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Authors' reply

Published online by Cambridge University Press:  02 January 2018

Michael P. Harms
Affiliation:
Department of Psychiatry (Box 8134), Washington University School of Medicine, 660 S. Euclid Ave, St Louis, MO 63110, USA. Email: mharms@conte.wustl.edu
Lei Wang
Affiliation:
Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago
Carolina Campanella
Affiliation:
Department of Psychiatry, Washington University School of Medicine, St Louis
Kristina Aldridge
Affiliation:
Department of Pathology and Anatomical Sciences, University of Missouri School of Medicine, Columbia
Amanda J. Moffitt
Affiliation:
Department of Pathology and Anatomical Sciences, University of Missouri School of Medicine, Columbia
John Kuelper
Affiliation:
Department of Psychiatry, Washington University School of Medicine, St Louis
J. Tilak Ratnanather
Affiliation:
Center for Imaging Science, The Johns Hopkins University, Baltimore
Michael I. Miller
Affiliation:
Center for Imaging Science, The Johns Hopkins University, Baltimore
Deanna M. Barch
Affiliation:
Department of Psychiatry, Washington University School of Medicine and Department of Psychology, Washington University, St Louis
John G. Csernansky
Affiliation:
Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, USA
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Abstract

Type
Columns
Copyright
Copyright © Royal College of Psychiatrists, 2010 

We fully agree with Dr Palaniyappan that the manner in which regional measures are controlled for possible global changes has important implications for the interpretation of a study. In our study of prefrontal regions in individuals with schizophrenia and their siblings, we used global brain covariates matched in type (volume, surface area or thickness) to the structural measure being analysed. Reference Goghari, Rehm, Carter and MacDonald1 Regardless of the type of measure, the inclusion of an appropriate matched covariate is justified, so that the resulting statistical analysis can address the question of whether any regional differences between groups were in excess of possible global brain changes. We did not use intracranial volume as the covariate in our volume analyses because: (a) it is difficult to estimate accurately from T 1-weighted magnetic resonance images; and (b) it does not actually control for decreases in overall brain volume that may occur following the completion of skull growth. Rather, we used an estimate of non-prefrontal cortical grey matter volume as the covariate for the volume analyses, obtained by subtracting the sum of our estimates of prefrontal grey matter from a measure of overall cortical grey matter. The use of a ‘rest of the brain’ covariate of this sort is common, Reference Barton and Harvey2,Reference Rilling and Seligman3 so as to avoid using a covariate which itself includes a substantial contribution from the dependent variable of interest. In our study, non-prefrontal cortical grey matter volume itself differed between groups. Yet, even with the inclusion of this covariate the volumes of the inferior and middle frontal gyri differed between groups, indicating that the differences present in these gyri were in excess of differences that would be predicted based on the grey matter volume differences present in the rest of the brain.

Similarly, inclusion of a global thickness covariate was appropriate and necessary so that we could address whether any regional thickness differences were in excess of global cortical thickness differences between groups. Reference Goghari, Rehm, Carter and MacDonald1,Reference Kuperberg, Broome, McGuire, David, Eddy and Ozawa4 Since the computation of a ‘rest of the brain’ thickness was not possible (see Method), Reference Harms, Wang, Campanella, Aldridge, Moffitt and Kuelper5 the thickness covariate was the mean thickness of the whole cortex. Because prefrontal cortex was included in this overall measure, our thickness analyses should be viewed as conservative (i.e. biased towards finding a null result).

We agree that measures of cortical volume combine two distinct sources of genetic effects (thickness and surface area). Reference Panizzon, Fennema-Notestine, Eyler, Jernigan, Prom-Wormley and Neale6 As mentioned in our results, in the absence of covarying for overall brain changes we found statistically significant group differences for thickness and area of the inferior and middle frontal gyri. Further, the pattern of the thickness and area changes across groups was qualitatively similar to the pattern of the volume differences within these two gyri. Thus, we believe that changes in thickness and area both contributed to the volume differences across groups in these gyri, even if the thickness and area results did not themselves reach statistical significance after rigorously controlling for overall brain changes.

Footnotes

Edited by Kiriakos Xenitidis and Colin Campbell

References

1 Goghari, VM, Rehm, K, Carter, CS, MacDonald, AW 3rd. Regionally specific cortical thinning and gray matter abnormalities in the healthy relatives of schizophrenia patients. Cereb Cortex 2007; 17: 415–24.Google Scholar
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3 Rilling, JK, Seligman, RA. A quantitative morphometric comparative analysis of the primate temporal lobe. J Hum Evol 2002; 42: 505–33.CrossRefGoogle ScholarPubMed
4 Kuperberg, GR, Broome, MR, McGuire, PK, David, AS, Eddy, M, Ozawa, F, et al. Regionally localized thinning of the cerebral cortex in schizophrenia. Arch Gen Psychiatry 2003; 60: 878–88.Google Scholar
5 Harms, MP, Wang, L, Campanella, C, Aldridge, K, Moffitt, AJ, Kuelper, J, et al. Structural abnormalities in gyri of the prefrontal cortex in individuals with schizophrenia and their unaffected siblings. Br J Psychiatry 2010; 196: 150–7.CrossRefGoogle ScholarPubMed
6 Panizzon, MS, Fennema-Notestine, C, Eyler, LT, Jernigan, TL, Prom-Wormley, E, Neale, M, et al. Distinct genetic influences on cortical surface area and cortical thickness. Cereb Cortex 2009; 19: 2728–35.Google Scholar
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