Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Maternal mid-gestational and child cord blood immune signatures are strongly associated with offspring risk of ASD

Molecular Psychiatry volume 27, pages 1527–1541 (2022)Cite this article

Subjects

Abstract

Epidemiological studies and work in animal models indicate that immune activation may be a risk factor for autism spectrum disorders (ASDs). We measured levels of 60 cytokines and growth factors in 869 maternal mid-gestational (MMG) and 807 child cord blood (CB) plasma samples from 457 ASD (385 boys, 72 girls) and 497 control children (418 boys, 79 girls) from the Norwegian Autism Birth Cohort. We analyzed associations first using sex-stratified unadjusted and adjusted logistic regression models, and then employed machine learning strategies (LASSO + interactions, Random Forests, XGBoost classifiers) with cross-validation and randomly sampled test set evaluation to assess the utility of immune signatures as ASD biomarkers. We found prominent case–control differences in both boys and girls with alterations in a wide range of analytes in MMG and CB plasma including but not limited to IL1RA, TNFα, Serpin E1, VCAM1, VEGFD, EGF, CSF1, and CSF2. MMG findings were most striking, with particularly strong effect sizes in girls. Models did not change appreciably upon adjustment for maternal conditions, medication use, or emotional distress ratings. Findings were corroborated using machine learning approaches, with area under the receiver operating characteristic curve values in the test sets ranging from 0.771 to 0.965. Our results are consistent with gestational immunopathology in ASD, may provide insights into sex-specific differences, and have the potential to lead to biomarkers for early diagnosis.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

Fig. 1
Fig. 2: Autism spectrum disorders (ASDs) predictive modeling.

References

  1. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders (DSM-5(R)). Arlington, VA: American Psychiatric Publishing; 2013.

  2. Randall M, Egberts KJ, Samtani A, Scholten RJ, Hooft L, Livingstone N, et al. Diagnostic tests for autism spectrum disorder (ASD) in preschool children. Cochrane Database Syst Rev. 2018;7:CD009044.

    PubMed  Google Scholar 

  3. Zwaigenbaum L, Penner M. Autism spectrum disorder: advances in diagnosis and evaluation. BMJ. 2018;361:k1674.

    Article  PubMed  Google Scholar 

  4. Maenner MJ, Shaw KA, Baio J, Washington A, Patrick M, DiRienzo M, et al. Prevalence of autism spectrum disorder among children aged 8 years—Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2016. MMWR Surveill Summ. 2020;69:1–12.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Werling DM, Geschwind DH. Sex differences in autism spectrum disorders. Curr Opin Neurol. 2013;26:146–53.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Christensen J, Grønborg TK, Sørensen MJ, Schendel D, Parner ET, Pedersen LH, et al. Prenatal valproate exposure and risk of autism spectrum disorders and childhood autism. JAMA. 2013;309:1696–703.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Wiggs KK, Rickert ME, Sujan AC, Quinn PD, Larsson H, Lichtenstein P, et al. Antiseizure medication use during pregnancy and risk of ASD and ADHD in children. Neurology. 2020;95:e3232–e3240.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Meyer U, Nyffeler M, Yee BK, Knuesel I, Feldon J. Adult brain and behavioral pathological markers of prenatal immune challenge during early/middle and late fetal development in mice. Brain Behav Immun. 2008;22:469–86.

    Article  CAS  PubMed  Google Scholar 

  9. Bilbo SD, Block CL, Bolton JL, Hanamsagar R, Tran PK. Beyond infection—maternal immune activation by environmental factors, microglial development, and relevance for autism spectrum disorders. Exp Neurol. 2018;299:241–51.

    Article  CAS  PubMed  Google Scholar 

  10. Masi A, Quintana DS, Glozier N, Lloyd AR, Hickie IB, Guastella AJ. Cytokine aberrations in autism spectrum disorder: a systematic review and meta-analysis. Mol Psychiatry. 2015;20:440–6.

    Article  CAS  PubMed  Google Scholar 

  11. Brown AS. Epidemiologic studies of exposure to prenatal infection and risk of schizophrenia and autism. Dev Neurobiol. 2012;72:1272–6.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Hornig M, Bresnahan MA, Che X, Schultz AF, Ukaigwe JE, Eddy ML, et al. Prenatal fever and autism risk. Mol Psychiatry. 2018;23:759–66.

    Article  CAS  PubMed  Google Scholar 

  13. Estes ML, McAllister AK. Immune mediators in the brain and peripheral tissues in autism spectrum disorder. Nat Rev Neurosci. 2015;16:469–86.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Choi GB, Yim YS, Wong H, Kim S, Kim H, Kim SV, et al. The maternal interleukin-17a pathway in mice promotes autism-like phenotypes in offspring. Science. 2016;351:933–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Smith SE, Li J, Garbett K, Mirnics K, Patterson PH. Maternal immune activation alters fetal brain development through interleukin-6. J Neurosci. 2007;27:10695–702.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Deverman BE, Patterson PH. Cytokines and CNS development. Neuron. 2009;64:61–78.

    Article  CAS  PubMed  Google Scholar 

  17. Careaga M, Murai T, Bauman MD. Maternal immune activation and autism spectrum disorder: from rodents to nonhuman and human primates. Biol Psychiatry. 2017;81:391–401.

    Article  CAS  PubMed  Google Scholar 

  18. Corriveau RA, Huh GS, Shatz CJ. Regulation of class I MHC gene expression in the developing and mature CNS by neural activity. Neuron. 1998;21:505–20.

    Article  CAS  PubMed  Google Scholar 

  19. Needleman LA, McAllister AK. The major histocompatibility complex and autism spectrum disorder. Dev Neurobiol. 2012;72:1288–301.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Shatz CJ. MHC class I: an unexpected role in neuronal plasticity. Neuron. 2009;64:40–45.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Carpentier PA, Dingman AL, Palmer TD. Placental TNF-alpha signaling in illness-induced complications of pregnancy. Am J Pathol. 2011;178:2802–10.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Borsini A, Zunszain PA, Thuret S, Pariante CM. The role of inflammatory cytokines as key modulators of neurogenesis. Trends Neurosci. 2015;38:145–57.

    Article  CAS  PubMed  Google Scholar 

  23. Azmitia EC, Saccomano ZT, Alzoobaee MF, Boldrini M, Whitaker-Azmitia PM. Persistent angiogenesis in the autism brain: an immunocytochemical study of postmortem cortex, brainstem and cerebellum. J Autism Dev Disord. 2016;46:1307–18.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Prins JR, Eskandar S, Eggen BJL, Scherjon SA. Microglia, the missing link in maternal immune activation and fetal neurodevelopment; and a possible link in preeclampsia and disturbed neurodevelopment? J Reprod Immunol. 2018;126:18–22.

    Article  CAS  PubMed  Google Scholar 

  25. Kurzrock R, Estrov Z, Wetzler M, Gutterman JU, Talpaz M. LIF: not just a leukemia inhibitory factor. Endocr Rev. 1991;12:208–17.

    Article  CAS  PubMed  Google Scholar 

  26. Probert L. TNF and its receptors in the CNS: the essential, the desirable and the deleterious effects. Neuroscience. 2015;302:2–22.

    Article  CAS  PubMed  Google Scholar 

  27. Abdallah MW, Larsen N, Mortensen EL, Atladottir HO, Norgaard-Pedersen B, Bonefeld-Jorgensen EC, et al. Neonatal levels of cytokines and risk of autism spectrum disorders: an exploratory register-based historic birth cohort study utilizing the Danish Newborn Screening Biobank. J Neuroimmunol. 2012;252:75–82.

    Article  CAS  PubMed  Google Scholar 

  28. Abdallah MW, Larsen N, Grove J, Bonefeld-Jorgensen EC, Norgaard-Pedersen B, Hougaard DM, et al. Neonatal chemokine levels and risk of autism spectrum disorders: findings from a Danish historic birth cohort follow-up study. Cytokine. 2013;61:370–6.

    Article  CAS  PubMed  Google Scholar 

  29. Abdallah MW, Mortensen EL, Greaves-Lord K, Larsen N, Bonefeld-Jorgensen EC, Norgaard-Pedersen B, et al. Neonatal levels of neurotrophic factors and risk of autism spectrum disorders. Acta Psychiatr Scand. 2013;128:61–69.

    Article  CAS  PubMed  Google Scholar 

  30. Magnus P, Irgens LM, Haug K, Nystad W, Skjaerven R, Stoltenberg C, et al. Cohort profile: the Norwegian Mother and Child Cohort Study (MoBa). Int J Epidemiol. 2006;35:1146–50.

    Article  PubMed  Google Scholar 

  31. Magnus P, Birke C, Vejrup K, Haugan A, Alsaker E, Daltveit AK, et al. Cohort profile update: The Norwegian Mother and Child Cohort Study (MoBa). Int J Epidemiol. 2016;45:382–8.

    Article  PubMed  Google Scholar 

  32. Stoltenberg C, Schjolberg S, Bresnahan M, Hornig M, Hirtz D, Dahl C, et al. The Autism Birth Cohort: a paradigm for gene-environment-timing research. Mol Psychiatry. 2010;15:676–80.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Suren P, Havdahl A, Oyen AS, Schjolberg S, Reichborn-Kjennerud T, Magnus P, et al. Diagnosing autism spectrum disorder among children in Norway. Tidsskr Nor Laegeforen. 2019;139.

  34. Strand BH, Dalgard OS, Tambs K, Rognerud M. Measuring the mental health status of the Norwegian population: a comparison of the instruments SCL-25, SCL-10, SCL-5 and MHI-5 (SF-36). Nord J Psychiatry. 2003;57:113–8.

    Article  PubMed  Google Scholar 

  35. Ronningen KS, Paltiel L, Meltzer HM, Nordhagen R, Lie KK, Hovengen R, et al. The biobank of the Norwegian Mother and Child Cohort Study: a resource for the next 100 years. Eur J Epidemiol. 2006;21:619–25.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Bach JF. Infections and autoimmune diseases. J Autoimmun. 2005;25:74–80.

    Article  CAS  PubMed  Google Scholar 

  37. Goines PE, Croen LA, Braunschweig D, Yoshida CK, Grether J, Hansen R, et al. Increased midgestational IFN-gamma, IL-4 and IL-5 in women bearing a child with autism: a case-control study. Mol Autism. 2011;2:13.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Vignali DA. Multiplexed particle-based flow cytometric assays. J Immunol Methods. 2000;243:243–55.

    Article  CAS  PubMed  Google Scholar 

  39. Breen EJ, Tan W, Khan A. The statistical value of raw fluorescence signal in luminex xMAP based multiplex immunoassays. Sci Rep. 2016;6:26996.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Breen EJ, Polaskova V, Khan A. Bead-based multiplex immuno-assays for cytokines, chemokines, growth factors and other analytes: median fluorescence intensities versus their derived absolute concentration values for statistical analysis. Cytokine. 2015;71:188–98.

    Article  CAS  PubMed  Google Scholar 

  41. Helsel DR. Fabricating data: how substituting values for nondetects can ruin results, and what can be done about it. Chemosphere. 2006;65:2434–9.

    Article  CAS  PubMed  Google Scholar 

  42. Antweiler RC. Evaluation of statistical treatments of left-censored environmental data using coincident uncensored data sets. II. Group comparisons. Environ Sci Technol. 2015;49:13439–46.

    Article  CAS  PubMed  Google Scholar 

  43. Aggarwal CC. Outlier analysis. 1st ed. New York: Springer-Verlag; 2013, pp. XV, 446.

  44. Benjamini Y, Hochberg Y. Controlling the false discovery rate – a practical and powerful approach to multiple testing. J R Stat Soc Ser B Methodol. 1995;57:289–300.

    Google Scholar 

  45. Tibshirani R. Regression shrinkage and selection via the lasso. J R Stat Soc: Ser B Methodol. 1996;58:267–88.

    Google Scholar 

  46. Breiman L. Random forests. Mach Learn. 2001;45:5–32.

    Article  Google Scholar 

  47. Chen T, Guestrin C. XGBoost: a scalable tree boosting system. San Francisco, CA: 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining; 2016, pp. 785–94.

  48. Hoeting JA, Madigan D, Raftery AE, Volinsky CT. Bayesian model averaging: a tutorial. Stat Sci. 1999;14:382–401.

    Google Scholar 

  49. Sanchez-Meca J, Marin-Martinez F, Chacon-Moscoso S. Effect-size indices for dichotomized outcomes in meta-analysis. Psychol Methods. 2003;8:448–67.

    Article  PubMed  Google Scholar 

  50. Cohen J. Statistical power anaysis for the behavioral sciences. 2nd edn. New York: Routledge; 1988.

    Google Scholar 

  51. Efron B, Tibshirani RJ. An introduction to the bootstrap. 1st ed. Norwell, Massachusetts: Chapman & Hall; 1993.

  52. Brucato M, Ladd-Acosta C, Li M, Caruso D, Hong X, Kaczaniuk J, et al. Prenatal exposure to fever is associated with autism spectrum disorder in the boston birth cohort. Autism Res. 2017;10:1878–90.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Zerbo O, Iosif AM, Walker C, Ozonoff S, Hansen RL, Hertz-Picciotto I. Is maternal influenza or fever during pregnancy associated with autism or developmental delays? Results from the CHARGE (CHildhood Autism Risks from Genetics and Environment) study. J Autism Dev Disord. 2013;43:25–33.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Garlanda C, Dinarello CA, Mantovani A. The interleukin-1 family: back to the future. Immunity. 2013;39:1003–18.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Atzeni F, Sarzi-Puttini P. Tumor necrosis factor. In: Maloy S, Kelly H (eds). Brenner’s encyclopedia of genetics. 2nd ed. San Diego, CA: Academic Press; 2013, pp. 229–31.

  56. Sedger LM, McDermott MF. TNF and TNF-receptors: from mediators of cell death and inflammation to therapeutic giants – past, present and future. Cytokine Growth Factor Rev. 2014;25:453–72.

    Article  CAS  PubMed  Google Scholar 

  57. Chez MG, Dowling T, Patel PB, Khanna P, Kominsky M. Elevation of tumor necrosis factor-alpha in cerebrospinal fluid of autistic children. Pediatr Neurol. 2007;36:361–5.

    Article  PubMed  Google Scholar 

  58. Tsilioni I, Taliou A, Francis K, Theoharides TC. Children with autism spectrum disorders, who improved with a luteolin-containing dietary formulation, show reduced serum levels of TNF and IL-6. Transl Psychiatry. 2015;5:e647.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Mizejewski GJ, Lindau-Shepard B, Pass KA. Newborn screening for autism: in search of candidate biomarkers. Biomark Med. 2013;7:247–60.

    Article  CAS  PubMed  Google Scholar 

  60. Mahic M, Mjaaland S, Bovelstad HM, Gunnes N, Susser E, Bresnahan M, et al. Maternal immunoreactivity to herpes simplex virus 2 and risk of autism spectrum disorder in male offspring. mSphere. 2017;2:e00016–17.

  61. Mahic M, Che X, Susser E, Levin B, Reichborn-Kjennerud T, Magnus P, et al. Epidemiological and serological investigation into the role of gestational maternal influenza virus infection and autism spectrum disorders. mSphere. 2017;2:e00159–17.

  62. Stolp HB. Neuropoietic cytokines in normal brain development and neurodevelopmental disorders. Mol Cell Neurosci. 2013;53:63–68.

    Article  CAS  PubMed  Google Scholar 

  63. Chitu V, Gokhan S, Nandi S, Mehler MF, Stanley ER. Emerging roles for CSF-1 receptor and its ligands in the nervous system. Trends Neurosci. 2016;39:378–93.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Nandi S, Gokhan S, Dai XM, Wei S, Enikolopov G, Lin H, et al. The CSF-1 receptor ligands IL-34 and CSF-1 exhibit distinct developmental brain expression patterns and regulate neural progenitor cell maintenance and maturation. Dev Biol. 2012;367:100–13.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Kana V, Desland FA, Casanova-Acebes M, Ayata P, Badimon A, Nabel E, et al. CSF-1 controls cerebellar microglia and is required for motor function and social interaction. J Exp Med. 2019;216:2265–81.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Zengeler KE, Lukens JR. Innate immunity at the crossroads of healthy brain maturation and neurodevelopmental disorders. Nat Rev Immunol. 2021;21:454–68.

    Article  CAS  PubMed  Google Scholar 

  67. Han VX, Patel S, Jones HF, Dale RC. Maternal immune activation and neuroinflammation in human neurodevelopmental disorders. Nat Rev Neurol. 2021;17:564–79.

    Article  PubMed  Google Scholar 

  68. Costa D, Castelo R. Umbilical cord gene expression reveals the molecular architecture of the fetal inflammatory response in extremely preterm newborns. Pediatr Res. 2016;79:473–81.

    Article  CAS  PubMed  Google Scholar 

  69. Shen L, Liu X, Zhang H, Lin J, Feng C, Iqbal J. Biomarkers in autism spectrum disorders: current progress. Clin Chim Acta. 2020;502:41–54.

    Article  CAS  PubMed  Google Scholar 

  70. Levitt P, Campbell DB. The genetic and neurobiologic compass points toward common signaling dysfunctions in autism spectrum disorders. J Clin Invest. 2009;119:747–54.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We dedicate this paper to the memory of Sir Michael (Mike) Rutter, a dear friend and pioneer in autism and child psychiatry research, who helped build the ABC. We thank Wai Hung Wong, Nina Deoras, Parisa Zolfaghari, and Shobun Baile for laboratory analyses, Joy Ukaigwe for data preparation, Meredith Eddy for project coordination, and Kelly Magnus for assistance with manuscript preparation. We are grateful to the families in Norway participating in MoBa and the ABC study. This work was supported by National Institutes of Health grants NS047537 and NS086122, the Jane Botsford Johnson foundation, the Korein Foundation, the Simons Foundation Autism Research Initiative, the Norwegian Ministry of Health and Care Services, the Norwegian Ministry of Education and Research, and Research Council of Norway grants 189457, 190694, and 196452. The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Author information

Author notes

  1. These authors contributed equally: Xiaoyu Che, Mady Hornig.

Authors and Affiliations

  1. Center for Infection and Immunity, Mailman School of Public Health, Columbia University, New York, NY, USA

    Xiaoyu Che & W. Ian Lipkin

  2. Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, USA

    Xiaoyu Che

  3. Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA

    Mady Hornig, Michaeline Bresnahan, Ezra Susser & W. Ian Lipkin

  4. New York State Psychiatric Institute, New York, NY, USA

    Michaeline Bresnahan & Ezra Susser

  5. Norwegian Institute of Public Health, Oslo, Norway

    Camilla Stoltenberg, Per Magnus, Pål Surén, Siri Mjaaland & Ted Reichborn-Kjennerud

  6. Department of Global Public Health, University of Bergen, Bergen, Norway

    Camilla Stoltenberg

  7. Institute of Clinical Medicine, University of Oslo, Oslo, Norway

    Ted Reichborn-Kjennerud

  8. Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA

    W. Ian Lipkin

  9. Department of Pathology and Cell Biology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA

    W. Ian Lipkin

Authors
  1. Xiaoyu Che
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mady Hornig
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Michaeline Bresnahan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Camilla Stoltenberg
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Per Magnus
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Pål Surén
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Siri Mjaaland
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Ted Reichborn-Kjennerud
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Ezra Susser
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. W. Ian Lipkin
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

CS, ES, MB, MH, PM, and WIL developed the experimental design. MH directed cytokine assays. XC directed statistical analyses. WIL and XC wrote the manuscript. CS, ES, MB, MH, PM, PS, SM, TR-K, and WIL contributed to the data analysis, edited, and approved the manuscript.

Corresponding authors

Correspondence to Ezra Susser or W. Ian Lipkin.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Che, X., Hornig, M., Bresnahan, M. et al. Maternal mid-gestational and child cord blood immune signatures are strongly associated with offspring risk of ASD. Mol Psychiatry 27, 1527–1541 (2022). https://doi.org/10.1038/s41380-021-01415-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41380-021-01415-4

This article is cited by

Search

Advanced search

Quick links