Publications by authors named "Aiden Corvin"

177 Publications

Interleukin 6 predicts increased neural response during face processing in a sample of individuals with schizophrenia and healthy participants: A functional magnetic resonance imaging study.

Neuroimage Clin 2021 Oct 7;32:102851. Epub 2021 Oct 7.

Center for Neuroimaging and Cognitive Genomics (NICOG), School of Psychology, National University of Ireland Galway, Ireland. Electronic address:

Background: Deficits in facial emotion recognition are a core feature of schizophrenia and predictive of functional outcome. Higher plasma levels of the cytokine interleukin 6 (IL-6) have recently been associated with poorer facial emotion recognition in individuals with schizophrenia and healthy participants, but the neural mechanisms affected remain poorly understood.

Methods: Forty-nine individuals with schizophrenia or schizoaffective disorder and 158 healthy participants were imaged using functional magnetic resonance imaging during a dynamic facial emotion recognition task. Plasma IL-6 was measured from blood samples taken outside the scanner. Multiple regression was used in statistical parametric mapping software to test whether higher plasma IL-6 predicted increased neural response during task performance.

Results: Higher plasma IL-6 predicted increased bilateral medial prefrontal response during neutral face processing compared to angry face processing in the total sample (N = 207, t = 5.67) and increased left insula response during angry face processing compared to neutral face processing (N = 207, t = 4.40) (p < 0.05, family-wise error corrected across the whole brain at the cluster level).

Conclusions: These findings suggest that higher peripheral IL-6 levels predict altered neural response within brain regions involved in social cognition and emotion during facial emotion recognition. This is consistent with recent neuroimaging research on IL-6 and suggesting a possible neural mechanism by which this cytokine might affect facial emotion recognition accuracy.
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http://dx.doi.org/10.1016/j.nicl.2021.102851DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8515297PMC
October 2021

Microglial-expressed genetic risk variants, cognitive function and brain volume in patients with schizophrenia and healthy controls.

Transl Psychiatry 2021 09 23;11(1):490. Epub 2021 Sep 23.

School of Psychology, National University of Ireland, Galway, Ireland.

Changes in immune function are associated with variance in cognitive functioning in schizophrenia. Given that microglia are the primary innate immune cells in the brain, we examined whether schizophrenia risk-associated microglial genes (measured via polygenic score analysis) explained variation in cognition in patients with schizophrenia and controls (n = 1,238) and tested whether grey matter mediated this association. We further sought to replicate these associations in an independent sample of UK Biobank participants (n = 134,827). We then compared the strength of these microglial associations to that of neuronal and astroglial (i.e., other brain-expressed genes) polygenic scores, and used MAGMA to test for enrichment of these gene-sets with schizophrenia risk. Increased microglial schizophrenia polygenic risk was associated with significantly lower performance across several measures of cognitive functioning in both samples; associations which were then found to be mediated via total grey matter volume in the UK Biobank. Unlike neuronal genes which did show evidence of enrichment, the microglial gene-set was not significantly enriched for schizophrenia, suggesting that the relevance of microglia may be for neurodevelopmental processes related more generally to cognition. Further, the microglial polygenic score was associated with performance on a range of cognitive measures in a manner comparable to the neuronal schizophrenia polygenic score, with fewer cognitive associations observed for the astroglial score. In conclusion, our study supports the growing evidence of the importance of immune processes to understanding cognition and brain structure in both patients and in the healthy population.
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http://dx.doi.org/10.1038/s41398-021-01616-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8460789PMC
September 2021

A meta-analysis of deep brain structural shape and asymmetry abnormalities in 2,833 individuals with schizophrenia compared with 3,929 healthy volunteers via the ENIGMA Consortium.

Hum Brain Mapp 2021 Sep 8. Epub 2021 Sep 8.

Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) [Georgia State University, Georgia Institute of Technology], Emory University, Atlanta, Georgia, USA.

Schizophrenia is associated with widespread alterations in subcortical brain structure. While analytic methods have enabled more detailed morphometric characterization, findings are often equivocal. In this meta-analysis, we employed the harmonized ENIGMA shape analysis protocols to collaboratively investigate subcortical brain structure shape differences between individuals with schizophrenia and healthy control participants. The study analyzed data from 2,833 individuals with schizophrenia and 3,929 healthy control participants contributed by 21 worldwide research groups participating in the ENIGMA Schizophrenia Working Group. Harmonized shape analysis protocols were applied to each site's data independently for bilateral hippocampus, amygdala, caudate, accumbens, putamen, pallidum, and thalamus obtained from T1-weighted structural MRI scans. Mass univariate meta-analyses revealed more-concave-than-convex shape differences in the hippocampus, amygdala, accumbens, and thalamus in individuals with schizophrenia compared with control participants, more-convex-than-concave shape differences in the putamen and pallidum, and both concave and convex shape differences in the caudate. Patterns of exaggerated asymmetry were observed across the hippocampus, amygdala, and thalamus in individuals with schizophrenia compared to control participants, while diminished asymmetry encompassed ventral striatum and ventral and dorsal thalamus. Our analyses also revealed that higher chlorpromazine dose equivalents and increased positive symptom levels were associated with patterns of contiguous convex shape differences across multiple subcortical structures. Findings from our shape meta-analysis suggest that common neurobiological mechanisms may contribute to gray matter reduction across multiple subcortical regions, thus enhancing our understanding of the nature of network disorganization in schizophrenia.
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http://dx.doi.org/10.1002/hbm.25625DOI Listing
September 2021

Early life Adversity, functional connectivity and cognitive performance in Schizophrenia: The mediating role of IL-6.

Brain Behav Immun 2021 Nov 7;98:388-396. Epub 2021 Jul 7.

Centre for Neuroimaging, Cognition and Genomics (NICOG), School of Psychology, National University of Ireland, Galway, Ireland. Electronic address:

Objective: Exposure to childhood trauma (CT) is associated with cognitive impairment in schizophrenia, and deficits in social cognition in particular. Here, we sought to test whether IL-6 mediated the association between CT and social cognition both directly, and sequentially via altered default mode network (DMN) connectivity.

Methods: Three-hundred-and-eleven participants (104 patients and 207 healthy participants) were included, with MRI data acquired in a subset of n = 147. CT was measured using the childhood trauma questionnaire (CTQ). IL-6 was measured in both plasma and in toll like receptor (TLR) stimulated whole blood. The CANTAB emotion recognition task (ERT) was administered to assess social cognition, and cortical connectivity was assessed based on resting DMN connectivity.

Results: Higher IL-6 levels, measured both in plasma and in toll-like receptor (TLR-2) stimulated blood, were significantly correlated with higher CTQ scores and lower cognitive and social cognitive function. Plasma IL-6 was further observed to partly mediate the association between higher CT scores and lower emotion recognition performance (CTQ total: β -0.0234, 95% CI: -0.0573 to -0.0074; CTQ physical neglect: β = -0.0316, 95% CI: -0.0741 to -0.0049). Finally, sequential mediation was observed between plasma IL-6 levels and DMN connectivity in mediating the effects of higher CTQ on lower social cognitive function (β = -0.0618, 95% CI: -0.1523 to -0.285).

Conclusion: This work suggests that previous associations between CT and social cognition may be partly mediated via an increased inflammatory response. IL-6's association with changes in DMN activity further suggest at least one cortical network via which CT related effects on cognition may be transmitted.
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http://dx.doi.org/10.1016/j.bbi.2021.06.016DOI Listing
November 2021

Sex-Dependent Shared and Nonshared Genetic Architecture Across Mood and Psychotic Disorders.

Biol Psychiatry 2021 Mar 23. Epub 2021 Mar 23.

Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, Illinois; Department of Psychiatry and Behavioral Sciences, North Shore University Health System, Evanston, Illinois.

Background: Sex differences in incidence and/or presentation of schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BIP) are pervasive. Previous evidence for shared genetic risk and sex differences in brain abnormalities across disorders suggest possible shared sex-dependent genetic risk.

Methods: We conducted the largest to date genome-wide genotype-by-sex (G×S) interaction of risk for these disorders using 85,735 cases (33,403 SCZ, 19,924 BIP, and 32,408 MDD) and 109,946 controls from the PGC (Psychiatric Genomics Consortium) and iPSYCH.

Results: Across disorders, genome-wide significant single nucleotide polymorphism-by-sex interaction was detected for a locus encompassing NKAIN2 (rs117780815, p = 3.2 × 10), which interacts with sodium/potassium-transporting ATPase (adenosine triphosphatase) enzymes, implicating neuronal excitability. Three additional loci showed evidence (p < 1 × 10) for cross-disorder G×S interaction (rs7302529, p = 1.6 × 10; rs73033497, p = 8.8 × 10; rs7914279, p = 6.4 × 10), implicating various functions. Gene-based analyses identified G×S interaction across disorders (p = 8.97 × 10) with transcriptional inhibitor SLTM. Most significant in SCZ was a MOCOS gene locus (rs11665282, p = 1.5 × 10), implicating vascular endothelial cells. Secondary analysis of the PGC-SCZ dataset detected an interaction (rs13265509, p = 1.1 × 10) in a locus containing IDO2, a kynurenine pathway enzyme with immunoregulatory functions implicated in SCZ, BIP, and MDD. Pathway enrichment analysis detected significant G×S interaction of genes regulating vascular endothelial growth factor receptor signaling in MDD (false discovery rate-corrected p < .05).

Conclusions: In the largest genome-wide G×S analysis of mood and psychotic disorders to date, there was substantial genetic overlap between the sexes. However, significant sex-dependent effects were enriched for genes related to neuronal development and immune and vascular functions across and within SCZ, BIP, and MDD at the variant, gene, and pathway levels.
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http://dx.doi.org/10.1016/j.biopsych.2021.02.972DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8458480PMC
March 2021

Identifying nootropic drug targets via large-scale cognitive GWAS and transcriptomics.

Neuropsychopharmacology 2021 09 25;46(10):1788-1801. Epub 2021 May 25.

Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

Broad-based cognitive deficits are an enduring and disabling symptom for many patients with severe mental illness, and these impairments are inadequately addressed by current medications. While novel drug targets for schizophrenia and depression have emerged from recent large-scale genome-wide association studies (GWAS) of these psychiatric disorders, GWAS of general cognitive ability can suggest potential targets for nootropic drug repurposing. Here, we (1) meta-analyze results from two recent cognitive GWAS to further enhance power for locus discovery; (2) employ several complementary transcriptomic methods to identify genes in these loci that are credibly associated with cognition; and (3) further annotate the resulting genes using multiple chemoinformatic databases to identify "druggable" targets. Using our meta-analytic data set (N = 373,617), we identified 241 independent cognition-associated loci (29 novel), and 76 genes were identified by 2 or more methods of gene identification. Actin and chromatin binding gene sets were identified as novel pathways that could be targeted via drug repurposing. Leveraging our transcriptomic and chemoinformatic databases, we identified 16 putative genes targeted by existing drugs potentially available for cognitive repurposing.
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http://dx.doi.org/10.1038/s41386-021-01023-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8357785PMC
September 2021

Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology.

Nat Genet 2021 06 17;53(6):817-829. Epub 2021 May 17.

Department of Neuroscience, Istituto Di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy.

Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies.
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http://dx.doi.org/10.1038/s41588-021-00857-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8192451PMC
June 2021

Changes in Default-Mode Network Associated With Childhood Trauma in Schizophrenia.

Schizophr Bull 2021 Aug;47(5):1482-1494

School of Psychology, National University of Ireland Galway, Galway, Ireland.

Background: There is considerable evidence of dysconnectivity within the default-mode network (DMN) in schizophrenia, as measured during resting-state functional MRI (rs-fMRI). History of childhood trauma (CT) is observed at a higher frequency in schizophrenia than in the general population, but its relationship to DMN functional connectivity has yet to be investigated.

Methods: CT history and rs-fMRI data were collected in 65 individuals with schizophrenia and 132 healthy controls. Seed-based functional connectivity between each of 4 a priori defined seeds of the DMN (medial prefrontal cortex, right and left lateral parietal lobes, and the posterior cingulate cortex) and all other voxels of the brain were compared across groups. Effects of CT on functional connectivity were examined using multiple regression analyses. Where significant associations were observed, regression analyses were further used to determine whether variance in behavioral measures of Theory of Mind (ToM), previously associated with DMN recruitment, were explained by these associations.

Results: Seed-based analyses revealed evidence of widespread reductions in functional connectivity in patients vs controls, including between the left/right parietal lobe (LP) and multiple other regions, including the parietal operculum bilaterally. Across all subjects, increased CT scores were associated with reduced prefrontal-parietal connectivity and, in patients, with increased prefrontal-cerebellar connectivity also. These CT-associated differences in DMN connectivity also predicted variation in behavioral measures of ToM.

Conclusions: These findings suggest that CT history is associated with variation in DMN connectivity during rs-fMRI in patients with schizophrenia and healthy participants, which may partly mediate associations observed between early life adversity and cognitive performance.
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http://dx.doi.org/10.1093/schbul/sbab025DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8379545PMC
August 2021

Converting single nucleotide variants between genome builds: from cautionary tale to solution.

Brief Bioinform 2021 09;22(5)

Neuropsychiatric Genetics Research Group in the Department of Psychiatry, Trinity College Dublin, Ireland.

Next-generation sequencing studies are dependent on a high-quality reference genome for single nucleotide variant (SNV) calling. Although the two most recent builds of the human genome are widely used, position information is typically not directly comparable between them. Re-alignment gives the most accurate position information, but this procedure is often computationally expensive, and therefore, tools such as liftOver and CrossMap are used to convert data from one build to another. However, the positions of converted SNVs do not always match SNVs derived from aligned data, and in some instances, SNVs are known to change chromosome when converted. This is a significant problem when compiling sequencing resources or comparing results across studies. Here, we describe a novel algorithm to identify positions that are unstable when converting between human genome reference builds. These positions are detected independent of the conversion tools and are determined by the chain files, which provide a mapping of contiguous positions from one build to another. We also provide the list of unstable positions for converting between the two most commonly used builds GRCh37 and GRCh38. Pre-excluding SNVs at these positions, prior to conversion, results in SNVs that are stable to conversion. This simple procedure gives the same final list of stable SNVs as applying the algorithm and subsequently removing variants at unstable positions. This work highlights the care that must be taken when converting SNVs between genome builds and provides a simple method for ensuring higher confidence converted data. Unstable positions and algorithm code, available at https://github.com/cathaloruaidh/genomeBuildConversion.
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http://dx.doi.org/10.1093/bib/bbab069DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8425424PMC
September 2021

Minding metabolism: targeted interventions to improve cardio-metabolic monitoring across early and chronic psychosis.

Ir J Med Sci 2021 Mar 8. Epub 2021 Mar 8.

Department of Psychiatry, Sligo/Leitrim Mental Health Services, Sligo, Ireland.

Background: Antipsychotics (APs) increase weight, metabolic syndrome, diabetes and cardiovascular disease. Guidelines recommend cardio-metabolic monitoring at initial assessment, at 3 months and then annually in people prescribed APs.

Aim: To determine the rates of cardio-metabolic monitoring in AP treated early and chronic psychosis and to assess the impact of targeted improvement strategies.

Methods: Medical records were reviewed in two cohorts of first-episode psychosis (FEP) patients before and after the implementation of a physical health parameter checklist and electronic laboratory order set. In a separate group of patients with chronic psychotic disorders, adherence to annual monitoring was assessed before and 3 months after an awareness-raising educational intervention.

Results: In FEP, fasting glucose (39% vs 67%, p=0.05), HbA1c (0% vs 24%, p=0.005) and prolactin (18% vs 67%, p=0.001) monitoring improved. There were no significant differences in weight (67% vs 67%, p=1.0), BMI (3% vs 10%, p=0.54), waist circumference (3% vs 0%, p=1.0), fasting lipids (61% vs 76% p=0.22) or ECG monitoring (67% vs 67%, p=1.0). Blood pressure (BP) (88% vs 57%, p=0.04) and heart rate (91% vs 65%, p=0.03) monitoring dis-improved. Diet (0%) and exercise (<15%) assessment was poor. In chronic psychotic disorders, BP monitoring improved (20% vs 41.4%, p=0.05), whereas weight (17.0% vs 34.1%, p=0.12), BMI (9.7% vs 12.1%, p=1.0), fasting glucose (17% vs 24.3%, p=0.58) and fasting lipids remained unchanged (17% vs 24.3%, p=0.58).

Conclusions: Targeted improvement strategies resulted in a significant improvement in a limited number of parameters in early and chronic psychotic disorders. Overall, monitoring remained suboptimal.
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http://dx.doi.org/10.1007/s11845-021-02576-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7938026PMC
March 2021

Rare Copy Number Variants Are Associated With Poorer Cognition in Schizophrenia.

Biol Psychiatry 2021 07 19;90(1):28-34. Epub 2020 Dec 19.

MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom. Electronic address:

Background: Cognitive impairment in schizophrenia is a major contributor to poor outcomes, yet its causes are poorly understood. Some rare copy number variants (CNVs) are associated with schizophrenia risk and affect cognition in healthy populations, but their contribution to cognitive impairment in schizophrenia has not been investigated. We examined the effect of 12 schizophrenia CNVs on cognition in those with schizophrenia.

Methods: General cognitive ability was measured using the Measurement and Treatment Research to Improve Cognition in Schizophrenia composite z score in 875 patients with schizophrenia and in a replication sample of 519 patients with schizophrenia using Wechsler Adult Intelligence Scale Full Scale IQ. Using linear regression, we tested for association between cognition and schizophrenia CNV status, covarying for age and sex. In addition, we tested whether CNVs hitting genes in schizophrenia-enriched gene sets (loss-of-function intolerant and synaptic gene sets) were associated with cognitive impairment.

Results: A total of 23 schizophrenia CNV carriers were identified. Schizophrenia CNV carriers had lower general cognitive ability than nonschizophrenia CNV carriers in discovery (β = -0.66, 95% confidence interval [CI] = -1.31 to -0.01) and replication samples (β = -0.91, 95% CI = -1.71 to -0.11) and after meta-analysis (β = -0.76, 95% CI = -1.26 to -0.25, p = .003). CNVs hitting loss-of-function intolerant genes were associated with lower cognition (β = -0.15, 95% CI = -0.29 to -0.001, p = .048).

Conclusions: In those with schizophrenia, cognitive ability in schizophrenia CNV carriers is 0.5-1.0 standard deviations below non-CNV carriers, which may have implications for clinical assessment and management. We also demonstrate that rare CNVs hitting genes intolerant to loss-of-function variation lead to more severe cognitive impairment, above and beyond the effect of known schizophrenia CNVs.
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http://dx.doi.org/10.1016/j.biopsych.2020.11.025DOI Listing
July 2021

DNA methylation meta-analysis reveals cellular alterations in psychosis and markers of treatment-resistant schizophrenia.

Elife 2021 Feb 26;10. Epub 2021 Feb 26.

Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany.

We performed a systematic analysis of blood DNA methylation profiles from 4483 participants from seven independent cohorts identifying differentially methylated positions (DMPs) associated with psychosis, schizophrenia, and treatment-resistant schizophrenia. Psychosis cases were characterized by significant differences in measures of blood cell proportions and elevated smoking exposure derived from the DNA methylation data, with the largest differences seen in treatment-resistant schizophrenia patients. We implemented a stringent pipeline to meta-analyze epigenome-wide association study (EWAS) results across datasets, identifying 95 DMPs associated with psychosis and 1048 DMPs associated with schizophrenia, with evidence of colocalization to regions nominated by genetic association studies of disease. Many schizophrenia-associated DNA methylation differences were only present in patients with treatment-resistant schizophrenia, potentially reflecting exposure to the atypical antipsychotic clozapine. Our results highlight how DNA methylation data can be leveraged to identify physiological (e.g., differential cell counts) and environmental (e.g., smoking) factors associated with psychosis and molecular biomarkers of treatment-resistant schizophrenia.
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http://dx.doi.org/10.7554/eLife.58430DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8009672PMC
February 2021

Investigating rare pathogenic/likely pathogenic exonic variation in bipolar disorder.

Mol Psychiatry 2021 Jan 22. Epub 2021 Jan 22.

HudsonAlpha Institute for Biotechnology, Huntsville, AL, 35806, USA.

Bipolar disorder (BD) is a serious mental illness with substantial common variant heritability. However, the role of rare coding variation in BD is not well established. We examined the protein-coding (exonic) sequences of 3,987 unrelated individuals with BD and 5,322 controls of predominantly European ancestry across four cohorts from the Bipolar Sequencing Consortium (BSC). We assessed the burden of rare, protein-altering, single nucleotide variants classified as pathogenic or likely pathogenic (P-LP) both exome-wide and within several groups of genes with phenotypic or biologic plausibility in BD. While we observed an increased burden of rare coding P-LP variants within 165 genes identified as BD GWAS regions in 3,987 BD cases (meta-analysis OR = 1.9, 95% CI = 1.3-2.8, one-sided p = 6.0 × 10), this enrichment did not replicate in an additional 9,929 BD cases and 14,018 controls (OR = 0.9, one-side p = 0.70). Although BD shares common variant heritability with schizophrenia, in the BSC sample we did not observe a significant enrichment of P-LP variants in SCZ GWAS genes, in two classes of neuronal synaptic genes (RBFOX2 and FMRP) associated with SCZ or in loss-of-function intolerant genes. In this study, the largest analysis of exonic variation in BD, individuals with BD do not carry a replicable enrichment of rare P-LP variants across the exome or in any of several groups of genes with biologic plausibility. Moreover, despite a strong shared susceptibility between BD and SCZ through common genetic variation, we do not observe an association between BD risk and rare P-LP coding variants in genes known to modulate risk for SCZ.
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http://dx.doi.org/10.1038/s41380-020-01006-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8295400PMC
January 2021

Methyl-CpG-binding protein 2 mediates overlapping mechanisms across brain disorders.

Sci Rep 2020 12 17;10(1):22255. Epub 2020 Dec 17.

Neuropsychiatric Genetics, Department of Psychiatry, Trinity College Dublin, School of Medicine, Trinity Translational Medicine Institute, Trinity Center for Health Sciences, St James Hospital, Dublin 8, Dublin, Ireland.

MECP2 and its product, Methyl-CpG binding protein 2 (MeCP2), are mostly known for their association to Rett Syndrome (RTT), a rare neurodevelopmental disorder. Additional evidence suggests that MECP2 may underlie other neuropsychiatric and neurological conditions, and perhaps modulate common presentations and pathophysiology across disorders. To clarify the mechanisms of these interactions, we develop a method that uses the binding properties of MeCP2 to identify its targets, and in particular, the genes recognized by MeCP2 and associated to several neurological and neuropsychiatric disorders. Analysing mechanisms and pathways modulated by these genes, we find that they are involved in three main processes: neuronal transmission, immuno-reactivity, and development. Also, while the nervous system is the most relevant in the pathophysiology of the disorders, additional systems may contribute to MeCP2 action through its target genes. We tested our results with transcriptome analysis on Mecp2-null models and cells derived from a patient with RTT, confirming that the genes identified by our procedure are directly modulated by MeCP2. Thus, MeCP2 may modulate similar mechanisms in different pathologies, suggesting that treatments for one condition may be effective for related disorders.
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http://dx.doi.org/10.1038/s41598-020-79268-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7746753PMC
December 2020

Childhood trauma, brain structure and emotion recognition in patients with schizophrenia and healthy participants.

Soc Cogn Affect Neurosci 2020 12;15(12):1336-1350

School of Psychology, National University of Ireland Galway, Galway, Ireland.

Childhood trauma, and in particular physical neglect, has been repeatedly associated with lower performance on measures of social cognition (e.g. emotion recognition tasks) in both psychiatric and non-clinical populations. The neural mechanisms underpinning this association have remained unclear. Here, we investigated whether volumetric changes in three stress-sensitive regions-the amygdala, hippocampus and anterior cingulate cortex (ACC)-mediate the association between childhood trauma and emotion recognition in a healthy participant sample (N = 112) and a clinical sample of patients with schizophrenia (N = 46). Direct effects of childhood trauma, specifically physical neglect, on Emotion Recognition Task were observed in the whole sample. In healthy participants, reduced total and left ACC volumes were observed to fully mediate the association between both physical neglect and total childhood trauma score, and emotion recognition. No mediating effects of the hippocampus and amygdala volumes were observed for either group. These results suggest that reduced ACC volume may represent part of the mechanism by which early life adversity results in poorer social cognitive function. Confirmation of the causal basis of this association would highlight the importance of resilience-building interventions to mitigate the detrimental effects of childhood trauma on brain structure and function.
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http://dx.doi.org/10.1093/scan/nsaa160DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7759212PMC
December 2020

Effects of complement gene-set polygenic risk score on brain volume and cortical measures in patients with psychotic disorders and healthy controls.

Am J Med Genet B Neuropsychiatr Genet 2020 12 12;183(8):445-453. Epub 2020 Sep 12.

Cognitive Genetics & Cognitive Therapy Group, The Centre for Neuroimaging, Cognition and Genomics (NICOG), School of Psychology and Discipline of Biochemistry, National University of Ireland Galway, Galway, Ireland.

Multiple genome-wide association studies of schizophrenia have reported associations between genetic variants within the MHC region and disease risk, an association that has been partially accounted for by alleles of the complement component 4 (C4) gene. Following on previous findings of association between both C4 and other complement-related variants and memory function, we tested the hypothesis that polygenic scores calculated based on identified schizophrenia risk alleles within the "complement" system would be broadly associated with memory function and associated brain structure. We tested this using a polygenic risk score (PRS) calculated for complement genes, but excluding C4 variants. Higher complement-based PRS scores were observed to be associated with lower memory scores for the sample as a whole (N = 620, F change = 8.25; p = .004). A significant association between higher PRS and lower hippocampal volume was also observed (N = 216, R change = 0.016, p = .015). However, after correcting for further testing of association with the more general indices of cortical thickness, surface area or total brain volume, none of which were associated with complement, the association with hippocampal volume became non-significant. A post-hoc analysis of hippocampal subfields suggested an association between complement PRS and several hippocampal subfields, findings that appeared to be particularly driven by the patient sample. In conclusion, our study yielded suggestive evidence of association between complement-based schizophrenia PRS and variation in memory function and hippocampal volume.
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http://dx.doi.org/10.1002/ajmg.b.32820DOI Listing
December 2020

Functional Magnetic Resonance Imaging Connectivity Accurately Distinguishes Cases With Psychotic Disorders From Healthy Controls, Based on Cortical Features Associated With Brain Network Development.

Biol Psychiatry Cogn Neurosci Neuroimaging 2020 Jun 8. Epub 2020 Jun 8.

Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom; Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, United Kingdom.

Background: Machine learning (ML) can distinguish cases with psychotic disorder from healthy controls based on magnetic resonance imaging (MRI) data, but it is not yet clear which MRI metrics are the most informative for case-control ML, or how ML algorithms relate to the underlying biology.

Methods: We analyzed multimodal MRI data from 2 independent case-control studies of psychotic disorders (cases, n = 65, 28; controls, n = 59, 80) and compared ML accuracy across 5 selected MRI metrics from 3 modalities. Cortical thickness, mean diffusivity, and fractional anisotropy were estimated at each of 308 cortical regions, as well as functional and structural connectivity between each pair of regions. Functional connectivity data were also used to classify nonpsychotic siblings of cases (n = 64) and to distinguish cases from controls in a third independent study (cases, n = 67; controls, n = 81).

Results: In both principal studies, the most informative metric was functional MRI connectivity: The areas under the receiver operating characteristic curve were 88% and 76%, respectively. The cortical map of diagnostic connectivity features (ML weights) was replicable between studies (r = .27, p < .001); correlated with replicable case-control differences in functional MRI degree centrality and with a prior cortical map of adolescent development of functional connectivity; predicted intermediate probabilities of psychosis in siblings; and was replicated in the third case-control study.

Conclusions: ML most accurately distinguished cases from controls by a replicable pattern of functional MRI connectivity features, highlighting abnormal hubness of cortical nodes in an anatomical pattern consistent with the concept of psychosis as a disorder of network development.
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http://dx.doi.org/10.1016/j.bpsc.2020.05.013DOI Listing
June 2020

Childhood trauma, parental bonding, and social cognition in patients with schizophrenia and healthy adults.

J Clin Psychol 2021 01 12;77(1):241-253. Epub 2020 Aug 12.

School of Psychology, National University of Ireland Galway, Galway, Ireland.

Objective: This study investigated associations between childhood trauma, parental bonding, and social cognition (i.e., Theory of Mind and emotion recognition) in patients with schizophrenia and healthy adults.

Methods: Using cross-sectional data, we examined the recollections of childhood trauma experiences and social cognitive abilities in 74 patients with schizophrenia and 116 healthy adults.

Results: Patients had significantly higher scores compared with healthy participants on childhood trauma, and lower scores on parental bonding and social cognitive measures. Physical neglect was found to be the strongest predictor of emotion recognition impairments in both groups. Optimal parental bonding attenuated the impact of childhood trauma on emotion recognition.

Conclusion: The present study provides evidence of an association between physical neglect and emotion recognition in patients with schizophrenia and healthy individuals and shows that both childhood trauma and parental bonding may influence social cognitive development. Psychosocial interventions should be developed to prevent and mitigate the long-term effects of childhood adversities.
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http://dx.doi.org/10.1002/jclp.23023DOI Listing
January 2021

Deficit not bias: A quantifiable neuropsychological model of delusions.

Schizophr Res 2020 08 5;222:496-498. Epub 2020 Jun 5.

The Department of Psychiatry, Trinity College Dublin, Ireland; The National Forensic Mental Health Service, The Central Mental Hospital, Dundrum, Dublin 14, Ireland. Electronic address:

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http://dx.doi.org/10.1016/j.schres.2020.05.055DOI Listing
August 2020

Prevalence of N-Methyl-d-Aspartate Receptor antibody (NMDAR-Ab) encephalitis in patients with first episode psychosis and treatment resistant schizophrenia on clozapine, a population based study.

Schizophr Res 2020 08 1;222:455-461. Epub 2020 Jun 1.

Department of Psychiatry, Trinity College Dublin, Ireland; Department of Psychiatry, St James's Hospital, Dublin, Ireland.

Introduction: N-methyl-d-aspartate receptor antibody (NMDAR-Ab) encephalitis consensus criteria has recently been defined. We aimed to examine the prevalence of NMDAR-Ab encephalitis in patients with first episode psychosis (FEP) and treatment resistant schizophrenia (TRS) on clozapine, using clinical investigations, antibody testing and to retrospectively apply diagnostic consensus criteria.

Methods: Adult (18-65 years old) cases of FEP meeting inclusion criteria were recruited over three years and assessed using the Structured Clinical Interview for DSM-IV disorders (SCID). NMDAR-Ab was identified using a live cell-based assay (L-CBA). Seropositive cases were clinically investigated for features of encephalitis including neuro-imaging, EEG and CSF where possible. Serum was retested using immunohistochemistry (IHC) as part of diagnostic criteria guidelines. A cohort of patients with TRS was also recruited.

Results: 112 FEP patients were recruited over 3 years. NMDAR-Ab seroprevalence was 4/112 (3.5%) cases. One case (<1%) was diagnosed with definite NMDAR-Ab encephalitis and treated with immunotherapy. One of the three other seropositive cases met criteria for probable encephalitis. However all three were ultimately diagnosed with mood disorders with psychotic features. None have developed neurological features at three year follow up. 1/100 (1%) of patients with TRS was 100 patients with TRS were recruited. One case (1%) seropositive for NMDAR-Ab but did not meet criteria for encephalitis.

Conclusions: NMDAR-Ab encephalitis as defined by consensus guidelines occured rarely in psychiatric services in this study. Further studies are needed to establish pathogenicity of serum NMDAR-Ab antibodies. Psychiatric services should be aware of the clinical features of encephalitis.
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http://dx.doi.org/10.1016/j.schres.2019.11.023DOI Listing
August 2020

The Relationship Between White Matter Microstructure and General Cognitive Ability in Patients With Schizophrenia and Healthy Participants in the ENIGMA Consortium.

Am J Psychiatry 2020 06 26;177(6):537-547. Epub 2020 Mar 26.

School of Psychology, Centre for Neuroimaging and Cognitive Genomics, National Centre for Biomedical Engineering Science and Galway Neuroscience Centre, National University of Ireland Galway, Galway (Holleran, Cannon, McDonald, Morris, Mothersill, Donohoe); Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey (Kelly, Thompson, Jahanshad); Department of Psychiatry, University of Edinburgh, Edinburgh (Alloza, Lawrie); Department of Child and Adolescent Psychiatry, Instituto de Investigación Sanitaria Gregorio Marañón, IiSGM, Hospital General Universitario Gregorio Marañón, School of Medicine, CIBERSAM, Universidad Complutense, Madrid (Alloza, Arango, Janssen, Martinez); NORMENT, K.G. Jebsen Center for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo (Agartz); Department of Psychiatry, Ullevål University Hospital and Institute of Psychiatry, University of Oslo, Oslo (Andreassen); Laboratory of Neuropsychiatry, Department of Clinical and Behavioral Neurology, IRCCS Santa Lucia Foundation, Rome (Banaj, Piras, Spalletta); Mind Research Network and Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque (Calhoun); Neuroscience Research Australia and School of Psychiatry, University of New South Wales, Sydney (Carr); Neuropsychiatric Genetics Research Group, Department of Psychiatry, Trinity College Dublin (Corvin); Olin Neuropsychiatric Research Center, Institute of Living, Hartford Hospital and Department of Psychiatry, Yale University School of Medicine, New Haven, Conn. (Glahn); Department of Psychiatry, University of Pennsylvania, Philadelphia (Gur, Roalf, Satterthwaite); Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore (Hong, Kochunov, Rowland); National Institute of Mental Health, Klecany, Czech Republic (Hoschl, Spaniel); Department of Psychiatry and Mental Health (Howells, Stein, Uhlmann) and Neuroscience Institute (Howells, Stein), University of Cape Town, Cape Town, South Africa; Highfield Unit, Warneford Hospital, Oxford, U.K. (James); Mind Research Network, Lovelace Biomedical and Environmental Research Institute, Albuquerque, N.Mex. (Liu); Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Carlton South, Australia (Pantelis, Zalesky); Department of Psychiatry and Human Behavior, School of Medicine, University of California, Irvine (Potkin); Priority Centre for Brain and Mental Health Research (Schall, Rasser) and Priority Research Centre for Stroke and Brain Injury, University of Newcastle, Newcastle, Australia (Rasser); Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston (Spalletta); Kimel Family Translational Imaging-Genetics Research Laboratory, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Department of Psychiatry, University of Toronto, Toronto (Voineskos); Department of Biomedical Engineering and Melbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, Australia (Zalesky); Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, and Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine (van Erp); Department of Psychology, Georgia State University, Atlanta (Turner); and Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh (Deary).

Objective: Schizophrenia has recently been associated with widespread white matter microstructural abnormalities, but the functional effects of these abnormalities remain unclear. Widespread heterogeneity of results from studies published to date preclude any definitive characterization of the relationship between white matter and cognitive performance in schizophrenia. Given the relevance of deficits in cognitive function to predicting social and functional outcomes in schizophrenia, the authors carried out a meta-analysis of available data through the ENIGMA Consortium, using a common analysis pipeline, to elucidate the relationship between white matter microstructure and a measure of general cognitive performance, IQ, in patients with schizophrenia and healthy participants.

Methods: The meta-analysis included 760 patients with schizophrenia and 957 healthy participants from 11 participating ENIGMA Consortium sites. For each site, principal component analysis was used to calculate both a global fractional anisotropy component (gFA) and a fractional anisotropy component for six long association tracts (LA-gFA) previously associated with cognition.

Results: Meta-analyses of regression results indicated that gFA accounted for a significant amount of variation in cognition in the full sample (effect size [Hedges' g]=0.27, CI=0.17-0.36), with similar effects sizes observed for both the patient (effect size=0.20, CI=0.05-0.35) and healthy participant groups (effect size=0.32, CI=0.18-0.45). Comparable patterns of association were also observed between LA-gFA and cognition for the full sample (effect size=0.28, CI=0.18-0.37), the patient group (effect size=0.23, CI=0.09-0.38), and the healthy participant group (effect size=0.31, CI=0.18-0.44).

Conclusions: This study provides robust evidence that cognitive ability is associated with global structural connectivity, with higher fractional anisotropy associated with higher IQ. This association was independent of diagnosis; while schizophrenia patients tended to have lower fractional anisotropy and lower IQ than healthy participants, the comparable size of effect in each group suggested a more general, rather than disease-specific, pattern of association.
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http://dx.doi.org/10.1176/appi.ajp.2019.19030225DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7938666PMC
June 2020

The genetic architecture of the human cerebral cortex.

Science 2020 03;367(6484)

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder.
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http://dx.doi.org/10.1126/science.aay6690DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7295264PMC
March 2020

Identifying schizophrenia patients who carry pathogenic genetic copy number variants using standard clinical assessment: retrospective cohort study.

Br J Psychiatry 2020 05;216(5):275-279

Professor, Head of Discipline, Neuropsychiatric Genetics Research Group, Department of Psychiatry, School of Medicine, Trinity College Dublin, Ireland.

Background: Copy number variants (CNVs) play a significant role in disease pathogenesis in a small subset of individuals with schizophrenia (~2.5%). Chromosomal microarray testing is a first-tier genetic test for many neurodevelopmental disorders. Similar testing could be useful in schizophrenia.

Aims: To determine whether clinically identifiable phenotypic features could be used to successfully model schizophrenia-associated (SCZ-associated) CNV carrier status in a large schizophrenia cohort.

Method: Logistic regression and receiver operating characteristic (ROC) curves tested the accuracy of readily identifiable phenotypic features in modelling SCZ-associated CNV status in a discovery data-set of 1215 individuals with psychosis. A replication analysis was undertaken in a second psychosis data-set (n = 479).

Results: In the discovery cohort, specific learning disorder (OR = 8.12; 95% CI 1.16-34.88, P = 0.012), developmental delay (OR = 5.19; 95% CI 1.58-14.76, P = 0.003) and comorbid neurodevelopmental disorder (OR = 5.87; 95% CI 1.28-19.69, P = 0.009) were significant independent variables in modelling positive carrier status for a SCZ-associated CNV, with an area under the ROC (AUROC) of 74.2% (95% CI 61.9-86.4%). A model constructed from the discovery cohort including developmental delay and comorbid neurodevelopmental disorder variables resulted in an AUROC of 83% (95% CI 52.0-100.0%) for the replication cohort.

Conclusions: These findings suggest that careful clinical history taking to document specific neurodevelopmental features may be informative in screening for individuals with schizophrenia who are at higher risk of carrying known SCZ-associated CNVs. Identification of genomic disorders in these individuals is likely to have clinical benefits similar to those demonstrated for other neurodevelopmental disorders.
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http://dx.doi.org/10.1192/bjp.2019.262DOI Listing
May 2020

Moral cognition, the missing link between psychotic symptoms and acts of violence: a cross-sectional national forensic cohort study.

BMC Psychiatry 2019 12 19;19(1):408. Epub 2019 Dec 19.

National Forensic Mental Health Service, Central Mental Hospital, Dundrum, Dublin, Ireland.

Background: People with schizophrenia are ten times more likely to commit homicide than a member of the general population. The relationship between symptoms of schizophrenia and acts of violence is unclear. There has also been limited research on what determines the seriousness and form of violence, such as reactive or instrumental violence. Moral cognition may play a paradoxical role in acts of violence for people with schizophrenia. Thoughts which have moral content arising from psychotic symptoms may be a cause of serious violence.

Method: We investigated if psychotic symptoms and moral cognitions at the time of a violent act were associated with acts of violence using a cross-sectional national forensic cohort (n = 55). We examined whether moral cognitions were associated with violence when controlling for neurocognition and violence proneness. We explored the association between all psychotic symptoms present at the time of the violent act, psychotic symptoms judged relevant to the violent act and moral cognitions present at that time. Using mediation analysis, we examined whether moral cognitions were the missing link between symptoms and the relevance of symptoms for violence. We also investigated if specific moral cognitions mediated the relationship between specific psychotic symptoms, the seriousness of violence (including homicide), and the form of violence.

Results: Psychotic symptoms generally were not associated with the seriousness or form of violence. However, specific moral cognitions were associated with the seriousness and form of violence even when controlling for neurocognition and violence proneness. Specific moral cognitions were associated with specific psychotic symptoms present and relevant to violence. Moral cognitions mediated the relationship between the presence of specific psychotic symptoms and their relevance for violence, homicide, seriousness of violence, and the form of violence.

Conclusions: Moral cognitions including the need to reduce suffering, responding to an act of injustice or betrayal, the desire to comply with authority, or the wish to punish impure or disgusting behaviour, may be a key mediator explaining the relationship between psychotic symptoms and acts of violence. Our findings may have important implications for risk assessment, treatment and violence prevention.
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http://dx.doi.org/10.1186/s12888-019-2372-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6921589PMC
December 2019

Integrating machining learning and multimodal neuroimaging to detect schizophrenia at the level of the individual.

Hum Brain Mapp 2020 04 18;41(5):1119-1135. Epub 2019 Nov 18.

Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK.

Schizophrenia is a severe psychiatric disorder associated with both structural and functional brain abnormalities. In the past few years, there has been growing interest in the application of machine learning techniques to neuroimaging data for the diagnostic and prognostic assessment of this disorder. However, the vast majority of studies published so far have used either structural or functional neuroimaging data, without accounting for the multimodal nature of the disorder. Structural MRI and resting-state functional MRI data were acquired from a total of 295 patients with schizophrenia and 452 healthy controls at five research centers. We extracted features from the data including gray matter volume, white matter volume, amplitude of low-frequency fluctuation, regional homogeneity and two connectome-wide based metrics: structural covariance matrices and functional connectivity matrices. A support vector machine classifier was trained on each dataset separately to distinguish the subjects at individual level using each of the single feature as well as their combination, and 10-fold cross-validation was used to assess the performance of the model. Functional data allow higher accuracy of classification than structural data (mean 82.75% vs. 75.84%). Within each modality, the combination of images and matrices improves performance, resulting in mean accuracies of 81.63% for structural data and 87.59% for functional data. The use of all combined structural and functional measures allows the highest accuracy of classification (90.83%). We conclude that combining multimodal measures within a single model is a promising direction for developing biologically informed diagnostic tools in schizophrenia.
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http://dx.doi.org/10.1002/hbm.24863DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7268084PMC
April 2020

Association of Copy Number Variation of the 15q11.2 BP1-BP2 Region With Cortical and Subcortical Morphology and Cognition.

JAMA Psychiatry 2020 04;77(4):420-430

Department of Biological Psychology and Netherlands Twin Register, VU University Amsterdam, Amsterdam, the Netherlands.

Importance: Recurrent microdeletions and duplications in the genomic region 15q11.2 between breakpoints 1 (BP1) and 2 (BP2) are associated with neurodevelopmental disorders. These structural variants are present in 0.5% to 1.0% of the population, making 15q11.2 BP1-BP2 the site of the most prevalent known pathogenic copy number variation (CNV). It is unknown to what extent this CNV influences brain structure and affects cognitive abilities.

Objective: To determine the association of the 15q11.2 BP1-BP2 deletion and duplication CNVs with cortical and subcortical brain morphology and cognitive task performance.

Design, Setting, And Participants: In this genetic association study, T1-weighted brain magnetic resonance imaging were combined with genetic data from the ENIGMA-CNV consortium and the UK Biobank, with a replication cohort from Iceland. In total, 203 deletion carriers, 45 247 noncarriers, and 306 duplication carriers were included. Data were collected from August 2015 to April 2019, and data were analyzed from September 2018 to September 2019.

Main Outcomes And Measures: The associations of the CNV with global and regional measures of surface area and cortical thickness as well as subcortical volumes were investigated, correcting for age, age2, sex, scanner, and intracranial volume. Additionally, measures of cognitive ability were analyzed in the full UK Biobank cohort.

Results: Of 45 756 included individuals, the mean (SD) age was 55.8 (18.3) years, and 23 754 (51.9%) were female. Compared with noncarriers, deletion carriers had a lower surface area (Cohen d = -0.41; SE, 0.08; P = 4.9 × 10-8), thicker cortex (Cohen d = 0.36; SE, 0.07; P = 1.3 × 10-7), and a smaller nucleus accumbens (Cohen d = -0.27; SE, 0.07; P = 7.3 × 10-5). There was also a significant negative dose response on cortical thickness (β = -0.24; SE, 0.05; P = 6.8 × 10-7). Regional cortical analyses showed a localization of the effects to the frontal, cingulate, and parietal lobes. Further, cognitive ability was lower for deletion carriers compared with noncarriers on 5 of 7 tasks.

Conclusions And Relevance: These findings, from the largest CNV neuroimaging study to date, provide evidence that 15q11.2 BP1-BP2 structural variation is associated with brain morphology and cognition, with deletion carriers being particularly affected. The pattern of results fits with known molecular functions of genes in the 15q11.2 BP1-BP2 region and suggests involvement of these genes in neuronal plasticity. These neurobiological effects likely contribute to the association of this CNV with neurodevelopmental disorders.
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http://dx.doi.org/10.1001/jamapsychiatry.2019.3779DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6822096PMC
April 2020

Detecting schizophrenia at the level of the individual: relative diagnostic value of whole-brain images, connectome-wide functional connectivity and graph-based metrics.

Psychol Med 2020 08 8;50(11):1852-1861. Epub 2019 Aug 8.

Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, London, UK.

Background: Previous studies using resting-state functional neuroimaging have revealed alterations in whole-brain images, connectome-wide functional connectivity and graph-based metrics in groups of patients with schizophrenia relative to groups of healthy controls. However, it is unclear which of these measures best captures the neural correlates of this disorder at the level of the individual patient.

Methods: Here we investigated the relative diagnostic value of these measures. A total of 295 patients with schizophrenia and 452 healthy controls were investigated using resting-state functional Magnetic Resonance Imaging at five research centres. Connectome-wide functional networks were constructed by thresholding correlation matrices of 90 brain regions, and their topological properties were analyzed using graph theory-based methods. Single-subject classification was performed using three machine learning (ML) approaches associated with varying degrees of complexity and abstraction, namely logistic regression, support vector machine and deep learning technology.

Results: Connectome-wide functional connectivity allowed single-subject classification of patients and controls with higher accuracy (average: 81%) than both whole-brain images (average: 53%) and graph-based metrics (average: 69%). Classification based on connectome-wide functional connectivity was driven by a distributed bilateral network including the thalamus and temporal regions.

Conclusion: These results were replicated across the three employed ML approaches. Connectome-wide functional connectivity permits differentiation of patients with schizophrenia from healthy controls at single-subject level with greater accuracy; this pattern of results is consistent with the 'dysconnectivity hypothesis' of schizophrenia, which states that the neural basis of the disorder is best understood in terms of system-level functional connectivity alterations.
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http://dx.doi.org/10.1017/S0033291719001934DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7477363PMC
August 2020
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