Literature DB >> 35331004

Neurobiological Correlates of Change in Adaptive Behavior in Autism.

Charlotte M Pretzsch1, Tim Schäfer1, Michael V Lombardo1, Varun Warrier1, Caroline Mann1, Anke Bletsch1, Chris H Chatham1, Dorothea L Floris1, Julian Tillmann1, Afsheen Yousaf1, Emily Jones1, Tony Charman1, Sara Ambrosino1, Thomas Bourgeron1, Guillaume Dumas1, Eva Loth1, Bethany Oakley1, Jan K Buitelaar1, Freddy Cliquet1, Claire S Leblond1, Simon Baron-Cohen1, Christian F Beckmann1, Tobias Banaschewski1, Sarah Durston1, Christine M Freitag1, Declan G M Murphy1, Christine Ecker1.   

Abstract

OBJECTIVE: Autism spectrum disorder (ASD) is a lifelong neurodevelopmental condition that is associated with significant difficulties in adaptive behavior and variation in clinical outcomes across the life span. Some individuals with ASD improve, whereas others may not change significantly, or regress. Hence, the development of "personalized medicine" approaches is essential. However, this requires an understanding of the biological processes underpinning differences in clinical outcome, at both the individual and subgroup levels, across the lifespan.
METHODS: The authors conducted a longitudinal follow-up study of 483 individuals (204 with ASD and 279 neurotypical individuals, ages 6-30 years), with assessment time points separated by ∼12-24 months. Data collected included behavioral data (Vineland Adaptive Behavior Scale-II), neuroanatomical data (structural MRI), and genetic data (DNA). Individuals with ASD were grouped into clinically meaningful "increasers," "no-changers," and "decreasers" in adaptive behavior. First, the authors compared neuroanatomy between outcome groups. Next, they examined whether deviations from the neurotypical neuroanatomical profile were associated with outcome at the individual level. Finally, they explored the observed neuroanatomical differences' potential genetic underpinnings.
RESULTS: Outcome groups differed in neuroanatomical features (cortical volume and thickness, surface area), including in "social brain" regions previously implicated in ASD. Also, deviations of neuroanatomical features from the neurotypical profile predicted outcome at the individual level. Moreover, neuroanatomical differences were associated with genetic processes relevant to neuroanatomical phenotypes (e.g., synaptic development).
CONCLUSIONS: This study demonstrates, for the first time, that variation in clinical (adaptive) outcome is associated with both group- and individual-level variation in anatomy of brain regions enriched for genes relevant to ASD. This may facilitate the move toward better targeted/precision medicine approaches.

Entities:  

Keywords:  Autism Spectrum Disorder; Biological Markers; Genetics/Genomics; Neuroanatomy; Neurodevelopmental Disorders; Neuroimaging

Mesh:

Year:  2022        PMID: 35331004     DOI: 10.1176/appi.ajp.21070711

Source DB:  PubMed          Journal:  Am J Psychiatry        ISSN: 0002-953X            Impact factor:   18.112


  3 in total

1.  Advances in the identification and validation of autism biomarkers.

Authors:  Bethany F M Oakley; Eva Loth; Emily J H Jones; Christopher H Chatham; Declan G Murphy
Journal:  Nat Rev Drug Discov       Date:  2022-10       Impact factor: 112.288

2.  In-depth characterization of neuroradiological findings in a large sample of individuals with autism spectrum disorder and controls.

Authors:  Sara Ambrosino; Hasnaa Elbendary; Maarten Lequin; Dominique Rijkelijkhuizen; Tobias Banaschewski; Simon Baron-Cohen; Nico Bast; Sarah Baumeister; Jan Buitelaar; Tony Charman; Daisy Crawley; Flavio Dell'Acqua; Hannah Hayward; Rosemary Holt; Carolin Moessnang; Antonio M Persico; Roberto Sacco; Antonia San José Cáceres; Julian Tillmann; Eva Loth; Christine Ecker; Bob Oranje; Declan Murphy; Sarah Durston
Journal:  Neuroimage Clin       Date:  2022-07-16       Impact factor: 4.891

Review 3.  Lipid-Based Molecules on Signaling Pathways in Autism Spectrum Disorder.

Authors:  Kunio Yui; George Imataka; Shigemi Yoshihara
Journal:  Int J Mol Sci       Date:  2022-08-29       Impact factor: 6.208

  3 in total

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