Mark D Shen1, Christine W Nordahl2, Deana D Li2, Aaron Lee2, Kathleen Angkustsiri3, Robert W Emerson4, Sally J Rogers2, Sally Ozonoff2, David G Amaral2. 1. The Medical Investigation of Neurodevelopmental Disorders (MIND) Institute, UC Davis School of Medicine, University of California-Davis, Sacramento, CA, USA; Carolina Institute for Developmental Disabilities and Department of Psychiatry, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, USA. Electronic address: mark_shen@med.unc.edu. 2. The Medical Investigation of Neurodevelopmental Disorders (MIND) Institute, UC Davis School of Medicine, University of California-Davis, Sacramento, CA, USA; Department of Psychiatry and Behavioral Sciences, UC Davis School of Medicine, University of California-Davis, Sacramento, CA, USA. 3. The Medical Investigation of Neurodevelopmental Disorders (MIND) Institute, UC Davis School of Medicine, University of California-Davis, Sacramento, CA, USA; Department of Pediatrics, UC Davis School of Medicine, University of California-Davis, Sacramento, CA, USA. 4. Carolina Institute for Developmental Disabilities and Department of Psychiatry, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, USA.
Abstract
BACKGROUND: We previously showed, in two separate cohorts, that high-risk infants who were later diagnosed with autism spectrum disorder had abnormally high extra-axial cerebrospinal fluid (CSF) volume from age 6-24 months. The presence of increased extra-axial CSF volume preceded the onset of behavioural symptoms of autism and was predictive of a later diagnosis of autism spectrum disorder. In this study, we aimed to establish whether increased extra-axial CSF volume is found in a large, independent sample of children diagnosed with autism spectrum disorder, whether extra-axial CSF remains abnormally increased beyond infancy, and whether it is present in both normal-risk and high-risk children with autism. METHODS: In this case-control MRI study, children with autism spectrum disorder or with typical development aged 2-4 years were recruited from the community to the UC Davis MIND Institute Autism Phenome Project, based in Sacramento, CA, USA. The autism spectrum disorder group comprised children with autism spectrum disorder who were either normal risk (ie, from simplex families) or high risk (ie, from multiplex families). Measurements of extra-axial CSF volume, brain volume, head circumference, sleep problems, and familial risk status were derived from MRI and behavioural assessments. We applied a previously validated machine learning algorithm based on extra-axial CSF volume, brain volume, age, and sex to the current dataset. FINDINGS: Between July 20, 2007, and Dec 13, 2012, 159 children with autism spectrum disorder (132 male, 27 female) and 77 with typical development (49 male, 28 female) underwent MRI scans. The autism spectrum disorder group had an average of 15·1% more extra-axial CSF than controls after accounting for differences in brain volume, weight, age, and sex (least-squares mean 116·74 cm3 [SE 3·33] in autism group vs 101·40 cm3 [3·93] in typical development group; p=0·007; Cohen's d = 0·39). Subgroups of normal-risk (n=132) and high-risk (n=27) children with autism spectrum disorder had nearly identical extra-axial CSF volumes (p=0·78), and both subgroups had significantly greater volumes than controls. Both extra-axial CSF volume (p=0·004) and brain volume (p<0·0001) uniquely contributed to enlarged head circumference in the autism spectrum disorder group (p=0·04). Increased extra-axial CSF volume was associated with greater sleep disturbances (p=0·03) and lower non-verbal ability (p=0·04). The machine learning algorithm correctly predicted autism spectrum disorder diagnosis with a positive predictive value of 83% (95% CI 76·2-88·3). INTERPRETATION: Increased extra-axial CSF volume is a reliable brain anomaly that has now been found in three independent cohorts, comprising both high-risk and normal-risk children with autism spectrum disorder. Increased extra-axial CSF volume is detectable using conventional structural MRI scans from infancy through to age 3 years. These results suggest that increased extra-axial CSF volume could be an early stratification biomarker of a biologically based subtype of autism that might share a common underlying pathophysiology. FUNDING: US National Institutes of Health.
BACKGROUND: We previously showed, in two separate cohorts, that high-risk infants who were later diagnosed with autism spectrum disorder had abnormally high extra-axial cerebrospinal fluid (CSF) volume from age 6-24 months. The presence of increased extra-axial CSF volume preceded the onset of behavioural symptoms of autism and was predictive of a later diagnosis of autism spectrum disorder. In this study, we aimed to establish whether increased extra-axial CSF volume is found in a large, independent sample of children diagnosed with autism spectrum disorder, whether extra-axial CSF remains abnormally increased beyond infancy, and whether it is present in both normal-risk and high-risk children with autism. METHODS: In this case-control MRI study, children with autism spectrum disorder or with typical development aged 2-4 years were recruited from the community to the UC Davis MIND Institute Autism Phenome Project, based in Sacramento, CA, USA. The autism spectrum disorder group comprised children with autism spectrum disorder who were either normal risk (ie, from simplex families) or high risk (ie, from multiplex families). Measurements of extra-axial CSF volume, brain volume, head circumference, sleep problems, and familial risk status were derived from MRI and behavioural assessments. We applied a previously validated machine learning algorithm based on extra-axial CSF volume, brain volume, age, and sex to the current dataset. FINDINGS: Between July 20, 2007, and Dec 13, 2012, 159 children with autism spectrum disorder (132 male, 27 female) and 77 with typical development (49 male, 28 female) underwent MRI scans. The autism spectrum disorder group had an average of 15·1% more extra-axial CSF than controls after accounting for differences in brain volume, weight, age, and sex (least-squares mean 116·74 cm3 [SE 3·33] in autism group vs 101·40 cm3 [3·93] in typical development group; p=0·007; Cohen's d = 0·39). Subgroups of normal-risk (n=132) and high-risk (n=27) children with autism spectrum disorder had nearly identical extra-axial CSF volumes (p=0·78), and both subgroups had significantly greater volumes than controls. Both extra-axial CSF volume (p=0·004) and brain volume (p<0·0001) uniquely contributed to enlarged head circumference in the autism spectrum disorder group (p=0·04). Increased extra-axial CSF volume was associated with greater sleep disturbances (p=0·03) and lower non-verbal ability (p=0·04). The machine learning algorithm correctly predicted autism spectrum disorder diagnosis with a positive predictive value of 83% (95% CI 76·2-88·3). INTERPRETATION: Increased extra-axial CSF volume is a reliable brain anomaly that has now been found in three independent cohorts, comprising both high-risk and normal-risk children with autism spectrum disorder. Increased extra-axial CSF volume is detectable using conventional structural MRI scans from infancy through to age 3 years. These results suggest that increased extra-axial CSF volume could be an early stratification biomarker of a biologically based subtype of autism that might share a common underlying pathophysiology. FUNDING: US National Institutes of Health.
Authors: Mark D Shen; Sun Hyung Kim; Robert C McKinstry; Hongbin Gu; Heather C Hazlett; Christine W Nordahl; Robert W Emerson; Dennis Shaw; Jed T Elison; Meghan R Swanson; Vladimir S Fonov; Guido Gerig; Stephen R Dager; Kelly N Botteron; Sarah Paterson; Robert T Schultz; Alan C Evans; Annette M Estes; Lonnie Zwaigenbaum; Martin A Styner; David G Amaral; J Piven; H C Hazlett; C Chappell; S Dager; A Estes; D Shaw; K Botteron; R McKinstry; J Constantino; J Pruett; R Schultz; L Zwaigenbaum; J Elison; A C Evans; D L Collins; G B Pike; V Fonov; P Kostopoulos; S Das; G Gerig; M Styner; H Gu; Joseph Piven Journal: Biol Psychiatry Date: 2017-03-06 Impact factor: 13.382
Authors: Antoinette R Bailey; Brian N Giunta; Demian Obregon; William V Nikolic; Jun Tian; Cyndy D Sanberg; Danielle T Sutton; Jun Tan Journal: Int J Clin Exp Med Date: 2008-10-15
Authors: Farhad Mashayekhi; Clare E Draper; Carys M Bannister; Mohsen Pourghasem; P Jane Owen-Lynch; Jaleel A Miyan Journal: Brain Date: 2002-08 Impact factor: 13.501
Authors: Jerzy Wegiel; Janusz Frackowiak; Bozena Mazur-Kolecka; N Carolyn Schanen; Edwin H Cook; Marian Sigman; W Ted Brown; Izabela Kuchna; Jarek Wegiel; Krzysztof Nowicki; Humi Imaki; Shuang Yong Ma; Abha Chauhan; Ved Chauhan; David L Miller; Pankaj D Mehta; Michael Flory; Ira L Cohen; Eric London; Barry Reisberg; Mony J de Leon; Thomas Wisniewski Journal: PLoS One Date: 2012-05-02 Impact factor: 3.240
Authors: Simonne Cohen; Russell Conduit; Steven W Lockley; Shantha Mw Rajaratnam; Kim M Cornish Journal: J Neurodev Disord Date: 2014-12-11 Impact factor: 4.025
Authors: Arthur LeMaout; Han Bit Yoon; Sun Hyung Kim; Mahmoud Mostapha; Mark D Shen; Juan Prieto; Martin Styner Journal: Proc SPIE Int Soc Opt Eng Date: 2020-02-28
Authors: Veronica A Murphy; Mark D Shen; Sun Hyung Kim; Emil Cornea; Martin Styner; John H Gilmore Journal: Biol Psychiatry Cogn Neurosci Neuroimaging Date: 2020-04-01
Authors: Pearlynne L H Chong; Dea Garic; Mark D Shen; Iben Lundgaard; Amy J Schwichtenberg Journal: Sleep Med Rev Date: 2021-11-18 Impact factor: 11.609