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Altered resting-state networks associated with chronic itching in adolescents with atopic eczema

Poster No:

325

Submission Type:

Abstract Submission

Authors:

Xin Yi Ng¹^,2, Ines Argoub², Ullrich Bartsch³, Conor Broderick², Shona Cameron², Paola Dazzan⁴, Jesper Elberling⁵, Paul Gringras⁶, Desaline Joseph⁶, Ruchika Kumari², Nicole Mariani⁴, Carmine Pariante⁴, Samiha Rahman², Katya Rubia⁷, Alessandra Vigilante⁸^,9, Tobias Wood¹⁰, Alphonsus Yip², Carsten Flohr², Tomoki Arichi¹

Institutions:

¹Early Life Imaging Research Department, School of Biomedical Engineering and Imaging Sciences, King's College London, Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom, ²St John's Institute of Dermatology, King's College London, Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom, ³Surrey Sleep Research Centre, University of Surrey, Guildford, United Kingdom, ⁴Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom, ⁵Department of Dermatology and Allergy, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark, ⁶Paediatric Sleep Department, Evelina Children's Hospital, King's College London, Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom, ⁷Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom, ⁸Centre for Gene Therapy and Regenerative Medicine, School of Basic and Medical Biosciences, King's College London, London, United Kingdom, ⁹Hub for Applied Bioinformatics, King's College London, London, United Kingdom, ¹⁰Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom

First Author:

Xin Yi Ng
Early Life Imaging Research Department, School of Biomedical Engineering and Imaging Sciences|St John's Institute of Dermatology, King's College London, Guy's and St Thomas' NHS Foundation Trust
King's College London, Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom|London, United Kingdom

Co-Author(s):

Ines Argoub
St John's Institute of Dermatology, King's College London, Guy's and St Thomas' NHS Foundation Trust
London, United Kingdom

Ullrich Bartsch
Surrey Sleep Research Centre, University of Surrey
Guildford, United Kingdom

Conor Broderick
St John's Institute of Dermatology, King's College London, Guy's and St Thomas' NHS Foundation Trust
London, United Kingdom

Shona Cameron
St John's Institute of Dermatology, King's College London, Guy's and St Thomas' NHS Foundation Trust
London, United Kingdom

Paola Dazzan
Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience
King's College London, London, United Kingdom

Jesper Elberling
Department of Dermatology and Allergy, Herlev and Gentofte Hospital, University of Copenhagen
Copenhagen, Denmark

Paul Gringras
Paediatric Sleep Department, Evelina Children's Hospital, King's College London
Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom

Desaline Joseph
Paediatric Sleep Department, Evelina Children's Hospital, King's College London
Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom

Ruchika Kumari
St John's Institute of Dermatology, King's College London, Guy's and St Thomas' NHS Foundation Trust
London, United Kingdom

Nicole Mariani
Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience
King's College London, London, United Kingdom

Carmine Pariante
Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience
King's College London, London, United Kingdom

Samiha Rahman
St John's Institute of Dermatology, King's College London, Guy's and St Thomas' NHS Foundation Trust
London, United Kingdom

Katya Rubia
Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience
King's College London, London, United Kingdom

Alessandra Vigilante
Centre for Gene Therapy and Regenerative Medicine, School of Basic and Medical Biosciences|Hub for Applied Bioinformatics, King's College London
King's College London, London, United Kingdom|London, United Kingdom

Tobias Wood
Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience
King's College London, London, United Kingdom

Alphonsus Yip
St John's Institute of Dermatology, King's College London, Guy's and St Thomas' NHS Foundation Trust
London, United Kingdom

Carsten Flohr
St John's Institute of Dermatology, King's College London, Guy's and St Thomas' NHS Foundation Trust
London, United Kingdom

Tomoki Arichi
Early Life Imaging Research Department, School of Biomedical Engineering and Imaging Sciences
King's College London, Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom

Introduction:

Chronic inflammatory disorders have been shown to contribute to neuroinflammation, which in turn has been associated with alterations in functional connectivity. In atopic dermatitis, also known as atopic eczema (AE), a T-helper 2-mediated skin condition, patients suffer from chronic itching and scratching behaviour which further damages the skin and exacerbates cutaneous inflammation, leading to a vicious cycle of further itching and worsening inflammation (Cameron et al., 2024). AE patients also experience severe itching-scratching behaviour at night, leading to poor sleep quality. This is of further relevance as chronic sleep disturbances, particularly during early life, can alter brain development and neural connectivity. In this study, we aim to investigate whether resting-state functional connectivity differs between adolescent AE patients and healthy controls.

Methods:

16 AE adolescent patients with a range of disease severity (median age: 15, range: 12-18 years) and 9 healthy controls (median age: 15, range: 12-16 years) were recruited for the study. High-resolution structural MRI scans were acquired with both the 3D T1-weighted Magnetization-Prepared Rapid Gradient Echo (MPRAGE) and T2-weighted-Fluid-Attenuated Inversion Recovery (T2-FLAIR) sequences. Blood Oxygen Level Dependent (BOLD)-contrast resting fMRI scans were acquired from the participants with a multiband echo-planar imaging (EPI) sequence (Multiband acceleration factor = 4, TR = 933ms, TE = 32ms, FOV = 221 x 221 mm, Resolution = 2.7mm isotropic, Flip angle = 60°; 525 volumes). All MRI data were scanned on a 3.0 Tesla GE SIGNA Premier Scanner at the Centre for Neuroimaging Sciences, King's College London.

fMRI scans were preprocessed using fMRIprep (version 23.2.1) which includes motion correction, susceptibility distortion correction, slice timing correction and registration of fMRI scans to their respective T1 MPRAGE scans and MNI space (Esteban et al., 2019). White matter, cerebrospinal fluid, as well as 24 motion-related confounds, were regressed from the processed scans using Nilearn (Abraham et al., 2014). The fMRI data were then further preprocessed with the following steps on FSL (version 6.0.7.6): i) removal of the first 3 volumes, ii) spatial smoothing with 5mm FWHM and iii) high-pass temporal filtering with a threshold of 150s (Jenkinson et al., 2012). Single-subject ICA was then carried out using FSL's MELODIC and components classified as related to physiological noise, motion artefact, or multiband effects were regressed from the data (Beckmann & Smith, 2004; Jenkinson et al., 2012). The denoised data were then temporally concatenated for group ICA with a dimensionality of 30, followed by dual regression analysis to evaluate differences between the 2 groups controlling for the effects of age and eczema area and severity index (Nickerson et al., 2017).

Results:

16 resting-state networks were identified from the group ICA. In AE patients, there were significant increases in functional connectivity within the somatosensory-motor network. Significantly greater functional connectivity was also seen between the visual cortex and the temporoparietal network (TPN) in healthy controls compared to AE patients.

Conclusions:

This preliminary data suggests that AE patients exhibit enhanced somatosensory-motor functional connectivity, likely associated with chronic itching-scratching behaviours. We additionally identified decreased TPN-visual connectivity in AE patients. The temporoparietal junction (TPJ) has been suggested to be a multisensory integration hub and is crucial for visual-spatial attention to external stimuli. Increased somatosensory connectivity in AE patients could interfere with visual connectivity to the TPJ, possibly contributing to reduced attention to external stimuli. These alterations may reflect the neuropsychological effects of chronic itching-scratching behaviours in AE.

Disorders of the Nervous System:

Neurodevelopmental/ Early Life (eg. ADHD, autism) ¹

Modeling and Analysis Methods:

fMRI Connectivity and Network Modeling

Perception, Attention and Motor Behavior:

Perception: Tactile/Somatosensory ²

Keywords:

Somatosensory

Other - Resting-state networks; functional connectivity; itch; atopic dermatitis; atopic eczema; inflammation

^1|2Indicates the priority used for review

Abstract Information

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Please indicate below if your study was a "resting state" or "task-activation” study.

Resting state

Healthy subjects only or patients (note that patient studies may also involve healthy subjects):

Patients

Was this research conducted in the United States?

Were any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.

Yes

Were any animal research approved by the relevant IACUC or other animal research panel? NOTE: Any animal studies without IACUC approval will be automatically rejected.

Not applicable

Please indicate which methods were used in your research:

Functional MRI

Structural MRI

For human MRI, what field strength scanner do you use?

3.0T

Which processing packages did you use for your study?

AFNI

FSL

Free Surfer

Other, Please list - fMRIprep (version 23.2.1)

Provide references using APA citation style.

Abraham, A., Pedregosa, F., Eickenberg, M., Gervais, P., Mueller, A., Kossaifi, J., Gramfort, A., Thirion, B., & Varoquaux, G. (2014). Machine learning for neuroimaging with scikit-learn [Methods]. Frontiers in Neuroinformatics, 8. https://doi.org/10.3389/fninf.2014.00014

Beckmann, C. F., & Smith, S. M. (2004). Probabilistic independent component analysis for functional magnetic resonance imaging. IEEE Trans Med Imaging, 23(2), 137-152. https://doi.org/10.1109/tmi.2003.822821

Cameron, S., Donnelly, A., Broderick, C., Arichi, T., Bartsch, U., Dazzan, P., Elberling, J., Godfrey, E., Gringras, P., Heathcote, L. C., Joseph, D., Wood, T. C., Pariante, C., Rubia, K., & Flohr, C. (2024). Mind and skin: Exploring the links between inflammation, sleep disturbance and neurocognitive function in patients with atopic dermatitis. Allergy, 79(1), 26-36. https://doi.org/https://doi.org/10.1111/all.15818

Esteban, O., Markiewicz, C. J., Blair, R. W., Moodie, C. A., Isik, A. I., Erramuzpe, A., Kent, J. D., Goncalves, M., DuPre, E., Snyder, M., Oya, H., Ghosh, S. S., Wright, J., Durnez, J., Poldrack, R. A., & Gorgolewski, K. J. (2019). fMRIPrep: a robust preprocessing pipeline for functional MRI. Nature Methods, 16(1), 111-116. https://doi.org/10.1038/s41592-018-0235-4

Jenkinson, M., Beckmann, C. F., Behrens, T. E. J., Woolrich, M. W., & Smith, S. M. (2012). FSL. NeuroImage, 62(2), 782-790. https://doi.org/https://doi.org/10.1016/j.neuroimage.2011.09.015

Nickerson, L. D., Smith, S. M., Öngür, D., & Beckmann, C. F. (2017). Using Dual Regression to Investigate Network Shape and Amplitude in Functional Connectivity Analyses. Front Neurosci, 11, 115. https://doi.org/10.3389/fnins.2017.00115

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