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  • Schwarz, E, et al. (författare)
  • Reproducible grey matter patterns index a multivariate, global alteration of brain structure in schizophrenia and bipolar disorder
  • 2019
  • Ingår i: Translational psychiatry. - : Springer Science and Business Media LLC. - 2158-3188. ; 9:1, s. 12-
  • Tidskriftsartikel (refereegranskat)abstract
    • Schizophrenia is a severe mental disorder characterized by numerous subtle changes in brain structure and function. Machine learning allows exploring the utility of combining structural and functional brain magnetic resonance imaging (MRI) measures for diagnostic application, but this approach has been hampered by sample size limitations and lack of differential diagnostic data. Here, we performed a multi-site machine learning analysis to explore brain structural patterns of T1 MRI data in 2668 individuals with schizophrenia, bipolar disorder or attention-deficit/ hyperactivity disorder, and healthy controls. We found reproducible changes of structural parameters in schizophrenia that yielded a classification accuracy of up to 76% and provided discrimination from ADHD, through it lacked specificity against bipolar disorder. The observed changes largely indexed distributed grey matter alterations that could be represented through a combination of several global brain-structural parameters. This multi-site machine learning study identified a brain-structural signature that could reproducibly differentiate schizophrenia patients from controls, but lacked specificity against bipolar disorder. While this currently limits the clinical utility of the identified signature, the present study highlights that the underlying alterations index substantial global grey matter changes in psychotic disorders, reflecting the biological similarity of these conditions, and provide a roadmap for future exploration of brain structural alterations in psychiatric patients.
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  • Stokowy, T, et al. (författare)
  • Genetic variation in 117 myelination-related genes in schizophrenia: Replication of association to lipid biosynthesis genes
  • 2018
  • Ingår i: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 8:1, s. 6915-
  • Tidskriftsartikel (refereegranskat)abstract
    • Schizophrenia is a serious psychotic disorder with high heritability. Several common genetic variants, rare copy number variants and ultra-rare gene-disrupting mutations have been linked to disease susceptibility, but there is still a large gap between the estimated and explained heritability. Since several studies have indicated brain myelination abnormalities in schizophrenia, we aimed to examine whether variants in myelination-related genes could be associated with risk for schizophrenia. We established a set of 117 myelination genes by database searches and manual curation. We used a combination of GWAS (SCZ_N = 35,476; CTRL_N = 46,839), exome chip (SCZ_N = 269; CTRL_N = 336) and exome sequencing data (SCZ_N = 2,527; CTRL_N = 2,536) from schizophrenia cases and healthy controls to examine common and rare variants. We found that a subset of lipid-related genes was nominally associated with schizophrenia (p = 0.037), but this signal did not survive multiple testing correction (FWER = 0.16) and was mainly driven by the SREBF1 and SREBF2 genes that have already been linked to schizophrenia. Further analysis demonstrated that the lowest nominal p-values were p = 0.0018 for a single common variant (rs8539) and p = 0.012 for burden of rare variants (LRP1 gene), but none of them survived multiple testing correction. Our findings suggest that variation in myelination-related genes is not a major risk factor for schizophrenia.
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  • Thompson, PM, et al. (författare)
  • ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries
  • 2020
  • Ingår i: Translational psychiatry. - : Springer Science and Business Media LLC. - 2158-3188. ; 10:1, s. 100-
  • Tidskriftsartikel (refereegranskat)abstract
    • This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of “big data” (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA’s activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors.
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  • van der Meer, D, et al. (författare)
  • Brain scans from 21,297 individuals reveal the genetic architecture of hippocampal subfield volumes
  • 2020
  • Ingår i: Molecular psychiatry. - : Springer Science and Business Media LLC. - 1476-5578 .- 1359-4184. ; 25:11, s. 3053-3065
  • Tidskriftsartikel (refereegranskat)abstract
    • The hippocampus is a heterogeneous structure, comprising histologically distinguishable subfields. These subfields are differentially involved in memory consolidation, spatial navigation and pattern separation, complex functions often impaired in individuals with brain disorders characterized by reduced hippocampal volume, including Alzheimer’s disease (AD) and schizophrenia. Given the structural and functional heterogeneity of the hippocampal formation, we sought to characterize the subfields’ genetic architecture. T1-weighted brain scans (n = 21,297, 16 cohorts) were processed with the hippocampal subfields algorithm in FreeSurfer v6.0. We ran a genome-wide association analysis on each subfield, co-varying for whole hippocampal volume. We further calculated the single-nucleotide polymorphism (SNP)-based heritability of 12 subfields, as well as their genetic correlation with each other, with other structural brain features and with AD and schizophrenia. All outcome measures were corrected for age, sex and intracranial volume. We found 15 unique genome-wide significant loci across six subfields, of which eight had not been previously linked to the hippocampus. Top SNPs were mapped to genes associated with neuronal differentiation, locomotor behaviour, schizophrenia and AD. The volumes of all the subfields were estimated to be heritable (h2 from 0.14 to 0.27, all p < 1 × 10–16) and clustered together based on their genetic correlations compared with other structural brain features. There was also evidence of genetic overlap of subicular subfield volumes with schizophrenia. We conclude that hippocampal subfields have partly distinct genetic determinants associated with specific biological processes and traits. Taking into account this specificity may increase our understanding of hippocampal neurobiology and associated pathologies.
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