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Analysis of Diffusion Tensor Imaging Data From the UK Biobank Confirms Dosage Effect of 15q11.2 Copy Number Variation on White Matter and Shows Association With Cognition

  • Ana I. Silva
    Correspondence
    Address correspondence to Ana I. Silva, Ph.D.
    Affiliations
    Neuroscience and Mental Health Research Institute, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff, United Kingdom

    Cardiff University Brain Research Imaging Centre School of Psychology, Cardiff University, Cardiff, United Kingdom

    School for Mental Health and Neuroscience, Department of Psychiatry and Neuropsychology, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands
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  • George Kirov
    Affiliations
    Neuroscience and Mental Health Research Institute, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff, United Kingdom
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  • Kimberley M. Kendall
    Affiliations
    Neuroscience and Mental Health Research Institute, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff, United Kingdom
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  • Mathew Bracher-Smith
    Affiliations
    Neuroscience and Mental Health Research Institute, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff, United Kingdom
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  • Lawrence S. Wilkinson
    Affiliations
    Neuroscience and Mental Health Research Institute, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff, United Kingdom

    Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom

    School of Psychology, Cardiff University, Cardiff, United Kingdom
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  • Jeremy Hall
    Affiliations
    Neuroscience and Mental Health Research Institute, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff, United Kingdom

    Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, United Kingdom
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  • Magnus O. Ulfarsson
    Affiliations
    deCODE genetics/Amgen, Reykjavik, Iceland

    Faculty of Electrical and Computer Engineering, University of Iceland, Reykjavik, Iceland
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  • G. Bragi Walters
    Affiliations
    deCODE genetics/Amgen, Reykjavik, Iceland

    Faculty of Medicine, University of Iceland, Reykjavik, Iceland
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  • Hreinn Stefansson
    Affiliations
    deCODE genetics/Amgen, Reykjavik, Iceland
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  • Kari Stefansson
    Affiliations
    deCODE genetics/Amgen, Reykjavik, Iceland

    Faculty of Medicine, University of Iceland, Reykjavik, Iceland
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  • Author Footnotes
    1 DEJL and XC contributed equally to this work as joint senior authors.
    David E.J. Linden
    Footnotes
    1 DEJL and XC contributed equally to this work as joint senior authors.
    Affiliations
    Neuroscience and Mental Health Research Institute, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff, United Kingdom

    School for Mental Health and Neuroscience, Department of Psychiatry and Neuropsychology, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, the Netherlands
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  • Author Footnotes
    1 DEJL and XC contributed equally to this work as joint senior authors.
    Xavier Caseras
    Correspondence
    Xavier Caseras, Ph.D.
    Footnotes
    1 DEJL and XC contributed equally to this work as joint senior authors.
    Affiliations
    Neuroscience and Mental Health Research Institute, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff, United Kingdom
    Search for articles by this author
  • Author Footnotes
    1 DEJL and XC contributed equally to this work as joint senior authors.
Open AccessPublished:March 02, 2021DOI:https://doi.org/10.1016/j.biopsych.2021.02.969

      Abstract

      Background

      Copy number variations at the 15q11.2 BP1-BP2 locus are present in 0.5%–1.0% of the population, and the deletion is associated with several neurodevelopmental disorders. Previously, we showed a reciprocal effect of 15q11.2 copy number variation on fractional anisotropy, with widespread increases in deletion carriers. We aim to expand these findings using a larger sample of participants (N = 29,166) and higher resolution imaging and by examining the implications for cognitive performance.

      Methods

      Diffusion tensor imaging measures from participants with no neurological or psychiatric diagnoses were obtained from the UK Biobank database. We compared 15q11.2 BP1-BP2 deletion (n = 102) and duplication (n = 113) carriers to a large cohort of control individuals with no neuropsychiatric copy number variants (n = 28,951). Additionally, we assessed how changes in white matter mediated the association between carrier status and cognitive performance.

      Results

      Deletion carriers showed increases in fractional anisotropy in the internal capsule and cingulum and decreases in the posterior thalamic radiation compared with both duplication carriers and control subjects (who had intermediate values). Compared with control subjects, deletion carriers had lower scores across cognitive tasks, which were partly influenced by white matter. Reduced fractional anisotropy in the posterior thalamic radiation partially contributed to worse cognitive performance in deletion carriers.

      Conclusions

      These results, together with our previous findings, provide convergent evidence for an effect of 15q11.2 BP1-BP2 on white matter microstructure, this being more pronounced in deletion carriers. Additionally, changes in white matter were found to partially mediate cognitive ability in deletion carriers, providing a link between white matter changes in 15q11.2 BP1-BP2 carriers and cognitive function.

      Keywords

      Several copy number variants (CNVs) are associated with neurodevelopmental disorders (NDDs) in genome-wide studies, including intellectual disability, autism spectrum disorder (ASD), epilepsy, and schizophrenia (
      • Kirov G.
      CNVs in neuropsychiatric disorders.
      ,
      • Marshall C.R.
      • Howrigan D.P.
      • Merico D.
      • Thiruvahindrapuram B.
      • Wu W.
      • Greer D.S.
      • et al.
      Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects.
      ,
      • Coe B.P.
      • Witherspoon K.
      • Rosenfeld J.A.
      • van Bon B.W.M.
      • Vulto-van Silfhout A.T.
      • Bosco P.
      • et al.
      Refining analyses of copy number variation identifies specific genes associated with developmental delay.
      ). Altered white matter is common in many NDDs and has been shown to mediate core cognitive deficits in schizophrenia (
      • Kochunov P.
      • Coyle T.R.
      • Rowland L.M.
      • Jahanshad N.
      • Thompson P.M.
      • Kelly S.
      • et al.
      Association of white matter with core cognitive deficits in patients with schizophrenia.
      ,
      • Karbasforoushan H.
      • Duffy B.
      • Blackford J.U.
      • Woodward N.D.
      Processing speed impairment in schizophrenia is mediated by white matter integrity.
      ). However, whether alterations in white matter microstructure are associated with these CNVs and can explain—at least partly—cognitive deficits in carriers of the risk variants is not yet fully understood.
      The chromosome 15q11-13 region contains five breakpoints (BPs) that can give rise to CNVs (
      • Takumi T.
      • Tamada K.
      CNV biology in neurodevelopmental disorders.
      ). Deletions and duplications at 15q11.2 BP1-BP2 are the most prevalent in humans, being present in 0.5%–1.0% of the general population (
      • Stefansson H.
      • Meyer-Lindenberg A.
      • Steinberg S.
      • Magnusdottir B.
      • Morgen K.
      • Arnarsdottir S.
      • et al.
      CNVs conferring risk of autism or schizophrenia affect cognition in controls.
      ,
      • Crawford K.
      • Bracher-Smith M.
      • Owen D.
      • Kendall K.M.
      • Rees E.
      • Pardiñas A.F.
      • et al.
      Medical consequences of pathogenic CNVs in adults: Analysis of the UK Biobank.
      ). Deletions are associated with developmental and motor delays (
      • Butler M.G.
      Clinical and genetic aspects of the 15q11.2 BP 1–BP 2 microdeletion disorder.
      ), as well as increased susceptibility to attention-deficit/hyperactivity disorder, ASD, schizophrenia, epilepsy (
      • Kirov G.
      CNVs in neuropsychiatric disorders.
      ,
      • Cox D.M.
      • Butler M.G.
      The 15q11.2 BP1–BP2 microdeletion syndrome: A review.
      ), and congenital heart disease (
      • Williams S.G.
      • Nakev A.
      • Guo H.
      • Frain S.
      • Tenin G.
      • Liakhovitskaia A.
      • et al.
      Association of congenital cardiovascular malformation and neuropsychiatric phenotypes with 15q11.2 (BP1–BP2) deletion in the UK Biobank.
      ,
      • Geng J.
      • Picker J.
      • Zheng Z.
      • Zhang X.
      • Wang J.
      • Hisama F.
      • et al.
      Chromosome microarray testing for patients with congenital heart defects reveals novel disease causing loci and high diagnostic yield.
      ,
      • Glessner J.T.
      • Bick A.G.
      • Ito K.
      • Homsy J.
      • Rodriguez-Murillo L.
      • Fromer M.
      • et al.
      Increased frequency of de novo copy number variants in congenital heart disease by integrative analysis of single nucleotide polymorphism array and exome sequence data.
      ), whereas the pathogenicity of the corresponding duplication is less clear in population samples, where a significant risk for NDDs has not been established (
      • Kirov G.
      CNVs in neuropsychiatric disorders.
      ,
      • Coe B.P.
      • Witherspoon K.
      • Rosenfeld J.A.
      • van Bon B.W.M.
      • Vulto-van Silfhout A.T.
      • Bosco P.
      • et al.
      Refining analyses of copy number variation identifies specific genes associated with developmental delay.
      ) despite its link to neurodevelopmental phenotypes in clinical samples (
      • Burnside R.D.
      • Pasion R.
      • Mikhail F.M.
      • Carroll A.J.
      • Robin N.H.
      • Youngs E.L.
      • et al.
      Microdeletion/microduplication of proximal 15q11.2 between BP1 and BP2: A susceptibility region for neurological dysfunction including developmental and language delay.
      ,
      • van der Zwaag B.
      • Staal W.G.
      • Hochstenbach R.
      • Poot M.
      • Spierenburg H.A.
      • de Jonge M.V.
      • et al.
      A co-segregating microduplication of chromosome 15q11.2 pinpoints two risk genes for autism spectrum disorder.
      ). Carriers of the 15q11.2 BP1-BP2 deletion, unaffected by a diagnosed NDD, show lower cognitive function than noncarrier control subjects (
      • Williams S.G.
      • Nakev A.
      • Guo H.
      • Frain S.
      • Tenin G.
      • Liakhovitskaia A.
      • et al.
      Association of congenital cardiovascular malformation and neuropsychiatric phenotypes with 15q11.2 (BP1–BP2) deletion in the UK Biobank.
      ,
      • van der Meer D.
      • Sønderby I.E.
      • Kaufmann T.
      • Walters G.B.
      • Abdellaoui A.
      • et al.
      Writing Committee for the ENIGMA-CNV Working Group
      Association of copy number variation of the 15q11.2 BP1-BP2 region with cortical and subcortical morphology and cognition.
      ), as well as a higher prevalence of dyslexia and dyscalculia (
      • Stefansson H.
      • Meyer-Lindenberg A.
      • Steinberg S.
      • Magnusdottir B.
      • Morgen K.
      • Arnarsdottir S.
      • et al.
      CNVs conferring risk of autism or schizophrenia affect cognition in controls.
      ,
      • Ulfarsson M.O.
      • Walters G.B.
      • Gustafsson O.
      • Steinberg S.
      • Silva A.
      • Doyle O.M.
      • et al.
      15q11.2 CNV affects cognitive, structural and functional correlates of dyslexia and dyscalculia.
      ), whereas carriers of the corresponding duplication perform similarly to control subjects on many cognitive tests (
      • van der Meer D.
      • Sønderby I.E.
      • Kaufmann T.
      • Walters G.B.
      • Abdellaoui A.
      • et al.
      Writing Committee for the ENIGMA-CNV Working Group
      Association of copy number variation of the 15q11.2 BP1-BP2 region with cortical and subcortical morphology and cognition.
      ,
      • Ulfarsson M.O.
      • Walters G.B.
      • Gustafsson O.
      • Steinberg S.
      • Silva A.
      • Doyle O.M.
      • et al.
      15q11.2 CNV affects cognitive, structural and functional correlates of dyslexia and dyscalculia.
      ).
      The 15q11.2 BP1-BP2 interval comprises four genes: NIPA1, NIPA2, CYFIP1, and TUBGCP5 (
      • Chai J.H.
      • Locke D.P.
      • Greally J.M.
      • Knoll J.H.M.
      • Ohta T.
      • Dunai J.
      • et al.
      Identification of four highly conserved genes between breakpoint hotspots BP1 and BP2 of the Prader-Willi/Angelman syndromes deletion region that have undergone evolutionary transposition mediated by flanking duplicons.
      ). These genes are expressed in the central nervous system and have been individually associated with multiple disorders: NIPA1 with autosomal-dominant hereditary spastic paraplegia (
      • Rainier S.
      • Chai J.H.
      • Tokarz D.
      • Nicholls R.D.
      • Fink J.K.
      NIPA1 gene mutations cause autosomal dominant hereditary spastic paraplegia (SPG6).
      ), NIPA2 with childhood absence epilepsy (
      • Xie H.
      • Zhang Y.
      • Zhang P.
      • Wang J.
      • Wu Y.
      • Wu X.
      • et al.
      Functional study of NIPA2 mutations identified from the patients with childhood absence epilepsy.
      ), TUBHGCP5 with attention-deficit/hyperactivity disorder and obsessive-compulsive disorder (
      • Cox D.M.
      • Butler M.G.
      The 15q11.2 BP1–BP2 microdeletion syndrome: A review.
      ), and CYFIP1 with increasing susceptibility to ASD (
      • Toma C.
      • Torrico B.
      • Hervás A.
      • Valdés-Mas R.
      • Tristán-Noguero A.
      • Padillo V.
      • et al.
      Exome sequencing in multiplex autism families suggests a major role for heterozygous truncating mutations.
      ) and schizophrenia (
      • Tam G.W.C.
      • van de Lagemaat L.N.
      • Redon R.
      • Strathdee K.E.
      • Croning M.D.R.
      • Malloy M.P.
      • et al.
      Confirmed rare copy number variants implicate novel genes in schizophrenia.
      ). A recent report investigated protein-protein interactions of the four genes in this region and found that they interact with each other and that their predicted functions encompass crucial biological processes that are important for normal neuronal development, plasticity, and function (
      • Rafi S.K.
      • Butler M.G.
      The 15q11.2 BP1-BP2 microdeletion (Burnside-Butler) syndrome: In silico analyses of the four coding genes reveal functional associations with neurodevelopmental phenotypes.
      ).
      Using diffusion tensor imaging (DTI), we have previously shown an association between 15q11.2 BP1-BP2 CNV dosage and altered white matter microstructure in an Icelandic sample (
      • Silva A.I.
      • Ulfarsson M.O.
      • Stefansson H.
      • Gustafsson O.
      • Walters G.B.
      • Linden D.E.J.
      • et al.
      Reciprocal white matter changes associated with copy number variation at 15q11.2 BP1-BP2: A diffusion tensor imaging study.
      ). We found widespread increases of fractional anisotropy (FA) in deletion carriers relative to duplication carriers, with noncarrier control subjects showing intermediate values, and the largest effects were observed in the posterior limb of the internal capsule. The Icelandic gene pool is less heterogeneous than that of most European populations (
      • Helgason A.
      • Nicholson G.
      • Stefánsson K.
      • Donnelly P.
      A reassessment of genetic diversity in Icelanders: Strong evidence from multiple loci for relative homogeneity caused by genetic drift.
      ), facilitating the reduction of background noise caused by genetic variation (
      • Zeggini E.
      Using genetically isolated populations to understand the genomic basis of disease.
      ) but arguably also raising concerns about the replicability of these findings in more genetically diverse, heterogeneous populations (
      • Austin M.A.
      • Harding S.
      • McElroy C.
      Genebanks: A comparison of eight proposed international genetic databases.
      ).
      The aim of this study was to expand our previous findings to a more heterogeneous European population, using a bigger sample and higher resolution imaging, and to further investigate the potential mediation effects of white matter changes on the association between 15q11.2 BP1-BP2 and cognitive performance. To this end, we used a subsample of participants (∼29,000) from the UK Biobank for whom DTI-derived measures, along with genetic data, were available. Based on our previous findings, we hypothesized a dose-effect association between 15q11.2 BP1-BP2 carrier status and DTI-based white matter measures, with greater effects in deletion carriers. We also predicted white matter changes to mediate the association between this CNV and cognitive performance in deletion carriers.

      Methods and Materials

      Participants

      A subsample of participants from the UK Biobank (www.ukbiobank.ac.uk) was used in this study. Ethical approval was granted by the North West Multi-Centre Ethics committee, and all subjects provided informed consent to participate in the UK Biobank project. Data were released to Cardiff University after application to the UK Biobank (project ref. 17044).
      To avoid potential confounding from population stratification, we only selected participants who self-reported as white British or Irish descent and for whom white British and Irish ancestry was confirmed, using the two first principal components provided by the UK Biobank (
      • Legge S.E.
      • Jones H.J.
      • Kendall K.M.
      • Pardiñas A.F.
      • Menzies G.
      • Bracher-Smith M.
      • et al.
      Association of genetic liability to psychotic experiences with neuropsychotic disorders and traits.
      ) (Figure S1 in Supplement 1) (73,126 participants removed). Furthermore, to avoid confounding effects of disease, only participants with no personal history—based on self-reported diagnosis from a doctor at any assessment visit or existing hospital records—of neuropsychiatric disorders (i.e., schizophrenia, psychosis, ASD, dementia, or intellectual disability) or medical/neurological conditions that could impact white matter (i.e., alcohol or other substance dependency, Parkinson’s disease, Alzheimer’s disease, multiple sclerosis, or other neurodegenerative conditions) were selected (37,176 participants removed). After applying these exclusions, 392,340 participants remained (the number of participants excluded per carrier group and condition is presented in Table S1 in Supplement 2).

      Genotyping, CNV Calling, and CNV Quality Control

      DNA extraction and processing workflow are described at https://biobank.ctsu.ox.ac.uk/crystal/crystal/docs/genotyping_sample_workflow.pdf. CNV calling was performed by Kendall et al. (
      • Kendall K.M.
      • Rees E.
      • Escott-Price V.
      • Einon M.
      • Thomas R.
      • Hewitt J.
      • et al.
      Cognitive performance among carriers of pathogenic copy number variants: Analysis of 152,000 UK Biobank subjects.
      ), and quality control parameters are briefly explained in Supplemental Methods in Supplement 1. Carriers of CNVs at the 15q11.2 BP1-BP2 locus and participants with no neurodevelopmental CNVs (NoCNV) were selected. For the NoCNV group, we selected participants that carried none of the 93 CNVs (Table S2 in Supplement 2) that have previously been associated with NDDs (
      • Coe B.P.
      • Witherspoon K.
      • Rosenfeld J.A.
      • van Bon B.W.M.
      • Vulto-van Silfhout A.T.
      • Bosco P.
      • et al.
      Refining analyses of copy number variation identifies specific genes associated with developmental delay.
      ,
      • Wang K.
      • Li M.
      • Hadley D.
      • Liu R.
      • Glessner J.
      • Grant S.F.A.
      • et al.
      PennCNV: An integrated hidden Markov model designed for high-resolution copy number variation detection in whole-genome SNP genotyping data.
      ,
      • Dittwald P.
      • Gambin T.
      • Szafranski P.
      • Li J.
      • Amato S.
      • Divon M.Y.
      • et al.
      NAHR-mediated copy-number variants in a clinical population: Mechanistic insights into both genomic disorders and Mendelizing traits.
      ). The 15q11.2 BP1-BP2 interval was manually inspected to confirm that it included the key genes within the region (Table S3 in Supplement 2). We found 1468 15q11.2 BP1-BP2 deletion carriers, 1752 duplication carriers, and 358,257 NoCNV carriers in the remaining sample after exclusions and quality control.

      DTI Data

      We used standard DTI measures made available by the UK Biobank. Imaging protocols can be found in brain magnetic resonance imaging documentation (http://biobank.ctsu.ox.ac.uk/crystal/crystal/docs/brain_mri.pdf). DTI data were acquired using a multishell approach with two b-values (b = 1000 and 2000 s/mm2). For each diffusion-weighted shell, 50 diffusion-encoding directions were acquired. Tensor fitting utilizes b = 1000 s/mm2 data, leading to the generation of FA, axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD) maps. DTI maps were used in Tract-Based Spatial Statistics (TBSS) processing, and TBSS-derived measures were computed by averaging the skeletonized images of each DTI map within a set of 48 standard-space tract masks defined by the JHU White Matter Atlas (ICBM-DTI-81) (
      • Mori S.
      • Wakana S.
      • van Zijl P.C.M.
      • Nagae-Poetscher L.M.
      MRI Atlas of Human White Matter.
      ).
      DTI data were available for 29,978 participants in the UK Biobank; of those, 102 were 15q11.2 BP1-BP2 deletion carriers, 113 were duplication carriers, and 28,951 were NoCNV carriers. Participants were aged between 40 and 70 years, and the numbers of females and males were similar in each group. Demographic information is provided in Table 1.
      Table 1Demographic Characteristics of Individuals With Neuroimaging Data Available From the UK Biobank After Exclusions
      Demographic Characteristics15q11.2 BP1-BP2 CNVsTest Statistic
      Statistical differences in sex and age between each group (deletion, NoCNV, and duplication) were assessed using χ2 and analysis of variance, respectively.
      p Value
      DeletionNoCNVDuplication
      UK BiobankTotal10228,951113
      Male, n (%)55 (54%)13,623 (47%)52 (46%)χ22 = 1.97.37
      Age, mean (SD); [range]55.4 (7.3); [40–68]54.9 (7.4); [40–70]54.8 (7.2); [40–69]F2 = 0.42.5
      deCODE (
      • Silva A.I.
      • Ulfarsson M.O.
      • Stefansson H.
      • Gustafsson O.
      • Walters G.B.
      • Linden D.E.J.
      • et al.
      Reciprocal white matter changes associated with copy number variation at 15q11.2 BP1-BP2: A diffusion tensor imaging study.
      )
      Total301927
      Male, n (%)14 (47%)12 (63%)12 (44%)χ22 = 1.78.41
      Age, mean (SD); [range]42.8 (12.5); [21–65]38.9 (10.6); [22–59]43.5 (13.5); [22–65]F2 = 0.026.87
      See Methods and Materials for exclusion criteria. Details from the Icelandic sample (deCODE), used in our previous study (
      • Silva A.I.
      • Ulfarsson M.O.
      • Stefansson H.
      • Gustafsson O.
      • Walters G.B.
      • Linden D.E.J.
      • et al.
      Reciprocal white matter changes associated with copy number variation at 15q11.2 BP1-BP2: A diffusion tensor imaging study.
      ), are shown for comparison.
      CNV, copy number variant; NoCNV, no pathogenic CNVs.
      a Statistical differences in sex and age between each group (deletion, NoCNV, and duplication) were assessed using χ2 and analysis of variance, respectively.
      To avoid the potential effect of extreme values that could have resulted from poor data quality or processing problems, outlier values of FA, AD, RD, and MD, defined as values ± 2.5 SDs from the group mean, were removed from the analyses. Outlier identification was run individually for each white matter tract and within each carrier group. The number of data points excluded per tract and carrier group are presented in Table S4 in Supplement 2. Overall, no carrier group had a significant excess of outlier data points compared with the other groups.
      The mean TBSS-derived measures (FA, AD, RD, and MD) from 30 white matter tracts were considered for analyses (Table 2). These included the tracts analyzed in our previous study (
      • Silva A.I.
      • Ulfarsson M.O.
      • Stefansson H.
      • Gustafsson O.
      • Walters G.B.
      • Linden D.E.J.
      • et al.
      Reciprocal white matter changes associated with copy number variation at 15q11.2 BP1-BP2: A diffusion tensor imaging study.
      ) plus other regions recently highlighted because of their association with psychiatric disorders (
      • Koshiyama D.
      • Fukunaga M.
      • Okada N.
      • Morita K.
      • Nemoto K.
      • Usui K.
      • et al.
      White matter microstructural alterations across four major psychiatric disorders: Mega-analysis study in 2937 individuals.
      ).
      Table 2The 30 White Matter Tracts Selected for This Study and Corresponding Abbreviations
      White Matter TractsAbbreviation
      Genu Corpus CallosumGenuCC
      Body Corpus CallosumBodyCC
      Splenium Corpus CallosumSpleniumCC
      Body of the FornixFornix
      Corticospinal Tract—Right and LeftCST_R; CST_L
      Anterior Limb of the Internal Capsule—Right and LeftALIC_R; ALIC_L
      Posterior Limb of the Internal Capsule—Right and LeftPLIC_R; PLIC_L
      Anterior Corona Radiata—Right and LeftACR_R; ACR_L
      Superior Corona Radiata—Right and LeftSCR_R; SCR_L
      Posterior Corona Radiata—Right and LeftPCR_R; PCR_L
      Posterior Thalamic Radiation—Right and LeftPTR_R; PTR_L
      Sagittal Stratum (Includes Inferior Longitudinal Fasciculus)—Right and LeftSStratum_R; SStratum_L
      External Capsule—Right and LeftExtC_R; ExtC_L
      Cingulum (Cingulate Gyrus Portion)—Right and LeftCing_CG_R; Cing_CG_L
      Cingulum (Hippocampus Portion)—Right and LeftCing_HIP_R; Cing_HIP_L
      Superior Longitudinal Fasciculus—Right and LeftSLF_R; SLF_L
      Uncinate Fasciculus—Right and LeftUnc_R; Unc_L

      Cognitive Data

      Participants in the UK Biobank also underwent a series of cognitive tests. We evaluated the performance on seven cognitive tasks that had been performed by at least 10% of the participants: the pairs matching, reaction time, fluid intelligence, digit span, symbol digit substitution, and trail making A and B tasks. Cognitive measures were normally distributed and standardized following a previously published approach (
      • Kendall K.M.
      • Rees E.
      • Escott-Price V.
      • Einon M.
      • Thomas R.
      • Hewitt J.
      • et al.
      Cognitive performance among carriers of pathogenic copy number variants: Analysis of 152,000 UK Biobank subjects.
      ), detailed in Supplemental Methods in Supplement 1. All cognitive measures were transformed so that lower values represented poorer performance. Table 3 describes the sample sizes used for each task in our neuroimaging sample. Because cognitive data are available for many more participants in the UK Biobank than those with neuroimaging data, we also report an extended analysis considering the full sample in Table S6 in Supplement 2.
      Table 3Effects of 15q11.2 BP1-BP2 Copy Number Variation on Cognitive Performance in UK Biobank Participants for Whom DTI Data Were Available
      Effects15q11.2 BP1-BP2 CNVsDeletion vs NoCNVDuplication vs NoCNVDosage
      Deletion, nNoCNV, nDuplication, nCohen’s d (SE)p ValuepFDRCohen’s d (SE)p ValuepFDRF Statisticp Value
      Pairs Matching10228,599112−0.04 (0.10).63.800.01 (0.10).88.9F2,28805 = 0.17.8
      Reaction Time10228,898113−0.32 (0.10).001.01
      p < .05 after FDR correction.
      0.17 (0.10).07.1F2,29105 = 7.14.0008
      Fluid Intelligence8926,690108−0.32 (0.10).003.01
      p < .05 after FDR correction.
      −0.04 (0.10).71.8F2,26879 = 4.33.01
      Digit Span7119,79981−0.29 (0.12).02.05−0.1 (0.12).38.5F2,19943 = 3.27.04
      Symbol Substitution6215,12755−0.36 (0.13).005.02
      p < .05 after FDR correction.
      0.13 (0.13).33.5F2,15236 = 4.79.008
      Trail Making A5213,53848−0.29 (0.14).04.09−0.04 (0.14).80.8F2,13630 = 2.52.08
      Trail Making B5213,53848−0.40 (0.14).004.02
      p < .05 after FDR correction.
      0.19 (0.14).20.3F2,13630 = 5.67.003
      Group differences were assessed using ANOVA followed by post hoc pairwise comparisons. Both uncorrected and FDR-corrected p values are shown.
      ANOVA, analysis of variance; BP, breakpoint; CNV, copy number variant; FDR, false discovery rate; NoCNV, no pathogenic CNVs.
      a p < .05 after FDR correction.

      Statistical Analyses

      Statistical analyses were performed in R V3.6.3 (R Foundation). CNV group effects were examined via analysis of variance, including age, sex, and handedness as covariates. For brain measures, we also included brain size (total gray matter + white matter volumes) as a covariate. Following this, post hoc pairwise comparisons were performed to measure differences between groups (deletion vs. NoCNV, duplication vs. NoCNV, and deletion vs. duplication). We used the Benjamini-Hochberg false discovery rate (p < .05) to account for multiple testing (
      • Benjamini Y.
      • Hochberg Y.
      Controlling the false discovery rate: A practical and powerful approach to multiple testing.
      ), for a total of 360 tests (30 tracts × 4 TBSS-derived measures × 3 group comparisons) in the case of imaging data and a total of 21 tests (7 cognitive test × 3 group comparisons) in the case of cognitive data. The interactions between copy number and age and between copy number and sex were also assessed. We repeated the analyses without excluding participants with neurological/psychiatric conditions (Tables S5 and S6 in Supplement 2).
      Cohen’s d effect sizes were calculated for the pairwise comparisons. Adjusted values for each group were used, regressing out the effects of age, sex, handedness, and brain volume using linear regression. Effect sizes across TBSS-derived measures for each comparison are shown in Figures S2–S4 in Supplement 1. Cohen classified effect sizes as negligible (d < 0.2), small (0.2 < d < 0.5), medium (0.5 < d <0.8), and large (d > 0.8) (
      • Cohen J.
      Chapter 1: The concepts of power analysis.
      ).
      To best examine the concordance between our current findings in the UK Biobank sample and our previous findings in the Icelandic deCODE sample (
      • Silva A.I.
      • Ulfarsson M.O.
      • Stefansson H.
      • Gustafsson O.
      • Walters G.B.
      • Linden D.E.J.
      • et al.
      Reciprocal white matter changes associated with copy number variation at 15q11.2 BP1-BP2: A diffusion tensor imaging study.
      ), we plotted the effect sizes from both samples using forest plots. To facilitate the comparison, we recalculated the effect sizes from the Icelandic sample using adjusted values for age, sex, and brain volume, and only white matter tracts showing group differences in either study are shown (Figures S5–S7 in Supplement 1).
      Mediation analysis was performed to test the hypothesis that 15q11.2 BP1-BP2 CNV effects on cognition are mediated by white matter abnormalities. Tracts showing a significant association between FA and carrier status were considered, as well as cognitive tasks that were significantly affected in carriers when compared with NoCNV carriers. Linear regression was used to look at overall effects of white matter on cognitive tasks (including all deletion and duplication carriers). Mediation analysis was conducted using the mediation package version 4.4.7 in R (http://CRAN.R-project.org/package=mediation), which uses structural equation modeling. We report the proportion of the total effect of copy number on cognitive performance mediated by FA, with p values calculated through quasi-Bayesian approximation using 5000 simulations. Age, sex, handedness, and brain volume were included as covariates. False discovery rate correction was again applied to account for multiple testing, in this case accounting for 28 tests (4 cognitive measures × 7 tracts).

      Results

      Group Differences on TBSS-Derived Measures

      15q11.2 BP1-BP2 deletion carriers showed increased FA relative to duplication carriers in ALIC_L, PLIC_R, PLIC_L, Cing_CG_R, Cing_HIP_R, and Cing_HIP_L and decreased FA in fornix and PTR_R (see Figure 1 and Table S7 in Supplement 2 for statistics). Deletion carriers also showed increased FA in ALIC_L, PLIC_L, and Cing_HIP_L and decreased FA in PTR_R when compared with NoCNV carriers. Additionally, deletion carriers showed significant decreases in MD in BodyCC and Unc_L and significant decreases in AD in BodyCC and SpleniumCC when compared with NoCNV carriers. 15q11.2 BP1-BP2 duplication carriers showed reduced FA in Cing_CG_R, Cing_HIP_R, and Cing_HIP_L compared with NoCNV carriers.
      Figure thumbnail gr1
      Figure 1(A) Boxplots showing the effects of 15q11.2 BP1-BP2 copy number variation on Tract-Based Spatial Statistics–derived measures. Group differences between deletion (n = 102), duplication (n = 113), and no pathogenic copy number variant (NoCNV; n = 28,951) carriers were assessed with an analysis of variance followed by post hoc pairwise comparisons. Here, only white matter tracts showing significant group differences after false discovery rate correction for multiple comparisons are shown. Statistics are documented in in . ∗p < .05, ∗∗p < .01, ∗∗∗p < .001. (B) Glass brain representation of the white matter regions defined by the JHU White Matter Atlas (ICBM-DTI-81).
      The effect sizes for FA were overall small (Cohen’s d < 0.5) when comparing carriers to noncarriers. Larger effects were found when comparing deletion to duplication carriers, these being of medium size (Cohen’s d > 0.5) for Cing_HIP_R, and Cing_HIP_L (Table S7 in Supplement 2), the latter showing a significant dosage effect with deletion and duplication carriers differing from NoCNV carriers in opposing directions. Diverging bar plots showing effect sizes for all 30 white matter tracts considered are shown in Figures S8–S11 in Supplement 1.
      No significant CNV × age and CNV × sex interactions were found after multiple testing correction (see Supplemental Findings in Supplement 1 and Tables S8 and S9 in Supplement 2).
      In the UK Biobank imaging sample, we found 4 deletion and 3 duplication carriers who carried an additional damaging CNV. We repeated the analysis removing these participants, which did not alter our results.

      Cognitive Performance in 15q11.2 CNV Carriers

      In our neuroimaging sample, deletion carriers showed poorer performance on reaction time, fluid intelligence, symbol substitution, and trail making B tasks, whereas duplication carriers achieved a similar level of performance as NoCNV carriers (Table 3). This was also true when considering all participants with cognitive data (Table S6 in Supplement 2), where deletion carriers showed poorer performance in pairs matching, reaction time, fluid intelligence, digit span, symbol substitution, and trail making B tasks; duplication carriers showed poorer performance only in pairs matching task and no effects on other tasks. No significant CNV × age or CNV × sex interactions were observed for cognitive performance (see Supplemental Findings in Supplement 1 and Tables S8 and S9 in Supplement 2).
      Because FA is the metric more commonly used in DTI studies and the one more widely associated with 15q11.2 BP1-BP2 carrier status here, we focused our mediation analysis only on this measure. As described above, four white matter tracts (ALIC_L, PLIC_L, PTR_R, and Cing_HIP_L) showed FA changes in deletion carriers and three tracts (Cing_CG_R, Cing_HIP_R, and Cing_HIP_L) in duplication carriers when compared with NoCNV carriers. Therefore, the effects of these tracts on fluid intelligence, reaction time, symbol substitution, and trail making B task performance were tested. FA variation in all these tracts was overall significantly associated with cognitive task performance, where increases in FA were associated with better performance (Table 4). Associations between cognitive tests and FA in regions for each CNV carrier status can be seen in Figures S14–S17 in Supplement 1. No significant CNV × FA interactions were observed in cognitive performance.
      Table 4Mediation Analysis Showing the Proportion of the Mediated Effect of FA on the Total Effect of 15q11.2 BP1-BP2 CNV on Reaction Time, Fluid Intelligence, Symbol Substitution, and Trail Making B
      WM TractsPath BMediation Effects
      β (SE)pFDRProportion Mediated (CI)p ValuepFDRComparison
      Reaction Time
      ALIC_L.03 (.006)3.67 × 10−7
      p < .05 after FDR correction.
      −0.029 (−0.09 to −0.01).004.03
      p < .05 after FDR correction.
      Del vs. NoCNV
      PLIC_L.003 (.006).6−0.003 (−0.02 to 0.01).51.6
      PTR_R.03 (.006)6.35 × 10−5
      p < .05 after FDR correction.
      0.024 (0.008 to 0.07).003.03
      p < .05 after FDR correction.
      Cing_HIP_L.02 (.006).003
      p < .05 after FDR correction.
      −0.022 (−0.07 to −0.01).002.03
      p < .05 after FDR correction.
      Cing_CG_R.04 (.006)1.32 × 10−11
      p < .05 after FDR correction.
      −0.07 (−0.57 to 0.26).07.1Dup vs. NoCNV
      Cing_HIP_R.03 (.006)2.6 × 10−5
      p < .05 after FDR correction.
      −0.052 (−0.41 to 0.2).07.1
      Cing_HIP_L.02 (.006).003
      p < .05 after FDR correction.
      −0.03 (−0.3 to 0.16).09.2
      Fluid Intelligence
      ALIC_L.03 (.006)4.34 × 10−7
      p < .05 after FDR correction.
      −0.02 (−0.07 to 0).06.1Del vs. NoCNV
      PLIC_L.02 (.006).006
      p < .05 after FDR correction.
      −0.012 (−0.05 to 0).03.09
      PTR_R.05 (.006)2.97 × 10−12
      p < .05 after FDR correction.
      0.044 (0.015 to 0.14).004.03
      p < .05 after FDR correction.
      Cing_HIP_L.02 (.006).004
      p < .05 after FDR correction.
      −0.023 (−0.07 to −0.01).007.03
      p < .05 after FDR correction.
      Cing_CG_R.01 (.006).060.01 (−0.59 to 0.6).9.9Dup vs. NoCNV
      Cing_HIP_R.03 (.006)2.75 × 10−5
      p < .05 after FDR correction.
      0.037 (−1.33 to 1.66).9.9
      Cing_HIP_L.02 (.006).004
      p < .05 after FDR correction.
      −0.03 (−0.88 to 1.05).8.9
      Symbol Substitution
      ALIC_L.04 (.007)3.65 × 10−9
      p < .05 after FDR correction.
      −0.05 (−0.19 to −0.01).009.03
      p < .05 after FDR correction.
      Del vs. NoCNV
      PLIC_L.009 (.007).2−0.006 (−0.04 to 0).2.3
      PTR_R.06 (.007)8.94 × 10−13
      p < .05 after FDR correction.
      0.06 (0.02 to 0.2).006.03
      p < .05 after FDR correction.
      Cing_HIP_L.02 (.008).001
      p < .05 after FDR correction.
      −0.02 (−0.09 to 0).01.04
      p < .05 after FDR correction.
      Cing_CG_R.05 (.008)2.7 × 10−10
      p < .05 after FDR correction.
      −0.13 (−2.31 to 1.6).3.4Dup vs. NoCNV
      Cing_HIP_R.02 (.008).04
      p < .05 after FDR correction.
      −0.03 (−0.55 to 0.35).3.4
      Cing_HIP_L.02 (.008).001
      p < .05 after FDR correction.
      −0.05 (−0.75 to 0.79).3.4
      Trail Making B
      ALIC_L.04 (.008)4.11 × 10−7
      p < .05 after FDR correction.
      −0.06 (−0.25 to −0.02).01.04
      p < .05 after FDR correction.
      Del vs. NoCNV
      PLIC_L.01 (.008).1−0.01 (−0.05 to 0).09.2
      PTR_R.05 (.008)3.65 × 10−9
      p < .05 after FDR correction.
      0.04 (−0.007 to 0.15).02.05
      p < .05 after FDR correction.
      Cing_HIP_L.01 (.008).2−0.01 (−0.05 to 0.01).2.3
      Cing_CG_R.03 (.008).0001
      p < .05 after FDR correction.
      −0.06 (−0.63 to 0.61).2.3Dup vs. NoCNV
      C_HIP_R.003 (.008).7−0.003 (−0.07 to 0.04).7.8
      Cing_HIP_L.01 (.008).2−0.01 (−0.28 to 0.18).4.5
      Negative proportions indicate opposite signs between the mediator (FA) and the total effect (CNV effect on cognitive measure). The linear regression (Path B) shows the overall effects of white matter on cognition (including all deletion and duplication carriers). Both uncorrected and corrected (FDR) p values are shown.
      CI, confidence interval; CNV, copy number variant; Del, deletion; Dup, duplication; FA, fractional anisotropy; FDR, false discovery rate; NoCNV, no pathogenic copy number variant; WM, white matter. See Table 2 for white matter tract abbreviations.
      a p < .05 after FDR correction.
      We found that ALIC_L, PTR_R, and Cing_HIP_L partially mediated cognitive performance in deletion carriers. Decreased FA in PTR_R was found to partially mediate cognitive performance on all four cognitive tasks, accounting for between 2.4% and 6% of the association between carrier status and cognitive performance (Table 4). Increased FA in ALIC_L in deletion carriers was associated with higher scores in reaction time, symbol substitution, and trail making B tasks, removing 2.9%, 5%, and 6% of the total effect of carrier status on each of these tasks, respectively. Similarly, increased FA in Cing_HIP_L in deletion carriers removed 2.2%, 2.3%, and 2% of the total effect of carrier status on reaction time, fluid intelligence score, and symbol substitution, respectively.

      Discussion

      To our knowledge, this is the largest study to date investigating the effects of the 15q11.2 BP1-BP2 CNV on white matter microstructure, as well as the first study examining how these effects are associated with cognitive ability. Using a large sample from the UK Biobank, we found more prominent differences between deletion and NoCNV carriers than between duplication and NoCNV carriers. These results are in line with our previous findings in an Icelandic sample, also showing larger effect sizes in deletion carriers (
      • Silva A.I.
      • Ulfarsson M.O.
      • Stefansson H.
      • Gustafsson O.
      • Walters G.B.
      • Linden D.E.J.
      • et al.
      Reciprocal white matter changes associated with copy number variation at 15q11.2 BP1-BP2: A diffusion tensor imaging study.
      ). Additionally, we showed that deletion carriers have poorer cognitive performance, which is partially mediated by changes in FA.
      Previous results from our group using an Icelandic sample showed increased FA in deletion carriers in the left inferior longitudinal fasciculus (ILF_L), PCR_L, PTR_R, C_CG_L, ALIC_L, PLIC_R, and PLIC_L compared with duplication carriers, but no significant differences were found between carriers and noncarriers (
      • Silva A.I.
      • Ulfarsson M.O.
      • Stefansson H.
      • Gustafsson O.
      • Walters G.B.
      • Linden D.E.J.
      • et al.
      Reciprocal white matter changes associated with copy number variation at 15q11.2 BP1-BP2: A diffusion tensor imaging study.
      ). Using the UK Biobank sample, we now report significant increased FA in ALIC_L, PLIC_R, and PLIC_L in deletion carriers compared with duplication carriers. Additionally, significant differences between deletion and NoCNV carriers are found in ALIC_L and PLIC_L. ALIC has been shown to be associated with emotion, decision making, cognition, and motivation (
      • Emos M.C.
      • Agarwal S.
      Neuroanatomy, Internal Capsule.
      ), whereas PLIC is an important structure for motor and sensory pathways (
      • Emos M.C.
      • Agarwal S.
      Neuroanatomy, Internal Capsule.
      ). In this study, we investigated the interaction between copy number and age in imaging and cognitive measures. FA age trajectories (Figure S12 in Supplement 1) show a possible CNV × age interaction in ALIC, BodyCC, and SpleniumCC, where FA increases with age in deletion carriers, and differs from the typical gradual reduction of FA with age (
      • Krogsrud S.K.
      • Fjell A.M.
      • Tamnes C.K.
      • Grydeland H.
      • Mork L.
      • Due-Tønnessen P.
      • et al.
      Changes in white matter microstructure in the developing brain—A longitudinal diffusion tensor imaging study of children from 4 to 11 years of age.
      ). However, these interactions were not significant after multiple comparison correction. A younger group (from childhood until adulthood) would be needed to reliably investigate the impact of 15q11.2 BP2-BP2 CNVs on white matter development.
      Current and previous results also showed similar effects (increased FA in deletion carriers compared with duplication carriers) in different portions of the cingulum; significant effects were found on Cing_CG_L in the Icelandic sample and on Cing_CG_R, Cing_HIP_R, and Cing_HIP_L in the UK Biobank sample. In the UK Biobank sample, duplication carriers show significant reduced FA in these three tracts compared with NoCNV carriers. The cingulum connects components of the limbic system, where different portions reflect distinct functions (
      • Jones D.K.
      • Christiansen K.F.
      • Chapman R.J.
      • Aggleton J.P.
      Distinct subdivisions of the cingulum bundle revealed by diffusion MRI fibre tracking: Implications for neuropsychological investigations.
      ). The hippocampal portion is linked to learning and episodic memory. Conversely, deletion carriers show reduced FA and increased RD in the fornix, a major output tract of the hippocampus that is also implicated in memory function. Although not significant, deletion carriers in the Icelandic sample also showed a decrease in FA in this structure (Figure S5 in Supplement 1).
      We found some divergence between our previous and current results. While deletion carriers showed increased FA in PTR_R and ILF_L in the Icelandic sample, they show reduced FA in the UK Biobank sample, with a significant FA reduction in PTR_R when compared with NoCNV carriers (Figure S5 in Supplement 1). Furthermore, when looking at effect sizes in all tracts (Figures S8–S11 in Supplement 1), an overall pattern of increased FA in deletion carriers in the Icelandic sample can be appreciated (the only exceptions being fornix and bilateral CST), whereas in the UK Biobank, the pattern is more heterogeneous. Divergent results could be explained by important differences between the two studies: the UK Biobank sample is considerably larger in size, increasing statistical power to detect true associations; it also represents a more genetically heterogeneous population of an older age than the Icelandic sample. Moreover, UK Biobank applied DTI acquisition protocols with higher resolution, which could also lead to more robust results.
      NDDs have been generally associated with global decreases in FA (
      • Koshiyama D.
      • Fukunaga M.
      • Okada N.
      • Morita K.
      • Nemoto K.
      • Usui K.
      • et al.
      White matter microstructural alterations across four major psychiatric disorders: Mega-analysis study in 2937 individuals.
      ,
      • Fitzsimmons J.
      • Kubicki M.
      • Shenton M.E.
      Review of functional and anatomical brain connectivity findings in schizophrenia.
      ,
      • Rane P.
      • Cochran D.
      • Hodge S.M.
      • Haselgrove C.
      • Kennedy D.N.
      • Frazier J.A.
      Connectivity in autism: A review of MRI connectivity studies.
      ), which contrasts with the findings of increased FA in 15q11.2 BP1-BP2 deletion carriers. This raises the question of how changes in FA relate to cognitive function and risk for disorder in these carriers. In our neuroimaging sample, deletion carriers performed worse during reaction time, fluid intelligence, symbol substitution, and trail making B tasks, whereas duplication carriers performed at a similar level as NoCNV control subjects in all tasks. The same pattern was observed when extending our analyses to all participants with cognitive data available, where additional effects in pairs matching and digit span tasks were seen in deletion carriers (Table S6 in Supplement 2). This pattern of effects is in line with previous studies, where the 15q11.2 BP1-BP2 deletion was reported as being more damaging than duplication for a variety of cognitive tests (
      • Stefansson H.
      • Meyer-Lindenberg A.
      • Steinberg S.
      • Magnusdottir B.
      • Morgen K.
      • Arnarsdottir S.
      • et al.
      CNVs conferring risk of autism or schizophrenia affect cognition in controls.
      ,
      • van der Meer D.
      • Sønderby I.E.
      • Kaufmann T.
      • Walters G.B.
      • Abdellaoui A.
      • et al.
      Writing Committee for the ENIGMA-CNV Working Group
      Association of copy number variation of the 15q11.2 BP1-BP2 region with cortical and subcortical morphology and cognition.
      ).
      Our analyses show that FA in white matter tracts affected by CNV carrier status correlates positively with cognitive performance in reaction time, fluid intelligence, symbol substitution, and trail making B tasks. Mediation analysis revealed that changes in PTR_R partially mediated the effects of deletion in all cognitive tasks, where lower FA in PTR_R in deletion carriers contributed to 2%–6% of the CNV effect across tasks. PTR is known to connect the caudal parts of the thalamus to both the parietal and occipital lobes (
      • George K.
      • Das M.J.
      Neuroanatomy, Thalamocortical Radiations.
      ) and has been previously indicated as the strongest white matter predictor for fluid intelligence (
      • Kievit R.A.
      • Fuhrmann D.
      • Borgeest G.S.
      • Simpson-Kent I.L.
      • Henson R.N.A.
      The neural determinants of age-related changes in fluid intelligence: A pre-registered, longitudinal analysis in UK Biobank.
      ). Conversely, the increased FA seen in ALIC_L and Cing_HIP_L in deletion carriers had the opposite effect on cognition, removing part of the CNV effect on performance. These findings suggest that increased FA in these regions contributes to better cognitive performance in deletion carriers.
      A recent study used data gathered through the Enhancing Neuro Imaging Genetics through Meta Analysis (ENIGMA) consortium (
      • Thompson P.M.
      • Stein J.L.
      • Medland S.E.
      • Hibar D.P.
      • Vasquez A.A.
      • Renteria M.E.
      • et al.
      The ENIGMA Consortium: Large-scale collaborative analyses of neuroimaging and genetic data.
      ) and UK Biobank to determine the effects of the 15q11.2 BP1-BP2 CNV on cortical and subcortical brain morphology. The study reported reduced brain surface area and thicker cortex in deletion carriers, where the significant differences in cortical thickness were more evident in the frontal, cingulate, and parietal lobes. Furthermore, this study found significant mediation effects of total surface area and cortical thickness on fluid intelligence, with similar proportions as the ones reported in this study (
      • van der Meer D.
      • Sønderby I.E.
      • Kaufmann T.
      • Walters G.B.
      • Abdellaoui A.
      • et al.
      Writing Committee for the ENIGMA-CNV Working Group
      Association of copy number variation of the 15q11.2 BP1-BP2 region with cortical and subcortical morphology and cognition.
      ). Taken together, these findings suggest that 15q11.2 BP1-BP2 CNV effects on white and gray matter provide partially complementary effects on cognitive ability.
      Among the four genes in this region, NIPA1 and CYFIP1 are known to be involved in mechanisms that, when dysregulated, have the potential to alter white matter. NIPA1 interacts with the bone morphogenic protein (BMP) receptor type II to inhibit BMP signaling, which contributes to axonal growth, guidance, and differentiation (
      • Tsang H.T.H.
      • Edwards T.L.
      • Wang X.
      • Connell J.W.
      • Davies R.J.
      • Durrington H.J.
      • et al.
      The hereditary spastic paraplegia proteins NIPA1, spastin and spartin are inhibitors of mammalian BMP signalling.
      ). Enhanced BMP signaling was found to cause abnormal distal axonal overgrowth at the presynaptic neuromuscular junction in a Drosophila model (
      • Wang X.
      • Shaw W.R.
      • Tsang H.T.H.
      • Reid E.
      • O’Kane C.J.
      Drosophila spichthyin inhibits BMP signaling and regulates synaptic growth and axonal microtubules.
      ). CYFIP1 is considered a likely contributor to 15q11.2 BP1-BP2–associated phenotypes. Dysregulations in this gene result in alterations in dendritic spine morphology and branching (
      • De Rubeis S.
      • Pasciuto E.
      • Li K.W.
      • Fernández E.
      • Di Marino D.
      • Buzzi A.
      • et al.
      CYFIP1 coordinates mRNA translation and cytoskeleton remodeling to ensure proper dendritic spine formation.
      ,
      • Pathania M.
      • Davenport E.C.
      • Muir J.
      • Sheehan D.F.
      • López-Doménech G.
      • Kittler J.T.
      The autism and schizophrenia associated gene CYFIP1 is critical for the maintenance of dendritic complexity and the stabilization of mature spines.
      ). CYFIP1 interacts in two distinct complexes (
      • De Rubeis S.
      • Pasciuto E.
      • Li K.W.
      • Fernández E.
      • Di Marino D.
      • Buzzi A.
      • et al.
      CYFIP1 coordinates mRNA translation and cytoskeleton remodeling to ensure proper dendritic spine formation.
      )—the WAVE regulatory complex, which regulates actin remodeling during neural wiring (
      • Chen Z.
      • Borek D.
      • Padrick S.B.
      • Gomez T.S.
      • Metlagel Z.
      • Ismail A.M.
      • et al.
      Structure and control of the actin regulatory WAVE complex.
      ), and the CYFIP1-eIF4E complex, which, through interactions with FMRP, regulates translation of FMRP-target messenger RNAs (
      • Napoli I.
      • Mercaldo V.
      • Boyl P.P.
      • Eleuteri B.
      • Zalfa F.
      • De Rubeis S.
      • et al.
      The fragile X syndrome protein represses activity-dependent translation through CYFIP1, a new 4E-BP.
      ). FMRP is the gene product of FMR1, which, when mutated, causes fragile X syndrome, the most common monogenic form of intellectual disability (
      • Lozano R.
      • Rosero C.A.
      • Hagerman R.J.
      Fragile X spectrum disorders.
      ).
      In our previous study, we hypothesized that CYFIP1 could be a primary contributor to white matter changes in 15q11.2 BP1-BP2 CNV carriers. Previous DTI studies have shown increased FA in patients with fragile X syndrome (
      • Hall S.S.
      • Dougherty R.F.
      • Reiss A.L.
      Profiles of aberrant white matter microstructure in fragile X syndrome.
      ,
      • Green T.
      • Barnea-Goraly N.
      • Raman M.
      • Hall S.S.
      • Lightbody A.A.
      • Bruno J.L.
      • et al.
      Specific effect of the fragile-X mental retardation-1 gene (FMR1) on white matter microstructure.
      ), similar to what we observed in 15q11.2 BP1-BP2 deletion carriers, suggesting that these changes could be in part due to disruptions in the CYFIP1-FMRP complex. Recently, we developed a novel Cyfip1-haploinsufficient rat line using CRISPR (clustered regularly interspaced short palindromic repeats)/Cas9 to assess the influence of Cyfip1 on white matter (
      • Silva A.I.
      • Haddon J.E.
      • Syed Y.A.
      • Trent S.
      • Lin T-CE
      • Patel Y.
      • et al.
      Cyfip1 haploinsufficient rats show white matter changes, myelin thinning, abnormal oligodendrocytes and behavioural inflexibility.
      ). Cyfip1 haploinsufficiency led to decreased FA, myelin thinning in the corpus callosum, and aberrant intracellular distribution of myelin basic protein in cultured oligodendrocytes. These findings contrasted with our previous results from the Icelandic sample, showing widespread increased FA in 15q11.2 BP1-BP2 deletion carriers. However, in the UK Biobank sample, reduced FA was found in PTR_R in deletion carriers, which contributed to worse cognitive performance. Decreased FA could indeed result from myelin deficits (
      • Alba-Ferrara L.M.
      • de Erausquin G.A.
      What does anisotropy measure? Insights from increased and decreased anisotropy in selective fiber tracts in schizophrenia.
      ) that could be caused by dysregulations in CYFIP1, which could in turn affect cognition (
      • Fields R.D.
      White matter in learning, cognition and psychiatric disorders.
      ,
      • Fields R.D.
      A new mechanism of nervous system plasticity: Activity-dependent myelination.
      ). Conversely, increased FA in ALIC_L and Cing_HIP_L led to better cognitive performance in deletion carriers, which could be associated with compensatory mechanisms as a response to primary deficits (e.g., in myelination or synapses). It is, however, difficult to speculate at this point, given that the individual or combined influence of the other three genes in this region on white matter is unknown, and disruptions to myelin and/or axons cannot be distinguished with traditional DTI methods.
      The effect sizes reported here were overall smaller than the ones in the Icelandic sample. In this study, we compared carriers to thousands of control subjects, which provides a better estimate of the general population mean and therefore a more reliable estimate of effect sizes (
      • Ferguson C.J.
      An effect size primer: A guide for clinicians and researchers.
      ). In the Icelandic sample, carriers were compared with 19 NoCNV control subjects, which may have led to an overestimation of the CNV effect. The 15q11.2 BP1-BP2 deletion has been proposed as a variant of uncertain clinical significance. However, more recent meta-analyses on published case-control studies have classified the deletion as a pathogenic of mild effect size (
      • Jønch A.E.
      • Douard E.
      • Moreau C.
      • Van Dijck A.
      • Passeggeri M.
      • Kooy F.
      • et al.
      Estimating the effect size of the 15Q11.2 BP1–BP2 deletion and its contribution to neurodevelopmental symptoms: Recommendations for practice.
      ). It is also important to note that the recruitment in UK Biobank and Iceland relies on volunteers who put themselves forward to be scanned, which could result in a significant healthy volunteer bias (
      • Fry A.
      • Littlejohns T.J.
      • Sudlow C.
      • Doherty N.
      • Adamska L.
      • Sprosen T.
      • et al.
      Comparison of sociodemographic and health-related characteristics of UK Biobank participants with those of the general population.
      ).
      Different sample characteristics and imaging acquisition protocols could explain some of the variability between our previous and current results. However, it is encouraging that we found concordant results from different samples, increasing our confidence of a CNV effect on white matter, particularly on the cingulum and internal capsule, which harbor important connections of the limbic system.

      Conclusions

      We provide converging evidence from two independent samples with different genetic and environmental backgrounds supporting the effects of 15q11.2 BP1-BP2 carrier status on white matter microstructure, with larger effects in deletion than duplication carriers. Our results also point toward a dose-dependent effect, showing a linear trend in most tracts, where carriers of no CNVs sit between deletion and duplication carriers. We further show that changes in white matter partially mediate the association between CNV carrier status and cognitive performance. These results add to the evidence of white matter changes as being an intermediate phenotype between genetic risk variants and cognitive or clinical phenotypes.

      Acknowledgments and Disclosures

      This research was conducted using the UK Biobank Resource under Application Number 17044. This research was supported by the Medical Research Council Programme (Grant No. G08005009 ); a Wellcome Trust Strategic Award 'DEFINE' (Grant No. 100202/Z/12/Z [to JH, LSW, and DEJL] ); core support from the Neuroscience and Mental Health Research Institute , Cardiff University; and a Wellcome Trust Clinical Research Training Fellowship (Grant No. 201171/Z/16/Z [to KMK]).
      MOU, GBW, HS, and KS are employees of deCODE genetics/Amgen. All other authors report no biomedical financial interests or potential conflicts of interest.

      Supplementary Material

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