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Wagner JB, Keehn B, Tager-Flusberg H, Nelson CA. Associations between attentional biases to fearful faces and social-emotional development in infants with and without an older sibling with autism. Infant Behav Dev 2023; 71:101811. [PMID: 36933374 PMCID: PMC10257765 DOI: 10.1016/j.infbeh.2023.101811] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 01/09/2023] [Accepted: 01/10/2023] [Indexed: 03/18/2023]
Abstract
During the first year of life, infants become increasingly attuned to facial emotion, with heightened sensitivity to faces conveying threat observed by age seven months as illustrated through attentional biases (e.g., slower shifting away from fearful faces). Individual differences in these cognitive attentional biases have been discussed in relation to broader social-emotional functioning, and the current study examines these associations in infants with an older sibling with autism spectrum disorder (ASD), a group with an elevated likelihood of a subsequent ASD diagnosis (ELA; n = 33), and a group of infants with no family history of ASD who are at low likelihood of ASD (LLA; n = 24). All infants completed a task measuring disengagement of attention from faces at 12 months (fearful, happy, neutral), and caregivers completed the Infant-Toddler Social and Emotional Assessment at 12, 18, and/or 24 months. For the full sample, greater fear bias in attention disengagement at 12 months related to more internalizing behaviors at 18 months, and this was driven by the LLA infants. When examining groups separately, findings revealed that LLA with a greater fear bias had more difficult behaviors at 12, 18, and 24 months; in contrast, ELA showed the opposite pattern, and this was most pronounced for ELA who later received an ASD diagnosis. These preliminary group-level findings suggest that heightened sensitivity to fearful faces might serve an adaptive function in children who later receive an ASD diagnosis, but in infants with no family history of ASD, increased biases might reflect a marker of social-emotional difficulties.
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Affiliation(s)
- Jennifer B Wagner
- College of Staten Island, City University of New York, 2800 Victory Boulevard, Staten Island, NY 10314, USA; The Graduate Center, City University of New York, 365 5th Avenue, New York, NY 10016, USA.
| | - Brandon Keehn
- Purdue University, Lyles-Porter Hall, 715 Clinic Drive, West Lafayette, IN 47907, USA
| | | | - Charles A Nelson
- Boston Children's Hospital/Harvard Medical School, 2 Brookline Place, Brookline, MA 02445, USA; Harvard Graduate School of Education, 13 Appian Way, Cambridge, MA 02138, USA
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Barbaro J, Sadka N, Gilbert M, Beattie E, Li X, Ridgway L, Lawson LP, Dissanayake C. Diagnostic Accuracy of the Social Attention and Communication Surveillance-Revised With Preschool Tool for Early Autism Detection in Very Young Children. JAMA Netw Open 2022; 5:e2146415. [PMID: 35275169 PMCID: PMC8917423 DOI: 10.1001/jamanetworkopen.2021.46415] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Accepted: 12/07/2021] [Indexed: 12/15/2022] Open
Abstract
Importance Early identification of children on the autism spectrum is crucial to facilitate access to early supports and services for children and families. The need for improved early autism identification tools is highlighted by the lack of sufficient diagnostic accuracy in current tools. Objectives To examine the diagnostic accuracy of the Social Attention and Communication Surveillance-Revised (SACS-R) and SACS-Preschool (SACS-PR) tools when used with a large, community-based, convenience sample and identify the prevalence of autism in this sample. Design, Setting, and Participants This diagnostic accuracy study was conducted in Melbourne, Australia, training maternal and child health nurses who monitored 13 511 children aged 11 to 42 months using the SACS-R and SACS-PR during their routine consultations (June 1, 2013, to July 31, 2018). Children identified as being at high likelihood for autism (12-24 months of age: n = 327; 42 months of age: n = 168) and at low likelihood for autism plus concerns (42 months of age: n = 28) were referred by their maternal and child health nurse for diagnostic assessment by the study team. Data analysis was performed from April 13, 2020, to November 29, 2021. Exposures Children were monitored with SACS-R and SACS-PR at 12, 18, 24, and 42 months of age. Main Outcomes and Measures Diagnostic accuracy of the SACS-R and SACS-PR was determined by comparing children's likelihood for autism with their diagnostic outcome using clinical judgment based on standard autism assessments (Autism Diagnostic Observation Schedule-Second Edition and Autism Diagnostic Interview-Revised). Results A total of 13 511 children (female: 6494 [48.1%]; male: 7017 [51.9%]) were monitored at least once with the SACS-R at their 12-, 18-, and 24-month-old routine maternal and child health consultations (mean [SD] age, 12.3 [0.59] months at 12 months; 18.3 [0.74] months at 18 months; 24.6 [1.12] months at 24 months) and followed up at their 42-month maternal and child health consultation (mean [SD] age, 44.0 [2.74] months) with SACS-PR (8419 [62.3%]). At 12 to 24 months, SACS-R showed high diagnostic accuracy, with 83% positive predictive value (95% CI, 0.77-0.87) and 99% estimated negative predictive value (95% CI, 0.01-0.02). Specificity (99.6% [95% CI, 0.99-1.00]) was high, with modest sensitivity (62% [95% CI, 0.57-0.66]). When the SACS-PR 42-month assessment was added, estimated sensitivity increased to 96% (95% CI, 0.94-0.98). Autism prevalence was 2.0% (1 in 50) between 11 and 30 months of age and 3.3% (1 in 31) between 11 and 42 months of age. Conclusions and Relevance The SACS-R with SACS-PR (SACS-R+PR) had high diagnostic accuracy for the identification of autism in a community-based sample of infants, toddlers, and preschoolers, indicating the utility of early autism developmental surveillance from infancy to the preschool period rather than 1-time screening. Its greater accuracy compared with psychometrics of commonly used autism screening tools when used in community-based samples suggests that the SACS-R+PR can be used universally for the early identification of autism.
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Affiliation(s)
- Josephine Barbaro
- Olga Tennison Autism Research Centre, School of Psychology and Public Health, La Trobe University, Melbourne, Australia
- Cooperative Research Centre for Living with Autism (Autism CRC), The University of Queensland, Indooroopilly, Queensland, Australia
| | - Nancy Sadka
- Olga Tennison Autism Research Centre, School of Psychology and Public Health, La Trobe University, Melbourne, Australia
| | - Melissa Gilbert
- Olga Tennison Autism Research Centre, School of Psychology and Public Health, La Trobe University, Melbourne, Australia
| | - Erin Beattie
- Olga Tennison Autism Research Centre, School of Psychology and Public Health, La Trobe University, Melbourne, Australia
| | - Xia Li
- Department of Mathematics and Statistics, La Trobe University, Melbourne, Australia
| | - Lael Ridgway
- Judith Lumley Centre, La Trobe University, Melbourne, Australia
| | - Lauren P. Lawson
- Olga Tennison Autism Research Centre, School of Psychology and Public Health, La Trobe University, Melbourne, Australia
- Cooperative Research Centre for Living with Autism (Autism CRC), The University of Queensland, Indooroopilly, Queensland, Australia
| | - Cheryl Dissanayake
- Olga Tennison Autism Research Centre, School of Psychology and Public Health, La Trobe University, Melbourne, Australia
- Cooperative Research Centre for Living with Autism (Autism CRC), The University of Queensland, Indooroopilly, Queensland, Australia
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Li W, Zhang Y, Su Y, Hao Y, Wang X, Yin X, Gong M, Gao Y, Meng L, Guo Q, Gao Q, Song L, Shi Y, Shi H. Intracerebroventricular injection of sclerostin reduced social hierarchy and impaired neuronal dendritic complexity in mice. Neurosci Lett 2022; 773:136514. [PMID: 35149200 DOI: 10.1016/j.neulet.2022.136514] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Revised: 02/04/2022] [Accepted: 02/05/2022] [Indexed: 10/19/2022]
Abstract
An increasing number of studies have demonstrated extensive functional links between bone and the brain. As a novel endocrine organ, bone has received increasing attention for its upregulatory functions in the brain. Sclerostin, a novel bone-derived endocrine molecule, secreted by osteocytes, can inhibit the bone morphogenetic protein (BMP) and wingless/integrated (Wnt) signaling pathways to regulate bone formation, but its effects on the central nervous system and neurosocial behaviors are unknown. This study investigated the effects of intracerebroventricular sclerostin injection on social-emotional behaviors in adult mice. The results showed that acute elevation of sclerostin levels in the brain could induce anxiety-like behaviors and reduce the social hierarchy of mice while reducing the dendritic complexity of pyramidal neurons in the mouse hippocampus. These data suggested that sclerostin may regulate social-emotional behaviors, providing new evidence for the existence of a bone-brain axis, new insights into the regulation of social behaviors by bone-derived endocrine molecules, and a new direction for the study of individual emotional behavior regulation.
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Affiliation(s)
- Wenshuya Li
- Neuroscience Research Center, Institute of Medical and Health Science of HeBMU, Hebei Medical University, Shijiazhuang, China, 050017; Hebei Key laboratory of Neurophysiology, Hebei Medical University, China, 050017
| | - Yan Zhang
- Neuroscience Research Center, Institute of Medical and Health Science of HeBMU, Hebei Medical University, Shijiazhuang, China, 050017; Hebei Key laboratory of Neurophysiology, Hebei Medical University, China, 050017
| | - Yujiao Su
- Neuroscience Research Center, Institute of Medical and Health Science of HeBMU, Hebei Medical University, Shijiazhuang, China, 050017; Hebei Key laboratory of Neurophysiology, Hebei Medical University, China, 050017
| | - Ying Hao
- Neuroscience Research Center, Institute of Medical and Health Science of HeBMU, Hebei Medical University, Shijiazhuang, China, 050017; Hebei Key laboratory of Neurophysiology, Hebei Medical University, China, 050017
| | - Xinhao Wang
- Neuroscience Research Center, Institute of Medical and Health Science of HeBMU, Hebei Medical University, Shijiazhuang, China, 050017; Hebei Key laboratory of Neurophysiology, Hebei Medical University, China, 050017
| | - Xi Yin
- Department of Functional Region of Diagnosis, Fourth Hospital of Hebei Medical University, Shijiazhuang, China, 050011
| | - Miao Gong
- Neuroscience Research Center, Institute of Medical and Health Science of HeBMU, Hebei Medical University, Shijiazhuang, China, 050017; Hebei Key laboratory of Neurophysiology, Hebei Medical University, China, 050017
| | - Yuan Gao
- Neuroscience Research Center, Institute of Medical and Health Science of HeBMU, Hebei Medical University, Shijiazhuang, China, 050017; Hebei Key laboratory of Neurophysiology, Hebei Medical University, China, 050017
| | - Li Meng
- Neuroscience Research Center, Institute of Medical and Health Science of HeBMU, Hebei Medical University, Shijiazhuang, China, 050017; Hebei Key laboratory of Neurophysiology, Hebei Medical University, China, 050017
| | - Qingjun Guo
- Neuroscience Research Center, Institute of Medical and Health Science of HeBMU, Hebei Medical University, Shijiazhuang, China, 050017; Hebei Key laboratory of Neurophysiology, Hebei Medical University, China, 050017
| | - Qiang Gao
- Neuroscience Research Center, Institute of Medical and Health Science of HeBMU, Hebei Medical University, Shijiazhuang, China, 050017; Hebei Key laboratory of Neurophysiology, Hebei Medical University, China, 050017
| | - Li Song
- Neuroscience Research Center, Institute of Medical and Health Science of HeBMU, Hebei Medical University, Shijiazhuang, China, 050017; Hebei Key laboratory of Neurophysiology, Hebei Medical University, China, 050017
| | - Yun Shi
- Neuroscience Research Center, Institute of Medical and Health Science of HeBMU, Hebei Medical University, Shijiazhuang, China, 050017; Department of Biochemistry and Molecular Biology, The Key Laboratory of Neural and Vascular Biology, Ministry of Education of China, Hebei Medical University, Shijiazhuang, Hebei 050017.
| | - Haishui Shi
- Neuroscience Research Center, Institute of Medical and Health Science of HeBMU, Hebei Medical University, Shijiazhuang, China, 050017; Hebei Key laboratory of Neurophysiology, Hebei Medical University, China, 050017.
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Chen D, Huang Y, Chen S, Huang Y, Swain A, Yu J. Predictive Model Construction for Social–Emotional Competence of Toddlers in Shanghai, China: A Population-Based Study. Front Public Health 2022; 9:797632. [PMID: 35174135 PMCID: PMC8841828 DOI: 10.3389/fpubh.2021.797632] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Accepted: 12/29/2021] [Indexed: 12/04/2022] Open
Abstract
Objective To construct a simple model containing predictors derived from Chinese Learning Accomplishment Profile (C-LAP) to better the evaluation of the social–emotional development of toddlers aged 24–36 months. Method The test results by C-LAP system and demographic information of toddlers aged 24–36 months were collected between 2013 and 2019 in Shanghai, China, whose guardians were voluntary to accept the investigation. We developed a norm with the dataset based on the study population. With the norm, stepwise regression and best subset analysis were applied to select predictors. Results Relying on the norm established and stepwise regression and also the best subset analysis, an optimal model containing only 6 indicators was finally determined and the nomogram of the model was constructed. In the training and validation dataset, the AUCs of the optimal model were 0.95 (95% CI: 0.94–0.96) and 0.88 (95% CI: 0.85–0.90), respectively. When the cutoff point of the model was set at 0.04, its sensitivity in training and validation dataset was 0.969 and 0.949, respectively, and the specificity in training and validation dataset is 0.802 and 0.736, respectively. Conclusion A simplified predictive model which includes only 6 items derived from C-LAP is developed to evaluate the probabilities of being at risk of developmental problem in social–emotional development for toddlers aged 24–36 months. Meanwhile, specificity and sensitivity of the model may be high enough for future fast screening.
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Affiliation(s)
- Deng Chen
- Key Laboratory of Public Health Safety, Institute of Clinical Epidemiology, Ministry of Education, School of Public Health, Fudan University, Shanghai, China
| | - Yilu Huang
- Key Laboratory of Public Health Safety, Institute of Clinical Epidemiology, Ministry of Education, School of Public Health, Fudan University, Shanghai, China
| | - Sikun Chen
- Key Laboratory of Public Health Safety, Institute of Clinical Epidemiology, Ministry of Education, School of Public Health, Fudan University, Shanghai, China
| | - Yunzhe Huang
- Shanghai VIP Health Care Co., Ltd (C-LAP), Shanghai, China
| | - Andrew Swain
- Shanghai VIP Health Care Co., Ltd (C-LAP), Shanghai, China
- Andrew Swain
| | - Jinming Yu
- Key Laboratory of Public Health Safety, Institute of Clinical Epidemiology, Ministry of Education, School of Public Health, Fudan University, Shanghai, China
- *Correspondence: Jinming Yu
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Hudock RL, Esler AN. Clinical considerations when conducting diagnostic evaluations to identify autism spectrum disorder in young children. Clin Neuropsychol 2022; 36:921-942. [DOI: 10.1080/13854046.2022.2025907] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Affiliation(s)
- Rebekah L. Hudock
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, Medical School, University of Minnesota, Minneapolis, MN, USA
| | - Amy N. Esler
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, Medical School, University of Minnesota, Minneapolis, MN, USA
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Xie H, Waschl N, Bian X, Wang R, Chen CY, Anunciação L, Chai Z, Song W, Li Y. Validity studies of a parent-completed social-emotional measure in a representative sample in China. APPLIED DEVELOPMENTAL SCIENCE 2021. [DOI: 10.1080/10888691.2021.1977642] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Affiliation(s)
- Huichao Xie
- Nanyang Technological University, National Institute of Education
| | - Nicolette Waschl
- Nanyang Technological University, National Institute of Education
| | | | | | | | | | | | - Wei Song
- Shanghai Jiading District Maternal and Child Healthcare Hospital
| | - Yan Li
- Shanghai Normal University
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