Genetic Association Between Schizophrenia and Cortical Brain Surface Area and Thickness

Cheng, Weiqiu; Frei, Oleksandr; Meer, Dennis van der; Wang, Yunpeng; O’Connell, Kevin; Chu, Yunhan; Bahrami, Shahram; Shadrin, Alexey; Alnæs, Dag; Hindley, Guy; Lin, Aihua; Karadag, Naz; Fan, Chun-Chieh; Kaufmann, Tobias; Molden, Espen; Dale, Anders M.; Djurovic, Srdjan; Smeland, Olav B.; Andreassen, Ole A.

doi:10.1001/jamapsychiatry.2021.1435

Cited by 61 publications

(66 citation statements)

References 80 publications

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“…The idea behind this is that in the presence of cross-trait enrichment, a variant with strong associations with both traits is more likely to represent a true association. This approach has been shown to allow for discovery of many novel variants (13), which have been found to replicate well (14,15). Further, owing to the distributed effects of genetic variants involved in brain morphology, the data can be analyzed more powerfully through a multivariate approach, capitalizing on the shared genetic signal across regional brain measures by considering the brain as an integrated unit (16), thereby providing greater statistical power and better alignment with the underlying biology than univariate approaches.…”

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confidence: 99%

Boosting Schizophrenia Genetics by Utilizing Genetic Overlap With Brain Morphology

Meer

Shadrin

O’Connell

et al. 2022

Biological Psychiatry

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confidence: 99%

Boosting Schizophrenia Genetics by Utilizing Genetic Overlap With Brain Morphology

Meer

Shadrin

O’Connell

et al. 2022

Biological Psychiatry

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“…This overlap is consistent with prior findings that have directly tested genetic overlap in risk for SZ and brain structure. Direct assessments of pleiotropy for disorders and brain structure have found evidence for the shared genetic basis of SZ and regional cortical thickness and surface area 91,92 and are starting to examine such contributions based on cross disorder data. 92 However, it is unknown whether group-level multivariate patterns of brain abnormalities are informative with regard to identifying individuals or clusters of individuals who may be more similar, either genetically, with regard to symptom profiles, treatment, or prognosis.…”

Section: Discussionmentioning

confidence: 99%

Cross disorder comparisons of brain structure in schizophrenia, bipolar disorder, major depressive disorder, and 22q11.2 deletion syndrome: A review of ENIGMA findings

Cheon

Bearden

Sun

et al. 2022

Psychiatry Clin Neurosci

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This review compares the main brain abnormalities in schizophrenia (SZ), bipolar disorder (BD), major depressive disorder (MDD), and 22q11.2 Deletion Syndrome (22q11DS) determined by ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) consortium investigations. We obtained ranked effect sizes for subcortical volumes, regional cortical thickness, cortical surface area, and diffusion tensor imaging abnormalities, comparing each of these disorders relative to healthy controls. In addition, the studies report on significant associations between brain imaging metrics and disorder-related factors such as symptom severity and treatments. Visual comparison of effect size profiles shows that effect sizes are generally in the same direction and scale in severity with the disorders (in the order SZ > BD > MDD). The effect sizes for 22q11DS, a rare genetic syndrome that increases the risk for psychiatric disorders, appear to be much larger than for either of the complex psychiatric disorders. This is consistent with the idea of generally larger effects on the brain of rare compared to common genetic variants. Cortical thickness and surface area effect sizes for 22q11DS with psychosis compared to 22q11DS without psychosis are more similar to those of SZ and BD than those of MDD; a pattern not observed for subcortical brain structures and fractional anisotropy effect sizes. The observed similarities in effect size profiles for cortical measures across the psychiatric disorders mimic those observed for shared genetic variance between these disorders reported based on family and genetic studies and are consistent with shared genetic risk for SZ and BD and structural brain phenotypes.

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“…The UK Biobank was approved by the National Health Service National Research Ethics Service (ref. 11/NW/0382). We previously used data from the online follow-up questionnaire on mental health to define 13 phenotypically independent profiles relevant for mental health 24 .…”

Section: Sample and Exclusion Criteriamentioning

confidence: 99%

“…Interactions between various brain phenotypes and genetics have been reported across structural 11,12 and functional 2,7,10 imaging modalities.…”

Section: Introductionmentioning

confidence: 99%

“…Both imaging and genetics studies have shown numerous but small associations between brain phenotypes, psychiatric disorders, and genetics, such as schizophrenia (SCZ) 1– 3 , bipolar disorder (BIP) 4,5 , major depressive disorder (MDD) 6,7 , and anxiety disorder (ANX) 8–10 . Interactions between various brain phenotypes and genetics have been reported across structural 11,12 and functional 2,7,10 imaging modalities.…”

Section: Introductionmentioning

confidence: 99%

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Shared genetic architecture between mental health and the brain functional connectome in the UK Biobank

Roelfs

Frei

Meer

et al. 2022

Preprint

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Psychiatric disorders are complex clinical conditions with large heterogeneity and overlap in symptoms, genetic liability and brain imaging abnormalities. Building on a dimensional conceptualization of mental health, previous studies have reported genetic overlap between psychiatric disorders and population-level mental health, and between psychiatric disorders and brain functional connectivity. Here, in 30.701 participants aged 45-82 from the UK Biobank we map the genetic associations between self-reported mental health and resting-state fMRI-based measures of brain network function. Multivariate Omnibus Statistical Test revealed 10 genetic loci associated with population-level mental symptoms. Next, conjunctional FDR identified 23 shared genetic variants between these symptom profiles and fMRI-based brain network measures. Functional annotation implicated genes involved in brain structure and function, in particular synaptic processes. These findings provide further genetic evidence of an association between brain function and mental health traits in the population.

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Genetic Association Between Schizophrenia and Cortical Brain Surface Area and Thickness

Cited by 61 publications

References 80 publications

Boosting Schizophrenia Genetics by Utilizing Genetic Overlap With Brain Morphology

Boosting Schizophrenia Genetics by Utilizing Genetic Overlap With Brain Morphology

Cross disorder comparisons of brain structure in schizophrenia, bipolar disorder, major depressive disorder, and 22q11.2 deletion syndrome: A review of ENIGMA findings

Shared genetic architecture between mental health and the brain functional connectome in the UK Biobank

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