Maternal age, autistic-like traits and mentalizing as predictors of child autistic-like traits in a population-based cohort / Novika Purnama SARI in Molecular Autism, 13 (2022)  

Public ISBD [article]  inMolecular Autism > 13 (2022) . - 26 p. Titre : Maternal age, autistic-like traits and mentalizing as predictors of child autistic-like traits in a population-based cohort Type de document : texte imprimé Auteurs : Novika Purnama SARI, Auteur ; Pauline W. JANSEN, Auteur ; Laura M. E. BLANKEN, Auteur ; Amber N. V. RUIGROK, Auteur ; Peter PRINZIE, Auteur ; Henning TIEMEIER, Auteur ; Simon BARON-COHEN, Auteur ; Marinus H. VAN IJZENDOORN, Auteur ; Tonya WHITE, Auteur Article en page(s) : 26 p. Langues : Anglais (eng) Mots-clés : Autistic Disorder/epidemiology  Child  Female  Humans  Male  Maternal Age  Mentalization  Mothers  Netherlands/epidemiology  Pregnancy  Autistic-like traits  Children   Mentalizing Index. décimale : PER Périodiques Résumé : BACKGROUND: Many empirical studies suggest that higher maternal age increases the likelihood of having an autistic child. However, little is known about factors that may explain this relationship or if higher maternal age is related to the number of autistic-like traits in offspring. One possibility is that mothers who have a higher number of autistic-like traits, including greater challenges performing mentalizing skills, are delayed in finding a partner. The goal of our study is to assess the relationship between maternal age, mentalizing skills and autistic-like traits as independent predictors of the number of autistic-like traits in offspring. METHODS: In a population-based study in the Netherlands, information on maternal age was collected during pre- and perinatal enrolment. Maternal mentalizing skills and autistic-like traits were assessed using the Reading the Mind in the Eyes Test and the Autism Spectrum Quotient, respectively. Autistic-like traits in children were assessed with the Social Responsiveness Scale. A total of 5718 mother/child dyads had complete data (M(agechild)=13.5 years; 50.2% girls). RESULTS: The relationship between maternal age and autistic-like traits in offspring best fits a U-shaped curve. Furthermore, higher levels of autistic features in mothers are linked to higher levels of autistic-like traits in their children. Lower mentalizing performance in mothers is linked to higher levels of autistic-like traits in their children. LIMITATIONS: We were able to collect data on both autistic-like traits and the mentalizing skills test in a large population of mothers, but we did not collect these data in a large number of the fathers. CONCLUSIONS: The relationships between older and younger mothers may have comparable underlying mechanisms, but it is also possible that the tails of the U-shaped curve are influenced by disparate mechanisms. En ligne : http://dx.doi.org/10.1186/s13229-022-00507-4 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=491 [article] Maternal age, autistic-like traits and mentalizing as predictors of child autistic-like traits in a population-based cohort [texte imprimé] / Novika Purnama SARI, Auteur ; Pauline W. JANSEN, Auteur ; Laura M. E. BLANKEN, Auteur ; Amber N. V. RUIGROK, Auteur ; Peter PRINZIE, Auteur ; Henning TIEMEIER, Auteur ; Simon BARON-COHEN, Auteur ; Marinus H. VAN IJZENDOORN, Auteur ; Tonya WHITE, Auteur . - 26 p. Langues : Anglais (eng) in Molecular Autism > 13 (2022) . - 26 p. Mots-clés : Autistic Disorder/epidemiology  Child  Female  Humans  Male  Maternal Age  Mentalization  Mothers  Netherlands/epidemiology  Pregnancy  Autistic-like traits  Children   Mentalizing Index. décimale : PER Périodiques Résumé : BACKGROUND: Many empirical studies suggest that higher maternal age increases the likelihood of having an autistic child. However, little is known about factors that may explain this relationship or if higher maternal age is related to the number of autistic-like traits in offspring. One possibility is that mothers who have a higher number of autistic-like traits, including greater challenges performing mentalizing skills, are delayed in finding a partner. The goal of our study is to assess the relationship between maternal age, mentalizing skills and autistic-like traits as independent predictors of the number of autistic-like traits in offspring. METHODS: In a population-based study in the Netherlands, information on maternal age was collected during pre- and perinatal enrolment. Maternal mentalizing skills and autistic-like traits were assessed using the Reading the Mind in the Eyes Test and the Autism Spectrum Quotient, respectively. Autistic-like traits in children were assessed with the Social Responsiveness Scale. A total of 5718 mother/child dyads had complete data (M(agechild)=13.5 years; 50.2% girls). RESULTS: The relationship between maternal age and autistic-like traits in offspring best fits a U-shaped curve. Furthermore, higher levels of autistic features in mothers are linked to higher levels of autistic-like traits in their children. Lower mentalizing performance in mothers is linked to higher levels of autistic-like traits in their children. LIMITATIONS: We were able to collect data on both autistic-like traits and the mentalizing skills test in a large population of mothers, but we did not collect these data in a large number of the fathers. CONCLUSIONS: The relationships between older and younger mothers may have comparable underlying mechanisms, but it is also possible that the tails of the U-shaped curve are influenced by disparate mechanisms. En ligne : http://dx.doi.org/10.1186/s13229-022-00507-4 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=491

Quantifying and exploring camouflaging in men and women with autism / Meng-Chuan LAI in Autism, 21-6 (August 2017)  

Public ISBD [article]  inAutism > 21-6 (August 2017) . - p.690-702 Titre : Quantifying and exploring camouflaging in men and women with autism Type de document : texte imprimé Auteurs : Meng-Chuan LAI, Auteur ; Michael V. LOMBARDO, Auteur ; Amber N. V. RUIGROK, Auteur ; Bhismadev CHAKRABARTI, Auteur ; Bonnie AUYEUNG, Auteur ; Peter SZATMARI, Auteur ; Francesca HAPPE, Auteur ; Simon BARON-COHEN, Auteur Article en page(s) : p.690-702 Langues : Anglais (eng) Index. décimale : PER Périodiques Résumé : Autobiographical descriptions and clinician observations suggest that some individuals with autism, particularly females, ?camouflage? their social communication difficulties, which may require considerable cognitive effort and lead to increased stress, anxiety and depression. Using data from 60 age- and IQ-matched men and women with autism (without intellectual disability), we operationalized camouflaging in adults with autism for the first time as the quantitative discrepancy between the person s ?external? behavioural presentation in social?interpersonal contexts (measured by the Autism Diagnostic Observation Schedule) and the person s ?internal? status (dispositional traits measured by the Autism Spectrum Quotient and social cognitive capability measured by the ?Reading the Mind in the Eyes? Test). We found that the operationalized camouflaging measure was not significantly correlated with age or IQ. On average, women with autism had higher camouflaging scores than men with autism (Cohen s d=0.98), with substantial variability in both groups. Greater camouflaging was associated with more depressive symptoms in men and better signal-detection sensitivity in women with autism. The neuroanatomical association with camouflaging score was largely sex/gender-dependent and significant only in women: from reverse inference, the most correlated cognitive terms were about emotion and memory. The underlying constructs, measurement, mechanisms, consequences and heterogeneity of camouflaging in autism warrant further investigation. En ligne : http://dx.doi.org/10.1177/1362361316671012 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=311 [article] Quantifying and exploring camouflaging in men and women with autism [texte imprimé] / Meng-Chuan LAI, Auteur ; Michael V. LOMBARDO, Auteur ; Amber N. V. RUIGROK, Auteur ; Bhismadev CHAKRABARTI, Auteur ; Bonnie AUYEUNG, Auteur ; Peter SZATMARI, Auteur ; Francesca HAPPE, Auteur ; Simon BARON-COHEN, Auteur . - p.690-702. Langues : Anglais (eng) in Autism > 21-6 (August 2017) . - p.690-702 Index. décimale : PER Périodiques Résumé : Autobiographical descriptions and clinician observations suggest that some individuals with autism, particularly females, ?camouflage? their social communication difficulties, which may require considerable cognitive effort and lead to increased stress, anxiety and depression. Using data from 60 age- and IQ-matched men and women with autism (without intellectual disability), we operationalized camouflaging in adults with autism for the first time as the quantitative discrepancy between the person s ?external? behavioural presentation in social?interpersonal contexts (measured by the Autism Diagnostic Observation Schedule) and the person s ?internal? status (dispositional traits measured by the Autism Spectrum Quotient and social cognitive capability measured by the ?Reading the Mind in the Eyes? Test). We found that the operationalized camouflaging measure was not significantly correlated with age or IQ. On average, women with autism had higher camouflaging scores than men with autism (Cohen s d=0.98), with substantial variability in both groups. Greater camouflaging was associated with more depressive symptoms in men and better signal-detection sensitivity in women with autism. The neuroanatomical association with camouflaging score was largely sex/gender-dependent and significant only in women: from reverse inference, the most correlated cognitive terms were about emotion and memory. The underlying constructs, measurement, mechanisms, consequences and heterogeneity of camouflaging in autism warrant further investigation. En ligne : http://dx.doi.org/10.1177/1362361316671012 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=311

Subgrouping autism and ADHD based on structural MRI population modelling centiles / Clara PECCI-TERROBA in Molecular Autism, 16 (2025)  

Public ISBD [article]  inMolecular Autism > 16 (2025) . - 33 Titre : Subgrouping autism and ADHD based on structural MRI population modelling centiles Type de document : texte imprimé Auteurs : Clara PECCI-TERROBA, Auteur ; Meng-Chuan LAI, Auteur ; Michael V. LOMBARDO, Auteur ; Bhismadev CHAKRABARTI, Auteur ; Amber N. V. RUIGROK, Auteur ; John SUCKLING, Auteur ; Evdokia ANAGNOSTOU, Auteur ; Jason P. LERCH, Auteur ; Margot J. TAYLOR, Auteur ; Rob NICOLSON, Auteur ; Stelios GEORGIADES, Auteur ; Jennifer CROSBIE, Auteur ; Russell SCHACHAR, Auteur ; Elizabeth KELLEY, Auteur ; Jessica JONES, Auteur ; Paul D. ARNOLD, Auteur ; Jakob SEIDLITZ, Auteur ; Aaron F. ALEXANDER-BLOCH, Auteur ; Edward T. BULLMORE, Auteur ; Simon BARON-COHEN, Auteur ; Saashi A. BEDFORD, Auteur ; Richard A. I. BETHLEHEM, Auteur ; Clara PECCI-TERROBA, Auteur ; Meng-Chuan LAI, Auteur ; Michael V. LOMBARDO, Auteur ; Bhismadev CHAKRABARTI, Auteur ; Amber N. V. RUIGROK, Auteur ; John SUCKLING, Auteur ; Evdokia ANAGNOSTOU, Auteur ; Jason P. LERCH, Auteur ; Margot J. TAYLOR, Auteur ; Rob NICOLSON, Auteur ; Stelios GEORGIADES, Auteur ; Jennifer CROSBIE, Auteur ; Russell SCHACHAR, Auteur ; Elizabeth KELLEY, Auteur ; Jessica JONES, Auteur ; Paul D. ARNOLD, Auteur ; Jakob SEIDLITZ, Auteur ; Aaron F. ALEXANDER-BLOCH, Auteur ; Edward T. BULLMORE, Auteur ; Simon BARON-COHEN, Auteur ; Saashi A. BEDFORD, Auteur ; Richard A. I. BETHLEHEM, Auteur Article en page(s) : 33 Langues : Anglais (eng) Mots-clés : Attention Deficit Disorder with Hyperactivity/diagnostic  imaging/classification/pathology  Humans  Autistic Disorder/diagnostic imaging/classification/pathology  Magnetic Resonance Imaging/methods  Male  Female  Child  Cluster Analysis  Adolescent  Algorithms  Machine Learning  Adhd  Autism  Neuroimaging  Population modelling  Structural MRI  Subgrouping  informed consent were obtained for each primary study. The Cambridge Psychology  Research Ethics Committee (PRE.2020.104) deemed that secondary analysis of  deidentified data did not require ethical oversight. Consent for publication: Not  applicable. Competing interests: RAIB, MVL, and M-CL are Associate Editors, and  EA and BC are Editorial Board members of Molecular Autism. SBC is a former  Editor-in-Chief of the journal. ETB reports consultancy work for Boehringer  Ingelheim, Sosei Heptares, SR One, and GlaxoSmithKline. ETB, RAIB, JS, and AFA-B  are cofounders of Centile Bioscience. PDA receives research support from Biohaven  Pharmaceuticals. M-CL has received editorial honorarium from SAGE Publications.  RN reported receiving grants from Brain Canada, Hoffman La Roche, Otsuka  Pharmaceuticals, and Maplight Therapeutics outside the submitted work. EA  reported receiving grants from Roche and Anavex  receiving nonfinancial support  from AMO Pharma and CRA-Simons Foundation  and receiving personal fees from  Roche, Impel, Ono, and Quadrant outside the submitted work. Index. décimale : PER Périodiques Résumé : BACKGROUND: Autism and attention deficit hyperactivity disorder (ADHD) are two highly heterogeneous neurodevelopmental conditions with variable underlying neurobiology. Imaging studies have yielded varied results, and it is now clear that there is unlikely to be one characteristic neuroanatomical profile of either condition. Parsing this heterogeneity could allow us to identify more homogeneous subgroups, either within or across conditions, which may be more clinically informative. This has been a pivotal goal for neurodevelopmental research using both clinical and neuroanatomical features, though results thus far have again been inconsistent with regards to the number and characteristics of subgroups. METHODS: Here, we use population modelling to cluster a multi-site dataset based on global and regional centile scores of cortical thickness, surface area and grey matter volume. We use HYDRA, a novel semi-supervised machine learning algorithm which clusters based on differences to controls and compare its performance to a traditional clustering approach. RESULTS: We identified distinct subgroups within autism and ADHD, as well as across diagnosis, often with opposite neuroanatomical alterations relatively to controls. These subgroups were characterised by different combinations of increased or decreased patterns of morphometrics. We did not find significant clinical differences across subgroups. LIMITATIONS: Crucially, however, the number of subgroups and their membership differed vastly depending on chosen features and the algorithm used, highlighting the impact and importance of careful method selection. CONCLUSIONS: We highlight the importance of examining heterogeneity in autism and ADHD and demonstrate that population modelling is a useful tool to study subgrouping in autism and ADHD. We identified subgroups with distinct patterns of alterations relative to controls but note that these results rely heavily on the algorithm used and encourage detailed reporting of methods and features used in future studies. En ligne : https://dx.doi.org/10.1186/s13229-025-00667-z Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=569 [article] Subgrouping autism and ADHD based on structural MRI population modelling centiles [texte imprimé] / Clara PECCI-TERROBA, Auteur ; Meng-Chuan LAI, Auteur ; Michael V. LOMBARDO, Auteur ; Bhismadev CHAKRABARTI, Auteur ; Amber N. V. RUIGROK, Auteur ; John SUCKLING, Auteur ; Evdokia ANAGNOSTOU, Auteur ; Jason P. LERCH, Auteur ; Margot J. TAYLOR, Auteur ; Rob NICOLSON, Auteur ; Stelios GEORGIADES, Auteur ; Jennifer CROSBIE, Auteur ; Russell SCHACHAR, Auteur ; Elizabeth KELLEY, Auteur ; Jessica JONES, Auteur ; Paul D. ARNOLD, Auteur ; Jakob SEIDLITZ, Auteur ; Aaron F. ALEXANDER-BLOCH, Auteur ; Edward T. BULLMORE, Auteur ; Simon BARON-COHEN, Auteur ; Saashi A. BEDFORD, Auteur ; Richard A. I. BETHLEHEM, Auteur ; Clara PECCI-TERROBA, Auteur ; Meng-Chuan LAI, Auteur ; Michael V. LOMBARDO, Auteur ; Bhismadev CHAKRABARTI, Auteur ; Amber N. V. RUIGROK, Auteur ; John SUCKLING, Auteur ; Evdokia ANAGNOSTOU, Auteur ; Jason P. LERCH, Auteur ; Margot J. TAYLOR, Auteur ; Rob NICOLSON, Auteur ; Stelios GEORGIADES, Auteur ; Jennifer CROSBIE, Auteur ; Russell SCHACHAR, Auteur ; Elizabeth KELLEY, Auteur ; Jessica JONES, Auteur ; Paul D. ARNOLD, Auteur ; Jakob SEIDLITZ, Auteur ; Aaron F. ALEXANDER-BLOCH, Auteur ; Edward T. BULLMORE, Auteur ; Simon BARON-COHEN, Auteur ; Saashi A. BEDFORD, Auteur ; Richard A. I. BETHLEHEM, Auteur . - 33. Langues : Anglais (eng) in Molecular Autism > 16 (2025) . - 33 Mots-clés : Attention Deficit Disorder with Hyperactivity/diagnostic  imaging/classification/pathology  Humans  Autistic Disorder/diagnostic imaging/classification/pathology  Magnetic Resonance Imaging/methods  Male  Female  Child  Cluster Analysis  Adolescent  Algorithms  Machine Learning  Adhd  Autism  Neuroimaging  Population modelling  Structural MRI  Subgrouping  informed consent were obtained for each primary study. The Cambridge Psychology  Research Ethics Committee (PRE.2020.104) deemed that secondary analysis of  deidentified data did not require ethical oversight. Consent for publication: Not  applicable. Competing interests: RAIB, MVL, and M-CL are Associate Editors, and  EA and BC are Editorial Board members of Molecular Autism. SBC is a former  Editor-in-Chief of the journal. ETB reports consultancy work for Boehringer  Ingelheim, Sosei Heptares, SR One, and GlaxoSmithKline. ETB, RAIB, JS, and AFA-B  are cofounders of Centile Bioscience. PDA receives research support from Biohaven  Pharmaceuticals. M-CL has received editorial honorarium from SAGE Publications.  RN reported receiving grants from Brain Canada, Hoffman La Roche, Otsuka  Pharmaceuticals, and Maplight Therapeutics outside the submitted work. EA  reported receiving grants from Roche and Anavex  receiving nonfinancial support  from AMO Pharma and CRA-Simons Foundation  and receiving personal fees from  Roche, Impel, Ono, and Quadrant outside the submitted work. Index. décimale : PER Périodiques Résumé : BACKGROUND: Autism and attention deficit hyperactivity disorder (ADHD) are two highly heterogeneous neurodevelopmental conditions with variable underlying neurobiology. Imaging studies have yielded varied results, and it is now clear that there is unlikely to be one characteristic neuroanatomical profile of either condition. Parsing this heterogeneity could allow us to identify more homogeneous subgroups, either within or across conditions, which may be more clinically informative. This has been a pivotal goal for neurodevelopmental research using both clinical and neuroanatomical features, though results thus far have again been inconsistent with regards to the number and characteristics of subgroups. METHODS: Here, we use population modelling to cluster a multi-site dataset based on global and regional centile scores of cortical thickness, surface area and grey matter volume. We use HYDRA, a novel semi-supervised machine learning algorithm which clusters based on differences to controls and compare its performance to a traditional clustering approach. RESULTS: We identified distinct subgroups within autism and ADHD, as well as across diagnosis, often with opposite neuroanatomical alterations relatively to controls. These subgroups were characterised by different combinations of increased or decreased patterns of morphometrics. We did not find significant clinical differences across subgroups. LIMITATIONS: Crucially, however, the number of subgroups and their membership differed vastly depending on chosen features and the algorithm used, highlighting the impact and importance of careful method selection. CONCLUSIONS: We highlight the importance of examining heterogeneity in autism and ADHD and demonstrate that population modelling is a useful tool to study subgrouping in autism and ADHD. We identified subgroups with distinct patterns of alterations relative to controls but note that these results rely heavily on the algorithm used and encourage detailed reporting of methods and features used in future studies. En ligne : https://dx.doi.org/10.1186/s13229-025-00667-z Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=569

---

1 (1 - 3 / 3) Par page : 25 50 100 200