Genome-Transcriptome-Functional Connectivity-Cognition Link Differentiates Schizophrenia From Bipolar Disorder

Jiayu Chen¹, Zening Fu¹, Juan R Bustillo^{2

3}, Nora I Perrone-Bizzozero^{2

3}, Dongdong Lin¹, Jose Canive³, Godfrey D Pearlson^{4

5}, Julia M Stephen⁶, Andrew R Mayer⁶, Steven G Potkin⁷, Theo G M van Erp⁸, Peter Kochunov⁹, L Elliot Hong⁹, Bhim M Adhikari⁹, Ole A Andreassen^{10

11}, Ingrid Agartz^{10

11

12}, Lars T Westlye^{10

13}, Jing Sui^{1

14}, Yuhui Du^{1

15}, Fabio Macciardi⁷, Faith M Hanlon⁶, Rex E Jung¹⁶, Jessica A Turner¹⁷, Jingyu Liu^{1

18}, Vince D Calhoun^{1

17}

Affiliations

¹ Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA.
² Department of Neurosciences, University of New Mexico School of Medicine, Albuquerque, NM, USA.
³ Department of Psychiatry and Behavioral Sciences, University of New Mexico School of Medicine, Albuquerque, NM, USA.
⁴ Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT, USA.
⁵ Department of Psychiatry and Neuroscience, Yale University, New Haven, CT, USA.
⁶ The Mind Research Network, Albuquerque, NM, USA.
⁷ Department of Psychiatry and Human Behavior, School of Medicine, University of California, Irvine, CA, USA.
⁸ Department of Psychiatry and Human Behavior, Clinical Translational Neuroscience Laboratory, School of Medicine, University of California, Irvine, CA, USA.
⁹ Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, USA.
¹⁰ Division of Mental Health and Addiction, Norwegian Centre for Mental Disorders Research (NORMENT), Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
¹¹ Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway.
¹² Department of Clinical Neuroscience, Centre for Psychiatric Research, Karolinska Institutet, Stockholm, Sweden.
¹³ Department of Psychology, University of Oslo, Oslo, Norway.
¹⁴ Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
¹⁵ School of Computer and Information Technology, Shanxi University, Taiyuan, China.
¹⁶ Department of Psychology, University of New Mexico, Albuquerque, NM, USA.
¹⁷ Psychology Department and Neuroscience Institute, Georgia State University, Atlanta, GA, USA.
¹⁸ Department of Computer Science, Georgia State University, Atlanta, GA, USA.

PMID: 35988022
PMCID: PMC9673262
DOI: 10.1093/schbul/sbac088

Genome-Transcriptome-Functional Connectivity-Cognition Link Differentiates Schizophrenia From Bipolar Disorder

Jiayu Chen et al. Schizophr Bull. 2022.

. 2022 Nov 18;48(6):1306-1317.

doi: 10.1093/schbul/sbac088.

Authors

Affiliations

¹ Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA.
² Department of Neurosciences, University of New Mexico School of Medicine, Albuquerque, NM, USA.
³ Department of Psychiatry and Behavioral Sciences, University of New Mexico School of Medicine, Albuquerque, NM, USA.
⁴ Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT, USA.
⁵ Department of Psychiatry and Neuroscience, Yale University, New Haven, CT, USA.
⁶ The Mind Research Network, Albuquerque, NM, USA.
⁷ Department of Psychiatry and Human Behavior, School of Medicine, University of California, Irvine, CA, USA.
⁸ Department of Psychiatry and Human Behavior, Clinical Translational Neuroscience Laboratory, School of Medicine, University of California, Irvine, CA, USA.
⁹ Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, USA.
¹⁰ Division of Mental Health and Addiction, Norwegian Centre for Mental Disorders Research (NORMENT), Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
¹¹ Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway.
¹² Department of Clinical Neuroscience, Centre for Psychiatric Research, Karolinska Institutet, Stockholm, Sweden.
¹³ Department of Psychology, University of Oslo, Oslo, Norway.
¹⁴ Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
¹⁵ School of Computer and Information Technology, Shanxi University, Taiyuan, China.
¹⁶ Department of Psychology, University of New Mexico, Albuquerque, NM, USA.
¹⁷ Psychology Department and Neuroscience Institute, Georgia State University, Atlanta, GA, USA.
¹⁸ Department of Computer Science, Georgia State University, Atlanta, GA, USA.

PMID: 35988022
PMCID: PMC9673262
DOI: 10.1093/schbul/sbac088

Abstract

Background and hypothesis: Schizophrenia (SZ) and bipolar disorder (BD) share genetic risk factors, yet patients display differential levels of cognitive impairment. We hypothesized a genome-transcriptome-functional connectivity (frontoparietal)-cognition pathway linked to SZ-versus-BD differences, and conducted a multiscale study to delineate this pathway.

Study designs: Large genome-wide studies provided single nucleotide polymorphisms (SNPs) conferring more risk for SZ than BD, and we identified their regulated genes, namely SZ-biased SNPs and genes. We then (a) computed the polygenic risk score for SZ (PRSSZ) of SZ-biased SNPs and examined its associations with imaging-based frontoparietal functional connectivity (FC) and cognitive performances; (b) examined the spatial correlation between ex vivo postmortem expressions of SZ-biased genes and in vivo, SZ-related FC disruptions across frontoparietal regions; (c) investigated SZ-versus-BD differences in frontoparietal FC; and (d) assessed the associations of frontoparietal FC with cognitive performances.

Study results: PRSSZ of SZ-biased SNPs was significantly associated with frontoparietal FC and working memory test scores. SZ-biased genes' expressions significantly correlated with SZ-versus-BD differences in FC across frontoparietal regions. SZ patients showed more reductions in frontoparietal FC than BD patients compared to controls. Frontoparietal FC was significantly associated with test scores of multiple cognitive domains including working memory, and with the composite scores of all cognitive domains.

Conclusions: Collectively, these multiscale findings support the hypothesis that SZ-biased genetic risk, through transcriptome regulation, is linked to frontoparietal dysconnectivity, which in turn contributes to differential cognitive deficits in SZ-versus BD, suggesting that potential biomarkers for more precise patient stratification and treatment.

Keywords: SNP; functional connectivity; gene expression; polygenic risk score; working memory.

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Figures

**Fig. 1.**
Method overview for integrating information from genetic, transcriptomic, neuroimaging, and cognitive domains. A step-by-step overview visually depicts the process of linking SZ-biased genetic risk to cognitive deficits through transcriptomics and neuroimaging. The seven tests are coded sequentially. A. Derive SZ-biased SNPs and genes. B. Resting fMRI functional connectivity (FC) analysis based on the AAL atlas, where the 4 AHBA annotations map to six AAL regions. C. Association between SZ-biased SNPs and frontoparietal FC. D. Association between SZ-biased SNPs and neurocognitive performance. E. Imaging transcriptomic association based on the Schaefer atlas. F. Association of frontoparietal FC with neurocognitive performance.

**Fig. 2.**
Group differences in functional connectivity. A. Mapping between AHBA frontoparietal brain tissue samples and AAL frontoparietal ROIs. B. Bar plots of averaged frontoparietal functional connectivity (9 pairs of the left hemisphere) within individual diagnosis groups of Cohort 1 and Cohort 2, respectively, where q reflects the FDR corrected significance level obtained from the meta-analysis (Stouffer’s z-test) of 2 cohorts, thresholded at 0.05 for statistical significance.

**Fig. 3.**
Frontoparietal imaging transcriptomic associations and associations between frontoparietal connectivity and neurocognitive performance. A. Schaefer ROIs mapped from the AHBA frontoparietal tissue samples. B. Frontoparietal imaging transcriptomic associations between SZ-biased gene expression and functional dysconnectivity of SZ-BD, SZ-HC, and BD-HC, respectively. Each dot represents one of the 32 ROIs in the scatter plot. C. Frontoparietal functional connectivity associations with neurocognitive performance.

See this image and copyright information in PMC

References

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Genome-Transcriptome-Functional Connectivity-Cognition Link Differentiates Schizophrenia From Bipolar Disorder

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Genome-Transcriptome-Functional Connectivity-Cognition Link Differentiates Schizophrenia From Bipolar Disorder

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