Le numéro de janvier 2020 de Biological Psychiatry est consacré aux mécanismes moléculaires dans les troubles du neurodéveloppement.

1. Thapar A. Infant Neuromotor Development : An Early Indicator of Genetic Liability for Neurodevelopmental Disorders. Biological Psychiatry ;2020 (2020/01/15/) ;87(2):93-94.

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2. Buxbaum JD. Making Sense of Antisense : Getting From a Locus to a Gene. Biological Psychiatry ;2020 (2020/01/15/) ;87(2):95-97.

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3. Bray NJ, Owen MJ. A Developmental Perspective on the Convergence of Genetic Risk Factors for Neuropsychiatric Disorders. Biological Psychiatry ;2020 (2020/01/15/) ;87(2):98-99.

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4. Johnson BV, Kumar R, Oishi S, Alexander S, Kasherman M, Vega MS, Ivancevic A, Gardner A, Domingo D, Corbett M, Parnell E, Yoon S, Oh T, Lines M, Lefroy H, Kini U, Van Allen M, Grønborg S, Mercier S, Küry S, Bézieau S, Pasquier L, Raynaud M, Afenjar A, Billette de Villemeur T, Keren B, Désir J, Van Maldergem L, Marangoni M, Dikow N, Koolen DA, VanHasselt PM, Weiss M, Zwijnenburg P, Sa J, Reis CF, López-Otín C, Santiago-Fernández O, Fernández-Jaén A, Rauch A, Steindl K, Joset P, Goldstein A, Madan-Khetarpal S, Infante E, Zackai E, McDougall C, Narayanan V, Ramsey K, Mercimek-Andrews S, Pena L, Shashi V, Schoch K, Sullivan JA, Acosta MT, Adams DR, Aday A, Alejandro ME, Allard P, Ashley EA, Azamian MS, Bacino CA, Bademci G, Baker E, Balasubramanyam A, Baldridge D, Barbouth D, Batzli GF, Beggs AH, Bellen HJ, Bernstein JA, Berry GT, Bican A, Bick DP, Birch CL, Bivona S, Bonnenmann C, Bonner D, Boone BE, Bostwick BL, Briere LC, Brokamp E, Brown DM, Brush M, Burke EA, Burrage LC, Butte MJ, Carrasquillo O, Peter Chang TC, Chao H-T, Clark GD, Coakley TR, Cobban LA, Cogan JD, Cole FS, Colley HA, Cooper CM, Cope H, Craigen WJ, D’Souza P, Dasari S, Davids M, Davidson JM, Dayal JG, Dell’Angelica EC, Dhar SU, Dorrani N, Dorset DC, Douine ED, Draper DD, Dries AM, Duncan L, Eckstein DJ, Emrick LT, Eng CM, Enns GM, Esteves C, Estwick T, Fernandez L, Ferreira C, Fieg EL, Fisher PG, Fogel BL, Forghani I, Friedman ND, Gahl WA, Godfrey RA, Goldman AM, Goldstein DB, Gourdine J-PF, Grajewski A, Groden CA, Gropman AL, Haendel M, Hamid R, Hanchard NA, High F, Holm IA, Hom J, Huang A, Huang Y, Isasi R, Jamal F, Jiang Y-h, Johnston JM, Jones AL, Karaviti L, Kelley EG, Koeller DM, Kohane IS, Kohler JN, Krakow D, Krasnewich DM, Korrick S, Koziura M, Krier JB, Kyle JE, Lalani SR, Lam B, Lanpher BC, Lanza IR, Lau CC, Lazar J, LeBlanc K, Lee BH, Lee H, Levitt R, Levy SE, Lewis RA, Lincoln SA, Liu P, Liu XZ, Loo SK, Loscalzo J, Maas RL, Macnamara EF, MacRae CA, Maduro VV, Majcherska MM, Malicdan MCV, Mamounas LA, Manolio TA, Markello TC, Marom R, Martin MG, Martínez-Agosto JA, Marwaha S, May T, McCauley J, McConkie-Rosell A, McCormack CE, McCray AT, Merker JD, Metz TO, Might M, Morava-Kozicz E, Moretti PM, Morimoto M, Mulvihill JJ, Murdock DR, Nath A, Nelson SF, Newberry JS, Newman JH, Nicholas SK, Novacic D, Oglesbee D, Orengo JP, Pak S, Pallais JC, Palmer CGS, Papp JC, Parker NH, Phillips JA, Posey JE, Postlethwait JH, Potocki L, Pusey BN, Renteri G, Reuter CM, Rives L, Robertson AK, Rodan LH, Rosenfeld JA, Rowley RK, Sacco R, Sampson JB, Samson SL, Saporta M, Schaechter J, Schedl T, Scott DA, Shakachite L, Sharma P, Shields K, Shin J, Signer R, Sillari CH, Silverman EK, Sinsheimer JS, Smith KS, Solnica-Krezel L, Spillmann RC, Stoler JM, Stong N, Sweetser DA, Tamburro CP, Tan QKG, Tekin M, Telischi F, Thorson W, Tifft CJ, Toro C, Tran AA, Urv TK, Vogel TP, Waggott DM, Wahl CE, Walley NM, Walsh CA, Walker M, Wambach J, Wan J, Wang L-k, Wangler MF, Ward PA, Waters KM, Webb-Robertson B-JM, Wegner D, Westerfield M, Wheeler MT, Wise AL, Wolfe LA, Woods JD, Worthey EA, Yamamoto S, Yang J, Yoon AJ, Yu G, Zastrow DB, Zhao C, Zuchner S, Gahl W, Pinto e Vairo F, Pichurin PN, Ewing SA, Barnett SS, Klee EW, Perry MS, Koenig MK, Keegan CE, Schuette JL, Asher S, Perilla-Young Y, Smith LD, Bhoj E, Kaplan P, Li D, Oegema R, van Binsbergen E, van der Zwaag B, Smeland MF, Cutcutache I, Page M, Armstrong M, Lin AE, Steeves MA, Hollander Nd, Hoffer MJV, Reijnders MRF, Demirdas S, Koboldt DC, Bartholomew D, Mosher TM, Hickey SE, Shieh C, Sanchez-Lara PA, Graham JM, Tezcan K, Schaefer GB, Danylchuk NR, Asamoah A, Jackson KE, Yachelevich N, Au M, Pérez-Jurado LA, Kleefstra T, Penzes P, Wood SA, Burne T, Pierson TM, Piper M, Gécz J, Jolly LA. Partial Loss of USP9X Function Leads to a Male Neurodevelopmental and Behavioral Disorder Converging on Transforming Growth Factor β Signaling. Biological Psychiatry ;2020 (2020/01/15/) ;87(2):100-112.

Background The X-chromosome gene USP9X encodes a deubiquitylating enzyme that has been associated with neurodevelopmental disorders primarily in female subjects. USP9X escapes X inactivation, and in female subjects de novo heterozygous copy number loss or truncating mutations cause haploinsufficiency culminating in a recognizable syndrome with intellectual disability and signature brain and congenital abnormalities. In contrast, the involvement of USP9X in male neurodevelopmental disorders remains tentative. Methods We used clinically recommended guidelines to collect and interrogate the pathogenicity of 44 USP9X variants associated with neurodevelopmental disorders in males. Functional studies in patient-derived cell lines and mice were used to determine mechanisms of pathology. Results Twelve missense variants showed strong evidence of pathogenicity. We define a characteristic phenotype of the central nervous system (white matter disturbances, thin corpus callosum, and widened ventricles) ; global delay with significant alteration of speech, language, and behavior ; hypotonia ; joint hypermobility ; visual system defects ; and other common congenital and dysmorphic features. Comparison of in silico and phenotypical features align additional variants of unknown significance with likely pathogenicity. In support of partial loss-of-function mechanisms, using patient-derived cell lines, we show loss of only specific USP9X substrates that regulate neurodevelopmental signaling pathways and a united defect in transforming growth factor β signaling. In addition, we find correlates of the male phenotype in Usp9x brain-specific knockout mice, and further resolve loss of hippocampal-dependent learning and memory. Conclusions Our data demonstrate the involvement of USP9X variants in a distinctive neurodevelopmental and behavioral syndrome in male subjects and identify plausible mechanisms of pathogenesis centered on disrupted transforming growth factor β signaling and hippocampal function.

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5. O’Donoghue S, Green T, Ross JL, Hallmayer J, Lin X, Jo B, Huffman LC, Hong DS, Reiss AL. Brain Development in School-Age and Adolescent Girls : Effects of Turner Syndrome, Estrogen Therapy, and Genomic Imprinting. Biological Psychiatry ;2020 (2020/01/15/) ;87(2):113-122.

Background The study of Turner syndrome (TS) offers a unique window of opportunity for advancing scientific knowledge of how X chromosome gene imprinting, epigenetic factors, hormonal milieu, and chronologic age affect brain development in females. Methods We described brain growth trajectories in 55 girls with TS and 53 typically developing girls (258 magnetic resonance imaging datasets) spanning 5 years. Using novel nonparametric and mixed effects analytic approaches, we evaluated influences of X chromosome genomic imprinting and hormone replacement therapy on brain development. Results Parieto-occipital gray and white matter regions showed slower growth during typical pubertal timing in girls with TS relative to typically developing girls. In contrast, some basal ganglia, cerebellar, and limited cortical areas showed enhanced volume growth with peaks around 10 years of age. Conclusions The parieto-occipital finding suggests that girls with TS may be particularly vulnerable to altered brain development during adolescence. Basal ganglia regions may be relatively preserved in TS owing to their maturational growth before or early in typical pubertal years. Taken together, our findings indicate that particular brain regions are more vulnerable to TS genetic and hormonal effects during puberty. These specific alterations in neurodevelopment may be more likely to affect long-term cognitive behavioral outcomes in young girls with this common genetic condition.

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6. Beighley JS, Hudac CM, Arnett AB, Peterson JL, Gerdts J, Wallace AS, Mefford HC, Hoekzema K, Turner TN, O’Roak BJ, Eichler EE, Bernier RA. Clinical Phenotypes of Carriers of Mutations in CHD8 or Its Conserved Target Genes. Biological Psychiatry ;2020 (2020/01/15/) ;87(2):123-131.

Background Variants disruptive to CHD8 (which codes for the protein CHD8 [chromodomain-helicase-DNA-binding protein 8]) are among the most common mutations revealed by exome sequencing in autism spectrum disorder (ASD). Recent work has indicated that CHD8 plays a role in the regulation of other ASD-risk genes. However, it is unclear whether a possible shared genetic ontology extends to the phenotype. Methods This study (N = 143 ; 42.7% female participants) investigated clinical and behavioral features of individuals ascertained for the presence of a known disruptive ASD-risk mutation that is 1) CHD8 (CHD8 group) (n = 15), 2) a gene targeted by CHD8 (target group) (n = 22), or 3) a gene without confirmed evidence of being targeted by CHD8 (other gene group) (n = 106). Results Results indicated shared features between the CHD8 and target groups that included less severe adaptive deficits in communication skills, similar functional language, more social motivation challenges in those with ASD, larger head circumference, higher weight, and lower seizure prevalence relative to the other gene group. Conclusions These similarities suggest broader genetic ontology accounts for aspects of phenotypic heterogeneity. Improved understanding of the relationships between related disruptive gene events may lead us to improved understanding of shared mechanisms and lead to more focused treatments for individuals with known genetic mutations.

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7. Serdarevic F, Tiemeier H, Jansen PR, Alemany S, Xerxa Y, Neumann A, Robinson E, Hillegers MHJ, Verhulst FC, Ghassabian A. Polygenic Risk Scores for Developmental Disorders, Neuromotor Functioning During Infancy, and Autistic Traits in Childhood. Biological Psychiatry ;2020 (2020/01/15/) ;87(2):132-138.

Background Impaired neuromotor development is often one of the earliest observations in children with autism spectrum disorder (ASD). We investigated whether a genetic predisposition to developmental disorders was associated with nonoptimal neuromotor development during infancy and examined the genetic correlation between nonoptimal neuromotor development and autistic traits in the general population. Methods In a population-based cohort in The Netherlands (2002–2006), we calculated polygenic risk scores (PRSs) for ASD and attention-deficit/hyperactivity disorder (ADHD) using genome-wide association study summary statistics. In 1921 children with genetic data, parents rated autistic traits at 6 years of age. Among them, 1174 children (61.1%) underwent neuromotor examinations (tone, responses, senses, and other observations) during infancy (9–20 weeks of age). We used linear regressions to examine associations of PRSs with neuromotor scores and autistic traits. We performed a bivariate genome-based restricted maximum likelihood analysis to explore whether genetic susceptibility underlies the association between neuromotor development and autistic traits. Results Higher PRSs for ASD were associated with less optimal overall infant neuromotor development, in particular low muscle tone. Higher PRSs for ADHD were associated with less optimal senses. PRSs for ASD and those for ADHD both were associated with autistic traits. The single nucleotide polymorphism–based heritability of overall motor development was 20% (SE = .21) and of autistic traits was 68% (SE = .26). The genetic correlation between overall motor development and autistic traits was .35 (SE = .21, p < .001). Conclusions We found that genetic liabilities for ASD and ADHD covary with neuromotor development during infancy. Shared genetic liability might partly explain the association between nonoptimal neuromotor development during infancy and autistic traits in childhood.

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8. Ross PJ, Zhang W-B, Mok RSF, Zaslavsky K, Deneault E, D’Abate L, Rodrigues DC, Yuen RKC, Faheem M, Mufteev M, Piekna A, Wei W, Pasceri P, Landa RJ, Nagy A, Varga B, Salter MW, Scherer SW, Ellis J. Synaptic Dysfunction in Human Neurons With Autism-Associated Deletions in PTCHD1-AS. Biological Psychiatry ;2020 (2020/01/15/) ;87(2):139-149.

Background The Xp22.11 locus that encompasses PTCHD1, DDX53, and the long noncoding RNA PTCHD1-AS is frequently disrupted in male subjects with autism spectrum disorder (ASD), but the functional consequences of these genetic risk factors for ASD are unknown. Methods To evaluate the functional consequences of PTCHD1 locus deletions, we generated induced pluripotent stem cells (iPSCs) from unaffected control subjects and 3 subjects with ASD with microdeletions affecting PTCHD1-AS/PTCHD1, PTCHD1-AS/DDX53, or PTCHD1-AS alone. Function of iPSC-derived cortical neurons was assessed using molecular approaches and electrophysiology. We also compiled novel and known genetic variants of the PTCHD1 locus to explore the roles of PTCHD1 and PTCHD1-AS in genetic risk for ASD and other neurodevelopmental disorders. Finally, genome editing was used to explore the functional consequences of deleting a single conserved exon of PTCHD1-AS. Results iPSC-derived neurons from subjects with ASD exhibited reduced miniature excitatory postsynaptic current frequency and N-methyl-D-aspartate receptor hypofunction. We found that 35 ASD-associated deletions mapping to the PTCHD1 locus disrupted exons of PTCHD1-AS. We also found a novel ASD-associated deletion of PTCHD1-AS exon 3 and showed that exon 3 loss altered PTCHD1-AS splicing without affecting expression of the neighboring PTCHD1 coding gene. Finally, targeted disruption of PTCHD1-AS exon 3 recapitulated diminished miniature excitatory postsynaptic current frequency, supporting a role for the long noncoding RNA in the etiology of ASD. Conclusions Our genetic findings provide strong evidence that PTCHD1-AS deletions are risk factors for ASD, and human iPSC-derived neurons implicate these deletions in the neurophysiology of excitatory synapses and in ASD-associated synaptic impairment.

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9. Forsyth JK, Nachun D, Gandal MJ, Geschwind DH, Anderson AE, Coppola G, Bearden CE. Synaptic and Gene Regulatory Mechanisms in Schizophrenia, Autism, and 22q11.2 Copy Number Variant–Mediated Risk for Neuropsychiatric Disorders. Biological Psychiatry ;2020 (2020/01/15/) ;87(2):150-163.

Background 22q11.2 copy number variants are among the most highly penetrant genetic risk variants for developmental neuropsychiatric disorders such as schizophrenia (SCZ) and autism spectrum disorder (ASD). However, the specific mechanisms through which they confer risk remain unclear. Methods Using a functional genomics approach, we integrated transcriptomic data from the developing human brain, genome-wide association findings for SCZ and ASD, protein interaction data, and gene expression signatures from SCZ and ASD postmortem cortex to 1) organize genes into the developmental cellular and molecular systems within which they operate, 2) identify neurodevelopmental processes associated with polygenic risk for SCZ and ASD across the allelic frequency spectrum, and 3) elucidate pathways and individual genes through which 22q11.2 copy number variants may confer risk for each disorder. Results Polygenic risk for SCZ and ASD converged on partially overlapping neurodevelopmental modules involved in synaptic function and transcriptional regulation, with ASD risk variants additionally enriched for modules involved in neuronal differentiation during fetal development. The 22q11.2 locus formed a large protein network during development that disproportionately affected SCZ-associated and ASD-associated neurodevelopmental modules, including loading highly onto synaptic and gene regulatory pathways. SEPT5, PI4KA, and SNAP29 genes are candidate drivers of 22q11.2 synaptic pathology relevant to SCZ and ASD, and DGCR8 and HIRA are candidate drivers of disease-relevant alterations in gene regulation. Conclusions This approach offers a powerful framework to identify neurodevelopmental processes affected by diverse risk variants for SCZ and ASD and elucidate mechanisms through which highly penetrant, multigene copy number variants contribute to disease risk.

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10. Nielsen AN, Gratton C, Church JA, Dosenbach NUF, Black KJ, Petersen SE, Schlaggar BL, Greene DJ. Atypical Functional Connectivity in Tourette Syndrome Differs Between Children and Adults. Biological Psychiatry ;2020 (2020/01/15/) ;87(2):164-173.

Background Tourette syndrome (TS) is a neuropsychiatric disorder with symptomatology that typically changes over development. Whether and how brain function in TS also differs across development has been largely understudied. Here, we used functional connectivity magnetic resonance imaging to examine whole-brain functional networks in children and adults with TS. Methods Multivariate classification methods were used to find patterns among functional connections that distinguish individuals with TS from control subjects separately for children and adults (N = 202). We tested whether the patterns of connections that classify diagnosis in one age group (e.g., children) could classify diagnosis in another age group (e.g., adults). We also tested whether the developmental trajectory of these connections was altered in TS. Results Diagnostic classification was successful in children and adults separately but expressly did not generalize across age groups, suggesting that the patterns of functional connections that best distinguished individuals with TS from control subjects were age specific. Developmental patterns among these functional connections used for diagnostic classification deviated from typical development. Brain networks in childhood TS appeared “older” and brain networks in adulthood TS appeared “younger” in comparison with typically developing individuals. Conclusions Our results demonstrate that brain networks are differentially altered in children and adults with TS. The observed developmental trajectory of affected connections is consistent with theories of accelerated and/or delayed maturation, but may also involve anomalous developmental pathways. These findings further our understanding of neurodevelopmental trajectories in TS and carry implications for future applications aimed at predicting the clinical course of TS in individuals over development.

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11. O’Neill J, Bansal R, Goh S, Rodie M, Sawardekar S, Peterson BS. Parsing the Heterogeneity of Brain Metabolic Disturbances in Autism Spectrum Disorder. Biological Psychiatry ;2020 (2020/01/15/) ;87(2):174-184.

Background Despite rising prevalence of autism spectrum disorder (ASD), its brain bases remain uncertain. Abnormal levels of N-acetyl compounds, glutamate+glutamine, creatine+phosphocreatine, or choline compounds measured by proton magnetic resonance spectroscopy suggest that neuron or glial density, mitochondrial energetic metabolism, and/or inflammation contribute to ASD neuropathology. The neuroanatomic distribution of these metabolites could help evaluate leading theories of ASD. However, most prior magnetic resonance spectroscopy studies had small samples (all <60, most <20), interrogated only a small fraction of the brain, and avoided assessing effects of age, sex, and IQ. Methods We acquired near-whole-brain magnetic resonance spectroscopy of N-acetyl compounds, glutamate+glutamine, creatine+phosphocreatine, and choline compounds in 78 children and adults with ASD and 96 typically developing children and adults, rigorously evaluating effects of diagnosis and severity on metabolites, as moderated by age, sex, and IQ. Results Effects of ASD and its severity included reduced levels of multiple metabolites in white matter and the perisylvian cortex and elevated levels in the posterior cingulate, consistent with white matter and social-brain theories of ASD. Regionally, both slower and faster decreases of metabolites with age were observed in ASD versus TD. Male-female metabolite differences were widely smaller in ASD than typically developing children and adults. ASD-specific decreases in metabolites with decreasing IQ occurred in several brain areas. Conclusions Results support multifocal abnormal neuron or glial density, mitochondrial energetics, or neuroinflammation in ASD, alongside widespread starkly atypical moderating effects of age, sex, and IQ. These findings help parse the neurometabolic signature for ASD by phenotypic heterogeneity.

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12. Sevgi M, Diaconescu AO, Henco L, Tittgemeyer M, Schilbach L. Social Bayes : Using Bayesian Modeling to Study Autistic Trait–Related Differences in Social Cognition. Biological Psychiatry ;2020 (2020/01/15/) ;87(2):185-193.

Background The autistic spectrum is characterized by profound impairments of social interaction. The exact subpersonal processes, however, that underlie the observable lack of social reciprocity are still a matter of substantial controversy. Recently, it has been suggested that the autistic spectrum might be characterized by alterations of the brain’s inference about the causes of socially relevant sensory signals. Methods We used a novel reward-based learning task that required integration of nonsocial and social cues in conjunction with computational modeling. Thirty-six healthy subjects were selected based on their score on the Autism-Spectrum Quotient (AQ), and AQ scores were assessed for correlations with cue-related model parameters and task scores. Results Individual differences in AQ scores were significantly correlated with participants’ total task scores, with high AQ scorers performing more poorly in the task (r = −.39, 95% confidence interval = −0.68 to −0.13). Computational modeling of the behavioral data unmasked a learning deficit in high AQ scorers, namely, the failure to integrate social context to adapt one’s belief precision—the precision afforded to prior beliefs about changing states in the world—particularly in relation to the nonsocial cue. Conclusions More pronounced autistic traits in a group of healthy control subjects were related to lower scores associated with misintegration of the social cue. Computational modeling further demonstrated that these trait-related performance differences are not explained by an inability to process the social stimuli and their causes, but rather by the extent to which participants consider social information to infer the nonsocial cue.

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13. Jaworska N. Looking at the Big Neurochemical Picture of Autism Spectrum Disorder. Biological Psychiatry ;2020 (2020/01/15/) ;87(2):e5-e6.

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