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Early identification of autism spectrum disorder (ASD) is regarded as crucial for swift access to early intervention and, subsequently, better outcomes later in life. However, current instruments miss large proportions of children who later go on to be diagnosed with ASD, raising a question of what these instruments measure. The present study utilized data from the Norwegian Mother, Father, and Child Cohort Study and the Autism Birth Cohort study to explore the subsequent developmental and diagnostic characteristics of children raising developmental concern on the six-critical discriminative item criterion of the M-CHAT (DFA6) at 18 months of age (N = 834). The DFA6 identified 28.8% of children diagnosed with ASD (N = 163), but 4.4% with language disorder (N = 188) and 81.3% with intellectual disability (N = 32) without ASD. Scoring in the «at-risk» range was associated with lower IQ, impaired functional language, and greater severity of autism symptoms whether children had ASD or not.

The parental report-based Autism Diagnostic Interview-Revised (ADI-R) and the clinician observation-based Autism Diagnostic Observation Schedule (ADOS) have been validated primarily in U.S. clinics specialized in autism spectrum disorder (ASD), in which most children are referred by their parents because of ASD concern. This study assessed diagnostic agreement of the ADOS-2 and ADI-R toddler algorithms in a more broadly based sample of 679 toddlers (age 35-47 months) from the Norwegian Mother and Child Cohort. We also examined whether parental concern about ASD influenced instrument performance, comparing toddlers identified based on parental ASD concern (n = 48) and parent-reported signs of developmental problems (screening) without a specific concern about ASD (n = 400). The ADOS cutoffs showed consistently well-balanced sensitivity and specificity. The ADI-R cutoffs demonstrated good specificity, but reduced sensitivity, missing 43% of toddlers whose parents were not specifically concerned about ASD. The ADI-R and ADOS dimensional scores agreed well with clinical diagnoses (area under the curve ≥ 0.85), contributing additively to their prediction. On the ADI-R, different cutoffs were needed according to presence or absence of parental ASD concern, in order to achieve comparable balance of sensitivity and specificity. These results highlight the importance of taking parental concern about ASD into account when interpreting scores from parental report-based instruments such as the ADI-R. While the ADOS cutoffs performed consistently well, the additive contributions of ADI-R and ADOS scores to the prediction of ASD diagnosis underscore the value of combining instruments based on parent accounts and clinician observation in evaluation of ASD. Autism Res 2017, 10: 1672-1686. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.

Early identification of autism spectrum disorder (ASD) is regarded as crucial for swift access to early intervention and, subsequently, better outcomes later in life. However, current instruments miss large proportions of children who later go on to be diagnosed with ASD, raising a question of what these instruments measure. The present study utilized data from the Norwegian Mother, Father, and Child Cohort Study and the Autism Birth Cohort study to explore the subsequent developmental and diagnostic characteristics of children raising developmental concern on the six-critical discriminative item criterion of the M-CHAT (DFA6) at 18 months of age (N = 834). The DFA6 identified 28.8% of children diagnosed with ASD (N = 163), but 4.4% with language disorder (N = 188) and 81.3% with intellectual disability (N = 32) without ASD. Scoring in the 'at-risk' range was associated with lower IQ, impaired functional language, and greater severity of autism symptoms whether children had ASD or not., Author(s): Nina Stenberg [sup.1] , Synnve Schjølberg [sup.2] , Frederick Shic [sup.5] [sup.6] , Fred Volkmar [sup.4] , Anne-Siri Øyen [sup.2] [sup.8] , Michaeline Bresnahan [sup.7] , Britt Kveim Svendsen [...]

The present study objectives were to examine the performance of the new M‐CHAT‐R algorithm to the original M‐CHAT algorithm. The main purpose was to examine if the algorithmic changes increase identification of children later diagnosed with ASD, and to examine if there is a trade‐off when changing algorithms. We included 54,463 screened cases from the Norwegian Mother and Child Cohort Study. Children were screened using the 23 items of the M‐CHAT at 18 months. Further, the performance of the M‐CHAT‐R algorithm was compared to the M‐CHAT algorithm on the 23‐items. In total, 337 individuals were later diagnosed with ASD. Using M‐CHAT‐R algorithm decreased the number of correctly identified ASD children by 12 compared to M‐CHAT, with no children with ASD screening negative on the M‐CHAT criteria subsequently screening positive utilizing the M‐CHAT‐R algorithm. A nonparametric McNemar's test determined a statistically significant difference in identifying ASD utilizing the M‐CHAT‐R algorithm. The present study examined the application of 20‐item MCHAT‐R scoring criterion to the 23‐item MCHAT. We found that this resulted in decreased sensitivity and increased specificity for identifying children with ASD, which is a trade‐off that needs further investigation in terms of cost‐effectiveness. However, further research is needed to optimize screening for ASD in the early developmental period to increase identification of false negatives. Lay Summary: No study to this date has examined how the change in algorithm between the M‐CHAT and the M‐CHAT‐R affects the identification of ASD. The items and the instrument are very similar, but it has not been examined if the algorithm increases the identification rate of ASD. In this study, we utilized the Norwegian Mother, Father and Child study to examine how well the algorithm of the M‐CHAT performed in identifying children with ASD compared to the algorithm of the M‐CHAT‐R. Our study sample included 54,463 children, whereas 337 later received an ASD diagnosis. This present study shows that a change in algorithm is not necessarily improving the measure, as it did not increase the identification of children with ASD. However, the algorithmic change effectively decreased the number of children falsely identified at risk. [ABSTRACT FROM AUTHOR]

Autism spectrum disorder (ASD) and other neurodevelopmental disorders (NDs) are behaviorally defined disorders with overlapping clinical features that are often associated with higher‐order cognitive dysfunction, particularly executive dysfunction. Our aim was to determine if the polygenic score (PGS) for ASD is associated with parent‐reported executive dysfunction in everyday life using the Behavior Rating Inventory of Executive Function (BRIEF). Furthermore, we investigated if PGS for general intelligence (INT) and attention deficit/hyperactivity disorder (ADHD) also correlate with BRIEF. We included 176 children, adolescents and young adults aged 5–22 years with full‐scale intelligence quotient (IQ) above 70. All were admitted for clinical assessment of ASD symptoms and 68% obtained an ASD diagnosis. We found a significant difference between low and high ASD PGS groups in the BRIEF behavior regulation index (BRI) (P = 0.015, Cohen's d = 0.69). A linear regression model accounting for age, sex, full‐scale IQ, Social Responsiveness Scale (SRS) total score, ASD, ADHD and INT PGS groups as well as genetic principal components, significantly predicted the BRI score; F(11,130) = 8.142, P < 0.001, R2 = 0.41 (unadjusted). Only SRS total (P < 0.001), ASD PGS 0.1 group (P = 0.018), and sex (P = 0.022) made a significant contribution to the model. This suggests that the common ASD risk gene variants have a stronger association to behavioral regulation aspects of executive dysfunction than ADHD risk or INT variants in a clinical sample with ASD symptoms. Autism Res 2020, 13: 207–220. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. Lay Summary: People with autism spectrum disorder (ASD) often have difficulties with higher‐order cognitive processes that regulate thoughts and actions during goal‐directed behavior, also known as executive function (EF). We studied the association between genetics related to ASD and EF and found a relation between high polygenic score (PGS) for ASD and difficulties with behavior regulation aspects of EF in children and adolescents under assessment for ASD. Furthermore, high PGS for general intelligence was related to social problems. [ABSTRACT FROM AUTHOR]

Background: Autism spectrum disorders (ASDs) are characterized by persistent deficits in social communication and interaction and restricted, repetitive patterns of behavior, interests or activities. In most cases, the cause of ASD is likely to be a combination of genetic predisposition and environmental exposures occurring in fetal life or early infancy. Consequently, a prospective pregnancy cohort like MoBa represents an ideal platform for studies of ASDs in children. Methods: The Autism Birth Cohort (ABC) Study has identified potential ASD cases in MoBa through questionnaire-based screening, parental and professional referrals, and linkages to the Norwegian Patient Register. ASD diagnoses have been ascertained through in-person clinical assessments and medical record reviews. Current results: By the end of 2012, the ABC Study had identified 518 ASD cases in MoBa. The ASD prevalence in school-age children is 0.7-0.8%, which is in line with nationwide estimates for Norway. The most important source of ASD case identification was registry linkages, while only a minority was detected through early screening. Published findings show that screening at 18 months misses the majority of ASD cases. Analyses of risk factors for ASDs have shown that maternal use of folic acid supplements in early pregnancy may lower the child's risk of developing ASDs and that paternal obesity appears to increase the child's risk of ASDs. Future plans: ASD case identification will continue through annual registry linkages and subsequent reviews of medical records. Analyses of plasma samples and RNA samples will be conducted to investigate prenatal and perinatal microbial exposures, innate immune and inflammatory responses, biomarkers of autism risk, and exposures to xenobiotics. Analyses of deciduous teeth will also investigate the effect of medications and environmental toxins. Exome sequencing of DNA from ASD cases and their parents is ongoing, and will elucidate the role of de novo DNA mutations in the pathogenesis of ASDs. Future epidemiological analyses will explore the results of the 36-month screening for ASDs, the diagnostic stability and developmental trajectories in ASD children, and psychiatric and medical comorbidities in ASDs. [ABSTRACT FROM AUTHOR]

The present study objectives were to examine the performance of the new M-CHAT-R algorithm to the original M-CHAT algorithm. The main purpose was to examine if the algorithmic changes increase identification of children later diagnosed with ASD, and to examine if there is a trade-off when changing algorithms. We included 54,463 screened cases from the Norwegian Mother and Child Cohort Study. Children were screened using the 23 items of the M-CHAT at 18 months. Further, the performance of the M-CHAT-R algorithm was compared to the M-CHAT algorithm on the 23-items. In total, 337 individuals were later diagnosed with ASD. Using M-CHAT-R algorithm decreased the number of correctly identified ASD children by 12 compared to M-CHAT, with no children with ASD screening negative on the M-CHAT criteria subsequently screening positive utilizing the M-CHAT-R algorithm. A nonparametric McNemar's test determined a statistically significant difference in identifying ASD utilizing the M-CHAT-R algorithm. The present study examined the application of 20-item MCHAT-R scoring criterion to the 23-item MCHAT. We found that this resulted in decreased sensitivity and increased specificity for identifying children with ASD, which is a trade-off that needs further investigation in terms of cost-effectiveness. However, further research is needed to optimize screening for ASD in the early developmental period to increase identification of false negatives., (© 2021 The Authors. Autism Research published by International Society for Autism Research and Wiley Periodicals LLC.)

Autism spectrum disorder (ASD) and other neurodevelopmental disorders (NDs) are behaviorally defined disorders with overlapping clinical features that are often associated with higher-order cognitive dysfunction, particularly executive dysfunction. Our aim was to determine if the polygenic score (PGS) for ASD is associated with parent-reported executive dysfunction in everyday life using the Behavior Rating Inventory of Executive Function (BRIEF). Furthermore, we investigated if PGS for general intelligence (INT) and attention deficit/hyperactivity disorder (ADHD) also correlate with BRIEF. We included 176 children, adolescents and young adults aged 5-22 years with full-scale intelligence quotient (IQ) above 70. All were admitted for clinical assessment of ASD symptoms and 68% obtained an ASD diagnosis. We found a significant difference between low and high ASD PGS groups in the BRIEF behavior regulation index (BRI) (P = 0.015, Cohen's d = 0.69). A linear regression model accounting for age, sex, full-scale IQ, Social Responsiveness Scale (SRS) total score, ASD, ADHD and INT PGS groups as well as genetic principal components, significantly predicted the BRI score; F(11,130) = 8.142, P < 0.001, R 2 = 0.41 (unadjusted). Only SRS total (P < 0.001), ASD PGS 0.1 group (P = 0.018), and sex (P = 0.022) made a significant contribution to the model. This suggests that the common ASD risk gene variants have a stronger association to behavioral regulation aspects of executive dysfunction than ADHD risk or INT variants in a clinical sample with ASD symptoms. Autism Res 2020, 13: 207-220. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: People with autism spectrum disorder (ASD) often have difficulties with higher-order cognitive processes that regulate thoughts and actions during goal-directed behavior, also known as executive function (EF). We studied the association between genetics related to ASD and EF and found a relation between high polygenic score (PGS) for ASD and difficulties with behavior regulation aspects of EF in children and adolescents under assessment for ASD. Furthermore, high PGS for general intelligence was related to social problems., (© 2019 The Authors. Autism Research published by International Society for Autism Research published by Wiley Periodicals, Inc.)