Evidence map›Paper›PMID 32792019›Full record

ArticleThe British journal of psychiatry : the journal of mental science2021

Effects of genomic copy number variants penetrant for schizophrenia on cortical thickness and surface area in healthy individuals: analysis of the UK Biobank.

Xavier Caseras, George Kirov, Kimberley M Kendall, Elliott Rees, Sophie E Legge, Matthew Bracher-Smith, Valentina Escott-Price, Kevin Murphy

Open access · hybridAbstract read
In one paragraph

Article in The British journal of psychiatry : the journal of mental science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.3field-weighted citation impact, top 19% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Copy Number Variations and Schizophrenia.Molecular neurobiology · 2023
    Review
  7. Article
  8. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

Xavier CaserasMRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, UK.ORCID 0000-0002-8490-6891
George KirovMRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, UK.ORCID 0000-0002-3427-3950
Kimberley M KendallMRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, UK.
Elliott ReesMRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, UK.
Sophie E LeggeMRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, UK.ORCID 0000-0001-6617-0289
Matthew Bracher-SmithMRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, UK.
Valentina Escott-PriceMRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University; and UK Dementia Research Institute, Cardiff University, UK.
Kevin MurphyCardiff University Brain Research Imaging Centre (CUBRIC), School of Physics and Astronomy, Cardiff University, UK.
Cardiff University · GBUK Dementia Research Institute · GB

Funding

Medical Research Council G0801418Medical Research Council MR/L010305/1Medical Research Council MR/L023784/2Medical Research Council MR/T04604X/1Wellcome Trust 200804/Z/16/Z
6 · The paper itself

Abstract

backgroundSchizophrenia is a highly heritable disorder with undetermined neurobiological causes. Understanding the impact on brain anatomy of carrying genetic risk for the disorder will contribute to uncovering its neurobiological underpinnings.

aimsTo examine the effect of rare copy number variants (CNVs) associated with schizophrenia on brain cortical anatomy in a sample of unaffected participants from the UK Biobank.

methodWe used regression analyses to compare cortical thickness and surface area (total and across gyri) between 120 unaffected carriers of rare CNVs associated with schizophrenia and 16 670 participants without any pathogenic CNV. A measure of cortical thickness and surface area covariance across gyri was also compared between groups.

resultsCarrier status was associated with reduced surface area (β = -0.020 mm2, P < 0.001) and less robustly with increased cortical thickness (β = 0.015 mm, P = 0.035), and with increased covariance in thickness (carriers z = 0.31 v. non-carriers z = 0.22, P < 0.0005). Associations were mainly present in frontal and parietal areas and driven by a limited number of rare risk alleles included in our analyses (mainly 15q11.2 deletion for surface area and 16p13.11 duplication for thickness covariance).

conclusionsResults for surface area conformed with previous clinical findings, supporting surface area reductions as an indicator of genetic liability for schizophrenia. Results for cortical thickness, though, argued against its validity as a potential risk marker. Increased structural thickness covariance across gyri also appears related to risk for schizophrenia. The heterogeneity found across the effects of rare risk alleles suggests potential different neurobiological gateways into schizophrenia's phenotype.

Indexed as

SchizophreniaBiological Specimen BanksDNA Copy Number VariationsGenetic Predisposition to DiseaseGenomicsHumansMagnetic Resonance ImagingUnited Kingdomcopy number variationcortical anatomygeneticsImagingschizophrenia

Identifiers

PMID32792019
PMCPMC7844611
OpenAlexW3049104359

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.