Papers of the Week
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.
(1)1 Department of Educational Psychology, University of Minnesota, Minneapolis,
MN, USA firstname.lastname@example.org. (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:
PMID: 25937563 [PubMed - as supplied by publisher]
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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.
(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: email@example.com. (13)Center
for Integrative Genomics, University of Lausanne, 1015 Lausanne, Switzerland.
Electronic address: firstname.lastname@example.org.
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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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.
(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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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.
(1)Queen's University. email@example.com.
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
PMID: 25955670 [PubMed - as supplied by publisher]
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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).
(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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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),
(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.  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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