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Papers of the Week

  • 1) Brain. 2015 May 3. pii: awv118. [Epub ahead of print]

    Altered corpus callosum morphology associated with autism over the first 2 years of life.

    Wolff JJ(1), Gerig G(2), Lewis JD(3), Soda T(4), Styner MA(5), Vachet C(2),
    Botteron KN(6), Elison JT(7), Dager SR(8), Estes AM(9), Hazlett HC(5), Schultz
    RT(10), Zwaigenbaum L(11), Piven J(5); IBIS Network.
    
    Author information: 
    (1)1 Department of Educational Psychology, University of Minnesota, Minneapolis, 
    MN, USA jjwolff@umn.edu. (2)2 Scientific Computing and Imaging Institute,
    University of Utah, Salt Lake City, UT, USA. (3)3 Montreal Neurological
    Institute, McGill University, Montreal, QC, Canada. (4)4 Health Sciences and
    Technology, Harvard Medical School and Massachusetts Institute of Technology,
    Boston, MA, USA 5 Department of Psychiatry, University of North Carolina at
    Chapel Hill, Chapel Hill, NC, USA. (5)5 Department of Psychiatry, University of
    North Carolina at Chapel Hill, Chapel Hill, NC, USA 6 Carolina Institute for
    Developmental Disabilities, University of North Carolina at Chapel Hill, Chapel
    Hill, NC, USA. (6)7 Department of Psychiatry, Washington University at St. Louis,
    St. Louis, MO, USA. (7)8 Institute for Child Development, University of
    Minnesota, Minneapolis, MN, USA. (8)9 Department of Radiology, University of
    Washington, Seattle, WA, USA. (9)10 Department of Speech and Hearing Science,
    University of Washington, Seattle, WA, USA. (10)11 Centre for Autism Research,
    Children's Hospital of Philadelphia, Philadelphia, PA, USA. (11)12 Department of 
    Paediatrics, University of Alberta, Edmonton AB, Canada.
    
    Numerous brain imaging studies indicate that the corpus callosum is smaller in
    older children and adults with autism spectrum disorder. However, there are no
    published studies examining the morphological development of this connective
    pathway in infants at-risk for the disorder. Magnetic resonance imaging data were
    collected from 270 infants at high familial risk for autism spectrum disorder and
    108 low-risk controls at 6, 12 and 24 months of age, with 83% of infants
    contributing two or more data points. Fifty-seven children met criteria for ASD
    based on clinical-best estimate diagnosis at age 2 years. Corpora callosa were
    measured for area, length and thickness by automated segmentation. We found
    significantly increased corpus callosum area and thickness in children with
    autism spectrum disorder starting at 6 months of age. These differences were
    particularly robust in the anterior corpus callosum at the 6 and 12 month time
    points. Regression analysis indicated that radial diffusivity in this region,
    measured by diffusion tensor imaging, inversely predicted thickness. Measures of 
    area and thickness in the first year of life were correlated with repetitive
    behaviours at age 2 years. In contrast to work from older children and adults,
    our findings suggest that the corpus callosum may be larger in infants who go on 
    to develop autism spectrum disorder. This result was apparent with or without
    adjustment for total brain volume. Although we did not see a significant
    interaction between group and age, cross-sectional data indicated that area and
    thickness differences diminish by age 2 years. Regression data incorporating
    diffusion tensor imaging suggest that microstructural properties of callosal
    white matter, which includes myelination and axon composition, may explain group 
    differences in morphology.
    
    © The Author (2015). Published by Oxford University Press on behalf of the
    Guarantors of Brain. All rights reserved. For Permissions, please email:
    journals.permissions@oup.com.
    
    PMID: 25937563  [PubMed - as supplied by publisher]
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  • 2) Am J Hum Genet. 2015 Apr 29. pii: S0002-9297(15)00139-1. doi: 10.1016/j.ajhg.2015.04.002. [Epub ahead of print]

    A Potential Contributory Role for Ciliary Dysfunction in the 16p11.2 600 kb BP4-BP5 Pathology.

    Migliavacca E(1), Golzio C(2), Männik K(3), Blumenthal I(4), Oh EC(2), Harewood
    L(5), Kosmicki JA(6), Loviglio MN(5), Giannuzzi G(5), Hippolyte L(7), Maillard
    AM(7), Alfaiz AA(1); 16p11.2 European Consortium, van Haelst MM(8), Andrieux
    J(9), Gusella JF(10), Daly MJ(6), Beckmann JS(11), Jacquemont S(7), Talkowski
    ME(10), Katsanis N(12), Reymond A(13); 16p11 2 European Consortium.
    
    Collaborators: Migliavacca E, Männik K, Harewood L, Loviglio MN, Witwicki R,
    Didelot G, van der Werf I, Alfaiz AA, Zazhytska M, Giannuzzi G, Chrast J, Macé A,
    Bergmann S, Kutalik Z, Hippolyte L, Maillard AM, Siffredi V, Zufferey F, Martinet
    D, Bena F, Rauch A, Bouquillon S, Andrieux J, Delobel B, Boute O, Duban-Bedu B,
    Le Caignec C, Isidor B, Chiesa J, Keren B, Gilbert-Dussardier B, Touraine R,
    Campion D, Thambo CR, Mathieu-Dramard M, Plessis G, Kooy F, Peeters H, Ounap K,
    Vulto-van Silfhout AT, de Vries BB, van Binsbergen E, van Haelst MM, Nordgren A, 
    Mucciolo M, Renieri A, Rajcan-Separovic E, Philipps JA 3rd, Ellis RJ, Beckmann
    JS, Jacquemont S, Reymond A.
    
    Author information: 
    (1)Center for Integrative Genomics, University of Lausanne, 1015 Lausanne,
    Switzerland; Swiss Institute of Bioinformatics (SIB), 1015 Lausanne, Switzerland.
    (2)Center for Human Disease Modeling and Department of Cell Biology, Duke
    University, Durham, NC 27710, USA. (3)Center for Integrative Genomics, University
    of Lausanne, 1015 Lausanne, Switzerland; Estonian Genome Center, University of
    Tartu, Riia 23B, 51010 Tartu, Estonia. (4)Center for Human Genetic Research,
    Massachusetts General Hospital, Boston, MA 02114, USA. (5)Center for Integrative 
    Genomics, University of Lausanne, 1015 Lausanne, Switzerland. (6)Analytic and
    Translational Genetics Unit, Department of Medicine, Massachusetts General
    Hospital and Harvard Medical School, Boston, MA 02114, USA; Program in Medical
    and Population Genetics and Stanley Center for Psychiatric Research, Broad
    Institute of Harvard and MIT, 7 Cambridge Center, Cambridge, MA 02142, USA.
    (7)Service of Medical Genetics, Lausanne University Hospital (CHUV), 1011
    Lausanne, Switzerland. (8)Department of Medical Genetics, University Medical
    Center Utrecht, Lundlaan 6, 3508 AB Utrecht, the Netherlands. (9)Institut de
    Génétique Médicale, CHRU de Lille - Hôpital Jeanne de Flandre, Avenue Eugène
    Avinée, 59037 Lille, France. (10)Center for Human Genetic Research, Massachusetts
    General Hospital, Boston, MA 02114, USA; Departments of Genetics and Neurology,
    Harvard Medical School, Boston, MA 02114, USA. (11)Swiss Institute of
    Bioinformatics (SIB), 1015 Lausanne, Switzerland; Service of Medical Genetics,
    Lausanne University Hospital (CHUV), 1011 Lausanne, Switzerland; Department of
    Medical Genetics, University of Lausanne, 1011 Lausanne, Switzerland. (12)Center 
    for Human Disease Modeling and Department of Cell Biology, Duke University,
    Durham, NC 27710, USA. Electronic address: katsanis@cellbio.duke.edu. (13)Center 
    for Integrative Genomics, University of Lausanne, 1015 Lausanne, Switzerland.
    Electronic address: alexandre.reymond@unil.ch.
    
    The 16p11.2 600 kb copy-number variants (CNVs) are associated with mirror
    phenotypes on BMI, head circumference, and brain volume and represent frequent
    genetic lesions in autism spectrum disorders (ASDs) and schizophrenia. Here we
    interrogated the transcriptome of individuals carrying reciprocal 16p11.2 CNVs.
    Transcript perturbations correlated with clinical endophenotypes and were
    enriched for genes associated with ASDs, abnormalities of head size, and
    ciliopathies. Ciliary gene expression was also perturbed in orthologous mouse
    models, raising the possibility that ciliary dysfunction contributes to 16p11.2
    pathologies. In support of this hypothesis, we found structural ciliary defects
    in the CA1 hippocampal region of 16p11.2 duplication mice. Moreover, by using an 
    established zebrafish model, we show genetic interaction between KCTD13, a key
    driver of the mirrored neuroanatomical phenotypes of the 16p11.2 CNV, and
    ciliopathy-associated genes. Overexpression of BBS7 rescues head size and
    neuroanatomical defects of kctd13 morphants, whereas suppression or
    overexpression of CEP290 rescues phenotypes induced by KCTD13 under- or
    overexpression, respectively. Our data suggest that dysregulation of ciliopathy
    genes contributes to the clinical phenotypes of these CNVs.
    
    Copyright © 2015 The American Society of Human Genetics. Published by Elsevier
    Inc. All rights reserved.
    
    PMID: 25937446  [PubMed - as supplied by publisher]
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  • 3) Curr Neurol Neurosci Rep. 2015 Jun;15(6):553. doi: 10.1007/s11910-015-0553-1.

    Recent advances in the genetics of autism spectrum disorder.

    De Rubeis S(1), Buxbaum JD.
    
    Author information: 
    (1)Seaver Autism Center for Research and Treatment, Icahn School of Medicine at
    Mount Sinai, New York, 10029, NY, USA.
    
    Autism spectrum disorder (ASD) is a devastating neurodevelopmental disorder with 
    high prevalence in the population and a pronounced male preponderance. ASD has a 
    strong genetic basis, but until recently, a large fraction of the genetic factors
    contributing to liability was still unknown. Over the past 3 years,
    high-throughput next-generation sequencing on large cohorts has exposed a
    heterogeneous and complex genetic landscape and has revealed novel risk genes.
    Here, we provide an overview of the recent advances on the ASD genetic
    architecture, with an emphasis on the estimates of heritability, the contribution
    of common variants, and the role of inherited and de novo rare variation. We also
    examine the genetic components of the reported gender bias. Finally, we discuss
    the emerging findings from sequencing studies and how they illuminate crucial
    aspects of ASD pathophysiology.
    
    PMID: 25946996  [PubMed - in process]
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  • 4) Can J Public Health. 2015 Feb 3;106(2):e36-e42. doi: 10.17269/cjph.106.4667.

    The association between the interpregnancy interval and autism spectrum disorder in a Canadian cohort.

    Coo H, Ouellette-Kuntz H(1), Lam YM, Brownell M, Flavin MP, Roos LL.
    
    Author information: 
    (1)Queen's University. oullette@queensu.ca.
    
    OBJECTIVES: Two studies reported an increased risk of autistic disorder in
    children conceived less than 12 months after a previous birth. Our objective was 
    to examine the association between the interpregnancy interval (IPI) and autism
    spectrum disorder (ASD) in a Canadian cohort.
    METHODS: Using administrative datasets housed at the Manitoba Centre for Health
    Policy, we identified pairs of first- and second-born singleton siblings born
    between 1988 and 2005. Diagnoses of ASD were ascertained by searching physician
    billing claims, hospital discharge abstracts, education data, and a database
    containing information on individuals identified for a 2002-2007 ASD surveillance
    program in Manitoba. Logistic regression models were fit to examine the
    association between the IPI and ASD in 41,050 second-born siblings where the
    first-borns did not have ASD, using IPIs of ≥36 months as the reference category 
    and specifying three case groups. Case Group 1 included individuals with at least
    one ASD code (n = 490); Case Group 2 included those with two or more ASD codes (n
    = 375); and Case Group 3 comprised individuals with a record in the ASD
    surveillance program database (n = 141).
    RESULTS: The adjusted odds ratios (ORs) for IPIs shorter than 12 months ranged
    from 1.22 (95% CI: 0.91-1.63) for Case Group 1 to 1.72 (95% CI: 0.96-3.06) for
    Case Group 3. When the case groups were restricted to individuals with more
    severe ASD, the ORs increased and were significant for Case Groups 1 and 2.
    CONCLUSION: Our findings also support an association between short IPIs and more 
    severe ASD.
    
    PMID: 25955670  [PubMed - as supplied by publisher]
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  • 5) Hum Mol Genet. 2015 May 7. pii: ddv166. [Epub ahead of print]

    Spatiotemporal dynamics of the postnatal developing primate brain transcriptome.

    Bakken TE(1), Miller JA(1), Luo R(2), Bernard A(1), Bennett JL(3), Lee CK(1),
    Bertagnolli D(1), Parikshak NN(2), Smith KA(1), Sunkin SM(1), Amaral DG(3),
    Geschwind DH(2), Lein ES(1).
    
    Author information: 
    (1)Allen Institute for Brain Science, Seattle, WA. (2)Human Genetics Program,
    Department of Neurology and Semel Institute, David Geffen School of Medicine, UC 
    , Los Angeles, Los Angeles, CA. (3)Department of Psychiatry and Behavioral
    Science and M.I.N.D. Institute, UC Davis, Sacramento, CA.
    
    Developmental changes in the temporal and spatial regulation of gene expression
    drive the emergence of normal mature brain function, while disruptions in these
    processes underlie many neurodevelopmental abnormalities. To solidify our
    foundational knowledge of such changes in a primate brain with an extended period
    of postnatal maturation like in human, we investigated the whole-genome
    transcriptional profiles of rhesus monkey brains from birth to adulthood. We
    found that gene expression dynamics are largest from birth through infancy, after
    which gene expression profiles transition to a relatively stable state by young
    adulthood. Biological pathway enrichment analysis revealed that genes more highly
    expressed at birth are associated with cell adhesion and neuron differentiation, 
    while genes more highly expressed in juveniles and adults are associated with
    cell death. Neocortex showed significantly greater differential expression over
    time than sub-cortical structures, and this trend likely reflects the protracted 
    postnatal development of the cortex. Using network analysis, we identified 27
    co-expression modules containing genes with highly correlated expression patterns
    that are associated with specific brain regions, ages, or both. In particular,
    one module with high expression in neonatal cortex and striatum that decreases
    during infancy and juvenile development was significantly enriched for autism
    spectrum disorder (ASD)-related genes. This network was enriched for genes
    associated with axon guidance and interneuron differentiation, consistent with a 
    disruption in the formation of functional cortical circuitry in ASD.
    
    © The Author 2015. Published by Oxford University Press.
    
    PMID: 25954031  [PubMed - as supplied by publisher]
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  • 6) Nat Genet. 2015 May 11. doi: 10.1038/ng.3303. [Epub ahead of print]

    Excess of rare, inherited truncating mutations in autism.

    Krumm N(1), Turner TN(1), Baker C(1), Vives L(1), Mohajeri K(1), Witherspoon
    K(1), Raja A(2), Coe BP(1), Stessman HA(1), He ZX(3), Leal SM(3), Bernier R(4),
    Eichler EE(2).
    
    Author information: 
    (1)Department of Genome Sciences, University of Washington School of Medicine,
    Seattle, Washington, USA. (2)1] Department of Genome Sciences, University of
    Washington School of Medicine, Seattle, Washington, USA. [2] Howard Hughes
    Medical Institute, University of Washington, Seattle, Washington, USA. (3)Center 
    for Statistical Genetics, Department of Molecular and Human Genetics, Baylor
    College of Medicine, Houston, Texas, USA. (4)Department of Psychiatry and
    Behavioral Sciences, University of Washington, Seattle, Washington, USA.
    
    To assess the relative impact of inherited and de novo variants on autism risk,
    we generated a comprehensive set of exonic single-nucleotide variants (SNVs) and 
    copy number variants (CNVs) from 2,377 families with autism. We find that
    private, inherited truncating SNVs in conserved genes are enriched in probands
    (odds ratio = 1.14, P = 0.0002) in comparison to unaffected siblings, an effect
    involving significant maternal transmission bias to sons. We also observe a bias 
    for inherited CNVs, specifically for small (<100 kb), maternally inherited events
    (P = 0.01) that are enriched in CHD8 target genes (P = 7.4 × 10(-3)). Using a
    logistic regression model, we show that private truncating SNVs and rare,
    inherited CNVs are statistically independent risk factors for autism, with odds
    ratios of 1.11 (P = 0.0002) and 1.23 (P = 0.01), respectively. This analysis
    identifies a second class of candidate genes (for example, RIMS1, CUL7 and LZTR1)
    where transmitted mutations may create a sensitized background but are unlikely
    to be completely penetrant.
    
    PMID: 25961944  [PubMed - as supplied by publisher]
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