On the brain structure heterogeneity of autism: Parsing out acquisition site effects with significance-weighted principal component analysis
Martinez-Murcia, Francisco Jesús, Lai, Meng-Chuan, Górriz, Juan Manuel, Ramírez, Javier, Young, Adam M. H., Deoni, Sean C. L., Ecker, Christine, Lombardo, Michael V., Baron-Cohen, Simon, Murphy, Declan G. M., Bullmore, Edward T., Suckling, John, Bailey, Anthony J., Baron-Cohen, Simon, Bolton, Patrick F., Bullmore, Edward T., Carrington, Sarah, Catani, Marco, Chakrabarti, Bhismadev, ... Williams, Steven C.. (2017). On the brain structure heterogeneity of autism: Parsing out acquisition site effects with significance-weighted principal component analysis. Human Brain Mapping. 38(3), pp. 1208 - 1223. https://doi.org/10.1002/hbm.23449
|Authors||Martinez-Murcia, Francisco Jesús, Lai, Meng-Chuan, Górriz, Juan Manuel, Ramírez, Javier, Young, Adam M. H., Deoni, Sean C. L., Ecker, Christine, Lombardo, Michael V., Baron-Cohen, Simon, Murphy, Declan G. M., Bullmore, Edward T., Suckling, John, Bailey, Anthony J., Baron-Cohen, Simon, Bolton, Patrick F., Bullmore, Edward T., Carrington, Sarah, Catani, Marco, Chakrabarti, Bhismadev, Craig, Michael C., Daly, Eileen M., Deoni, Sean C. L., Ecker, Christine, Happé, Francesca, Henty, Julian, Jezzard, Peter, Johnston, Patrick, Jones, Derek Kenton, Lai, Meng Chuan, Lombardo, Michael V., Madden, Anya, Mullins, Diane, Murphy, Clodagh M., Murphy, Declan G. M., Pasco, Greg, Ruigrok, Amber N. V., Sadek, Susan A., Spain, Debbie, Stewart, Rose, Suckling, John, Wheelwright, Sally J. and Williams, Steven C.|
Neuroimaging studies have reported structural and physiological differences that could help understand the causes and development of Autism Spectrum Disorder ( ASD ). Many of them rely on multisite designs, with the recruitment of larger samples increasing statistical power. However, recent large-scale studies have put some findings into question, considering the results to be strongly dependent on the database used, and demonstrating the substantial heterogeneity within this clinically defined category. One major source of variance may be the acquisition of the data in multiple centres. In this work we analysed the differences found in the multisite, multi-modal neuroimaging database from the UK Medical Research Council Autism Imaging Multicentre Study ( MRC AIMS ) in terms of both diagnosis and acquisition sites. Since the dissimilarities between sites were higher than between diagnostic groups, we developed a technique called Significance Weighted Principal Component Analysis ( SWPCA ) to reduce the undesired intensity variance due to acquisition site and to increase the statistical power in detecting group differences. After eliminating site-related variance, statistically significant group differences were found, including Broca's area and the temporo-parietal junction. However, discriminative power was not sufficient to classify diagnostic groups, yielding accuracies results close to random. Our work supports recent claims that ASD is a highly heterogeneous condition that is difficult to globally characterize by neuroimaging, and therefore different ( and more homogenous ) subgroups should be defined to obtain a deeper understanding of ASD.
|Keywords||autism spectrum disorder; structural magnetic resonance imaging; structural heterogeneity; voxel based morphometry|
|Journal||Human Brain Mapping|
|Journal citation||38 (3), pp. 1208 - 1223|
|Publisher||John Wiley & Sons, Inc.|
|Digital Object Identifier (DOI)||https://doi.org/10.1002/hbm.23449|
|Open access||Open access|
|Page range||1208 - 1223|
© 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
|Place of publication||United States|
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