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White matter development and language abilities during infancy in autism spectrum disorder

Molecular Psychiatry (2024)Cite this article

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Abstract

White matter (WM) fiber tract differences are present in autism spectrum disorder (ASD) and could be important markers of behavior. One of the earliest phenotypic differences in ASD are language atypicalities. Although language has been linked to WM in typical development, no work has evaluated this association in early ASD. Participants came from the Infant Brain Imaging Study and included 321 infant siblings of children with ASD at high likelihood (HL) for developing ASD; 70 HL infants were later diagnosed with ASD (HL-ASD), and 251 HL infants were not diagnosed with ASD (HL-Neg). A control sample of 140 low likelihood infants not diagnosed with ASD (LL-Neg) were also included. Infants contributed expressive language, receptive language, and diffusion tensor imaging data at 6-, 12-, and 24 months. Mixed effects regression models were conducted to evaluate associations between WM and language trajectories. Trajectories of microstructural changes in the right arcuate fasciculus were associated with expressive language development. HL-ASD infants demonstrated a different developmental pattern compared to the HL-Neg and LL-Neg groups, wherein the HL-ASD group exhibited a positive association between WM fractional anisotropy and language whereas HL-Neg and LL-Neg groups showed weak or no association. No other fiber tracts demonstrated significant associations with language. In conclusion, results indicated arcuate fasciculus WM is linked to language in early toddlerhood for autistic toddlers, with the strongest associations emerging around 24 months. To our knowledge, this is the first study to evaluate associations between language and WM development during the pre-symptomatic period in ASD.

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Fig. 1: White matter fiber bundles from DTI tractography.
Fig. 2: Cross-sectional relations between white matter fractional anisotropy in the left and right arcuate segments and expressive/receptive language age equivalent by visit and likelihood group.
Fig. 3: Model predicted mean trajectories of expressive language age equivalent scores by likelihood group paneled by right arcuate-FP fractional anisotropy (FA) percentiles for whole sample.

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Data availability

Raw neuroimaging and behavioral that support the findings of this study are publicly available at the National Institutes of Mental Health Data Archive in collections 0019 and 2027. Any additional data may be made available by the corresponding author upon reasonable request.

Notes

  1. The term “high likelihood” is used here in place of the term “high-risk” and signifies an elevated likelihood of receiving an autism diagnosis due to family history and shared genetics [6].

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Acknowledgements

We thank the children and their families for their ongoing participation in this study. We also thank the numerous research assistants and volunteers who have worked on this project over the years. This work was supported by grants through the National Institutes of Health (K01-MH122779, PI: JBG; R01-HD055741, PI: JP; R01-HD055741-S1, PI: JP; P30-HD003110, PI: JP; U54-EB005149, PI: Kikinis) and the Simons Foundation (SFARI Grant 140209). Author TM was supported by NICHD T32HD040127. The funders had no role in study design, data collection, analysis, data interpretation, or the writing of the report.

Funding

RCM serves on the advisory board of Nous Imaging, Inc. and receives funding for meals and travel from Siemens Healthineers and Philips Healthcare. All other authors report no biomedical financial interests or potential conflicts of interest.

Author information

Author notes

  1. These authors contributed equally: Joseph Piven, Jessica B. Girault.

  2. A full list of members and their affiliations appears in the Supplementary Information.

Authors and Affiliations

  1. Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Carrboro, NC, USA

    Tyler C. McFayden, Gizem Cetin, Mark D. Shen, Heather C. Hazlett, Joseph Piven, Jessica B. Girault, J. Piven, H. C. Hazlett, M. D. Shen & J. B. Girault

  2. Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Joshua Rutsohn, Young Truong & Y. Truong

  3. Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA

    Elizabeth Forsen, Kelly Botteron & K. Botteron

  4. Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA

    Meghan R. Swanson

  5. Department of Speech Pathology and Audiology, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, India

    Shoba S. Meera

  6. Department of Educational Psychology, University of Minnesota, Minneapolis, MN, USA

    Jason J. Wolff & J. Wolff

  7. Institute of Child Development, University of Minnesota, Minneapolis, MN, USA

    Jed T. Elison & J. Elison

  8. Department of Radiology, University of Washington, Seattle, WA, USA

    Stephen R. Dager & S. Dager

  9. Institute on Human Development and Disability, University of Washington, Seattle, WA, USA

    Stephen R. Dager, Annette Estes, Tanya St. John, S. Dager, A. Estes & T. St. John

  10. Department of Speech and Hearing Sciences, University of Washington, Seattle, WA, USA

    Annette Estes, Tanya St. John, A. Estes & T. St. John

  11. Tandon School of Engineering, New York University, New York, NY, USA

    Guido Gerig & G. Gerig

  12. Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA

    Robert C. McKinstry & R. McKinstry

  13. Center for Autism Research, The Children’s Hospital of Philadelphia and University of Pennsylvania, Philadelphia, PA, USA

    Juhi Pandey, Robert Schultz, R. Schultz & J. Pandey

  14. Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Martin Styner & M. Styner

  15. Department of Pediatrics, University of Alberta, Edmonton, AB, Canada

    Lonnie Zwaigenbaum & L. Zwaigenbaum

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Consortia

the IBIS Network

  • J. Piven
  • , H. C. Hazlett
  • , M. D. Shen
  • , J. B. Girault
  • , S. Dager
  • , A. Estes
  • , T. St. John
  • , K. Botteron
  • , R. Schultz
  • , J. Pandey
  • , L. Zwaigenbaum
  • , J. Elison
  • , J. Wolff
  • , M. Styner
  • , G. Gerig
  • , R. McKinstry
  •  & Y. Truong

Contributions

1. Study concept & design: McFayden, Rutsohn, Cetin, Forsen, Swanson, Meera, Truong, Hazlett, Piven, Girault. 2. Data acquisition: Botteron, Dager, Estes, McKinstry, Pandey, Schultz, St. John, Zwaigenbaum, Hazlett, Piven. 3. Data analysis & Interpretation: McFayden, Rutsohn, Cetin, Forsen, Swanson, Wolff, Elison, Gerig, Styner, Truong, Hazlett, Piven, Girault. 4. Drafting of manuscript: McFayden, Rutsohn, Cetin, Forsen, Girault. 5. Critical revisions of the manuscript for important intellectual content: All authors.

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Correspondence to Tyler C. McFayden.

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McFayden, T.C., Rutsohn, J., Cetin, G. et al. White matter development and language abilities during infancy in autism spectrum disorder. Mol Psychiatry (2024). https://doi.org/10.1038/s41380-024-02470-3

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