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Parsing brain-behavior heterogeneity in very preterm born children using integrated similarity networks

View ORCID ProfileLaila Hadaya, Konstantina Dimitrakopoulou, View ORCID ProfileLucy Vanes, View ORCID ProfileDana Kanel, View ORCID ProfileSunniva Fenn-Moltu, View ORCID ProfileOliver Gale-Grant, View ORCID ProfileSerena J Counsell, View ORCID ProfileA David Edwards, View ORCID ProfileMansoor Saqi, View ORCID ProfileDafnis Batalle, View ORCID ProfileChiara Nosarti
doi: https://doi.org/10.1101/2022.10.20.513074
Laila Hadaya
1Centre for the Developing Brain, Department of Perinatal Imaging and Health, King’s College London, London, United Kingdom
2Department of Child and Adolescent Psychiatry, Institute of Psychiatry Psychology and Neuroscience, King’s College London, London, United Kingdom
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Konstantina Dimitrakopoulou
3Translational Bioinformatics Platform, NIHR Biomedical Research Centre, Guy’s and St. Thomas’ NHS Foundation Trust and King’s College London, London, United Kingdom
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Lucy Vanes
4Centre for Neuroimaging Sciences, Institute of Psychiatry Psychology and Neuroscience, King’s College London, London, United Kingdom
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Dana Kanel
1Centre for the Developing Brain, Department of Perinatal Imaging and Health, King’s College London, London, United Kingdom
2Department of Child and Adolescent Psychiatry, Institute of Psychiatry Psychology and Neuroscience, King’s College London, London, United Kingdom
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Sunniva Fenn-Moltu
1Centre for the Developing Brain, Department of Perinatal Imaging and Health, King’s College London, London, United Kingdom
5Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry Psychology and Neuroscience, King’s College London, London, United Kingdom
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Oliver Gale-Grant
1Centre for the Developing Brain, Department of Perinatal Imaging and Health, King’s College London, London, United Kingdom
5Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry Psychology and Neuroscience, King’s College London, London, United Kingdom
6MRC Centre for Neurodevelopmental Disorders, King’s College London, United Kingdom
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Serena J Counsell
1Centre for the Developing Brain, Department of Perinatal Imaging and Health, King’s College London, London, United Kingdom
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A David Edwards
1Centre for the Developing Brain, Department of Perinatal Imaging and Health, King’s College London, London, United Kingdom
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Mansoor Saqi
3Translational Bioinformatics Platform, NIHR Biomedical Research Centre, Guy’s and St. Thomas’ NHS Foundation Trust and King’s College London, London, United Kingdom
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Dafnis Batalle
1Centre for the Developing Brain, Department of Perinatal Imaging and Health, King’s College London, London, United Kingdom
5Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry Psychology and Neuroscience, King’s College London, London, United Kingdom
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Chiara Nosarti
1Centre for the Developing Brain, Department of Perinatal Imaging and Health, King’s College London, London, United Kingdom
2Department of Child and Adolescent Psychiatry, Institute of Psychiatry Psychology and Neuroscience, King’s College London, London, United Kingdom
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  • For correspondence: chiara.nosarti@kcl.ac.uk
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Abstract

Very preterm birth (VPT; ≤ 32 weeks’ gestation) is associated with altered brain development and cognitive and behavioral difficulties across the lifespan. However, heterogeneity in outcomes among individuals born VPT makes it challenging to identify those most vulnerable to neurodevelopmental sequelae. Here, we aimed to stratify VPT children into distinct behavioral subgroups and explore between-subgroup differences in neonatal brain structure and function. 198 VPT children (98 females) previously enrolled in the Evaluation of Preterm Imaging study (EudraCT 2009-011602-42) underwent Magnetic Resonance Imaging at term-equivalent age and neuropsychological assessments at 4-7 years. Using an integrative clustering approach, we combined neonatal socio-demographic, clinical factors and childhood socio-emotional and executive function outcomes, to identify distinct subgroups of children based on their similarity profiles in a multidimensional space. We characterized resultant subgroups using domain-specific outcomes (temperament, psychopathology, IQ and cognitively stimulating home environment) and explored between-subgroup differences in neonatal brain volumes (voxel-wise Tensor-Based-Morphometry), functional connectivity (voxel-wise degree centrality) and structural connectivity (Tract-Based-Spatial-Statistics). Results showed two-and three-cluster data-driven solutions. The two-cluster solution comprised a ‘resilient’ subgroup (lower psychopathology and higher IQ, executive function and socio-emotional outcomes) and an ‘at-risk’ subgroup (poorer behavioral and cognitive outcomes). The three-cluster solution showed an additional third ‘intermediate’ subgroup displaying behavioral and cognitive outcomes intermediate between the resilient and at-risk subgroups. The resilient subgroup had the most cognitively stimulating home environment and the at-risk subgroup showed the highest neonatal clinical risk, while the intermediate subgroup showed the lowest clinical but the highest socio-demographic risk. Compared to the intermediate subgroup, the resilient subgroup displayed larger neonatal insular and orbitofrontal volumes and stronger orbitofrontal functional connectivity, while the at-risk group showed widespread white matter microstructural alterations. These findings suggest that risk stratification following VPT birth is feasible and could be used translationally to guide personalized interventions aimed at promoting children’s resilience.

Competing Interest Statement

The authors have declared no competing interest.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted October 21, 2022.
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Parsing brain-behavior heterogeneity in very preterm born children using integrated similarity networks
Laila Hadaya, Konstantina Dimitrakopoulou, Lucy Vanes, Dana Kanel, Sunniva Fenn-Moltu, Oliver Gale-Grant, Serena J Counsell, A David Edwards, Mansoor Saqi, Dafnis Batalle, Chiara Nosarti
bioRxiv 2022.10.20.513074; doi: https://doi.org/10.1101/2022.10.20.513074
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Parsing brain-behavior heterogeneity in very preterm born children using integrated similarity networks
Laila Hadaya, Konstantina Dimitrakopoulou, Lucy Vanes, Dana Kanel, Sunniva Fenn-Moltu, Oliver Gale-Grant, Serena J Counsell, A David Edwards, Mansoor Saqi, Dafnis Batalle, Chiara Nosarti
bioRxiv 2022.10.20.513074; doi: https://doi.org/10.1101/2022.10.20.513074

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