grant agreement ERC-ADG No. 834057 [to DP]), the National Natural Science Foundation of China (Grant No. 82202264 [to YW]), the Netherlands Organization for Scientific Research (VIDI Grant No. 452-16-015 [to MPvdH], ALW open Grant No. ALWOP.179 [to MPvdH], Gravitation project BRAINSCAPES: A Road map from Neurogenetics to Neurobiology, Grant No. 024.004.012 [to DP and MPvdH]), and the ZonMw Open Competition project REMOVE (Grant No. 09120011910032 [to SCdL]). The genetic analyses were carried out on the Genetic Cluster Computer, which is financed by the Netherlands Scientific Organization (NWO: 480-05-003), Vrije Universiteit, Amsterdam, the Netherlands, and the Dutch Brain Foundation, and is hosted by the Dutch National Computing and Networking Services SURFSARA. YW performed the analyses. MPvdH and YW conceived the idea of this study. MPvdH supervised this study. SCdL and ET preprocessed MRI data. JES prepared genetic data and genetic analysis pipeline. TQ performed the mediation analysis. JR and UD provided MACS BD data. DP supervised the genetic analysis pipeline. YW wrote the paper with contributions from all co-authors. Codes are available from the corresponding author on reasonable request. Data visualization uses the Gramm toolbox (74) and the Simple Brain Plot (75) implemented in MATLAB (version R2021a; The MathWorks, Inc.). The UKB genotype data and MRI data that support the findings of this study are available in the UKB (accessed under application 16406; https://www.ukbiobank.ac.uk). The Centers for Biomedical Research Excellence dataset that supports the findings of this study is available at http://schizconnect.org. The Marburg-Münster Affective Disorders Cohort Study bipolar disorder data that support the findings of this study are available from the corresponding author on reasonable request. The authors report no biomedical financial interests or potential conflicts of interest. Publisher Copyright: © 2022 Society of Biological Psychiatry

PY - 2023/7/15

Y1 - 2023/7/15

N2 - BACKGROUND: Schizophrenia (SCZ) and bipolar disorder (BD) are severe psychiatric conditions that can involve symptoms of psychosis and cognitive dysfunction. The 2 conditions share symptomatology and genetic etiology and are regularly hypothesized to share underlying neuropathology. Here, we examined how genetic liability to SCZ and BD shapes normative variations in brain connectivity.METHODS: We examined the effect of the combined genetic liability for SCZ and BD on brain connectivity from two perspectives. First, we examined the association between polygenic scores for SCZ and BD for 19,778 healthy subjects from the UK Biobank and individual variation in brain structural connectivity reconstructed by means of diffusion weighted imaging data. Second, we conducted genome-wide association studies using genotypic and imaging data from the UK Biobank, taking SCZ-/BD-involved brain circuits as phenotypes of interest.RESULTS: Our findings showed brain circuits of superior parietal and posterior cingulate regions to be associated with polygenic liability for SCZ and BD, circuitry that overlaps with brain networks involved in disease conditions (r = 0.239, p < .001). Genome-wide association study analysis showed 9 significant genomic loci associated with SCZ-involved circuits and 14 loci associated with BD-involved circuits. Genes related to SCZ-/BD-involved circuits were significantly enriched in gene sets previously reported in genome-wide association studies for SCZ and BD.CONCLUSIONS: Our findings suggest that polygenic liability of SCZ and BD is associated with normative individual variation in brain circuitry.

AB - BACKGROUND: Schizophrenia (SCZ) and bipolar disorder (BD) are severe psychiatric conditions that can involve symptoms of psychosis and cognitive dysfunction. The 2 conditions share symptomatology and genetic etiology and are regularly hypothesized to share underlying neuropathology. Here, we examined how genetic liability to SCZ and BD shapes normative variations in brain connectivity.METHODS: We examined the effect of the combined genetic liability for SCZ and BD on brain connectivity from two perspectives. First, we examined the association between polygenic scores for SCZ and BD for 19,778 healthy subjects from the UK Biobank and individual variation in brain structural connectivity reconstructed by means of diffusion weighted imaging data. Second, we conducted genome-wide association studies using genotypic and imaging data from the UK Biobank, taking SCZ-/BD-involved brain circuits as phenotypes of interest.RESULTS: Our findings showed brain circuits of superior parietal and posterior cingulate regions to be associated with polygenic liability for SCZ and BD, circuitry that overlaps with brain networks involved in disease conditions (r = 0.239, p < .001). Genome-wide association study analysis showed 9 significant genomic loci associated with SCZ-involved circuits and 14 loci associated with BD-involved circuits. Genes related to SCZ-/BD-involved circuits were significantly enriched in gene sets previously reported in genome-wide association studies for SCZ and BD.CONCLUSIONS: Our findings suggest that polygenic liability of SCZ and BD is associated with normative individual variation in brain circuitry.

KW - Connectivity

KW - Genetics

KW - GWAS

KW - Imaging

KW - Polygenic score

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DO - 10.1016/j.biopsych.2022.11.006

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SN - 0006-3223

VL - 94

SP - 174

EP - 183

JO - Biological psychiatry

JF - Biological psychiatry

IS - 2

ER -

Associated Genetics and Connectomic Circuitry in Schizophrenia and Bipolar Disorder

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