Network analysis of canine brain morphometry links tumour risk to oestrogen deficiency and accelerated brain ageing

Nina M. Rzechorzek; Olivia M. Saunders; Lucy V. Hiscox; Tobias Schwarz; Katia Marioni-Henry; David J. Argyle; Jeffrey J. Schoenebeck; Tom C. Freeman

doi:10.1038/s41598-019-48446-0

Network analysis of canine brain morphometry links tumour risk to oestrogen deficiency and accelerated brain ageing

Nina M. Rzechorzek, Olivia M. Saunders, Lucy V. Hiscox, Tobias Schwarz, Katia Marioni-Henry, David J. Argyle, Jeffrey J. Schoenebeck, Tom C. Freeman

Department of Psychology

Research output: Contribution to journal › Article › peer-review

6 Citations (SciVal)

Abstract

Structural ‘brain age’ is a valuable but complex biomarker for several brain disorders. The dog is an unrivalled comparator for neurological disease modeling, however canine brain morphometric diversity creates computational and statistical challenges. Using a data-driven approach, we explored complex interactions between patient metadata, brain morphometry, and neurological disease. Twenty-four morphometric parameters measured from 286 canine brain magnetic resonance imaging scans were combined with clinical parameters to generate 9,438 data points. Network analysis was used to cluster patients according to their brain morphometry profiles. An ‘aged-brain’ profile, defined by a small brain width and volume combined with ventriculomegaly, was revealed in the Boxer breed. Key features of this profile were paralleled in neutered female dogs which, relative to un-neutered females, had an 11-fold greater risk of developing brain tumours. Boxer dog and geriatric dog groups were both enriched for brain tumour diagnoses, despite a lack of geriatric Boxers within the cohort. Our findings suggest that advanced brain ageing enhances brain tumour risk in dogs and may be influenced by oestrogen deficiency—a risk factor for dementia and brain tumours in humans. Morphometric features of brain ageing in dogs, like humans, might better predict neurological disease risk than patient chronological age.

Original language	English
Article number	12506
Journal	Scientific Reports
Volume	9
Issue number	1
Early online date	29 Aug 2019
DOIs	https://doi.org/10.1038/s41598-019-48446-0
Publication status	Published - 31 Dec 2019

Bibliographical note

Funding Information:
The authors gratefully acknowledge the Diagnostic Imaging Service and Dr. Darren Shaw of the Royal (Dick) School of Veterinary Studies for technical and advisory support. MRI scanning facilities were provided by Burgess Diagnostics Ltd., Preston, UK. Graphia Professional is a software product of Kajeka Ltd., Edinburgh, UK. OsiriX Medical Imaging Software was developed by Pixmeo SARL, Bernex, Switzerland. Images of canine breeds were all downloaded via Wikimedia Commons and each modified to remove background image data. Attributions are as follows: AFGH (By SheltieBoy (Flickr: AKC Helena Fall Dog Show 2011) [CC BY 2.0 (https://creativecommons. org/licenses/by/2.0)]); BOX (By Flickr user boxercab (Flickr here) [CC BY 2.0 (https://creativecommons. org/licenses/by/2.0)]); CKCS (By Mário Simoes (Flickr: Cavalier King Charles Spaniel) [CC BY 2.0 (https:// creativecommons.org/licenses/by/2.0)]); CHIH (Photo taken by en:User:Exdumpling in 2004 and uploaded to English Wikipedia as WhiteTanChihuahua.jpg claiming own work with PD-self license); FBUL (By The original uploader was EGILEO at Italian Wikipedia [CC BY 2.0 (https://creativecommons.org/licenses/by/2.0)]; DDBX (By X posid [CC0]); GREY (By FLickr user Scott Feldstein (Flickr here) [CC BY 2.0 (https://creativecommons. org/licenses/by/2.0)]); LAB (By Desaix83, d’après le travail de Chrizwheatley [Public domain]); Shiba Inu (By Takashiba at English Wikipedia [Public domain]); SPOO (By Inbalsigal [CC BY 3.0 (https://creativecommons. org/licenses/by/3.0)]). Photograph in Fig. 4h contributed by lead author. This work was supported by a Wellcome Trust Integrated Training Fellowship for Veterinarians (096409/Z/11/Z to N.M.R) and an MSD Animal Health Connect Bursary (to O.M.S.). T.C.F. is supported by the Roslin Institute Strategic Grant from the Biotechnology and Biological Sciences Research Council (BBSRC BB/P013732/1). Funding sources did not have any involvement in the study design; the collection, analysis and interpretation of data; writing of the report; or the decision to submit the article for publication. The corresponding author had full access to all of the data used in the study and is responsible for the decision to submit this work for publication.

Publisher Copyright:
© 2019, The Author(s).

Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.

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title = "Network analysis of canine brain morphometry links tumour risk to oestrogen deficiency and accelerated brain ageing",

abstract = "Structural {\textquoteleft}brain age{\textquoteright} is a valuable but complex biomarker for several brain disorders. The dog is an unrivalled comparator for neurological disease modeling, however canine brain morphometric diversity creates computational and statistical challenges. Using a data-driven approach, we explored complex interactions between patient metadata, brain morphometry, and neurological disease. Twenty-four morphometric parameters measured from 286 canine brain magnetic resonance imaging scans were combined with clinical parameters to generate 9,438 data points. Network analysis was used to cluster patients according to their brain morphometry profiles. An {\textquoteleft}aged-brain{\textquoteright} profile, defined by a small brain width and volume combined with ventriculomegaly, was revealed in the Boxer breed. Key features of this profile were paralleled in neutered female dogs which, relative to un-neutered females, had an 11-fold greater risk of developing brain tumours. Boxer dog and geriatric dog groups were both enriched for brain tumour diagnoses, despite a lack of geriatric Boxers within the cohort. Our findings suggest that advanced brain ageing enhances brain tumour risk in dogs and may be influenced by oestrogen deficiency—a risk factor for dementia and brain tumours in humans. Morphometric features of brain ageing in dogs, like humans, might better predict neurological disease risk than patient chronological age.",

author = "Rzechorzek, {Nina M.} and Saunders, {Olivia M.} and Hiscox, {Lucy V.} and Tobias Schwarz and Katia Marioni-Henry and Argyle, {David J.} and Schoenebeck, {Jeffrey J.} and Freeman, {Tom C.}",

note = "Funding Information: The authors gratefully acknowledge the Diagnostic Imaging Service and Dr. Darren Shaw of the Royal (Dick) School of Veterinary Studies for technical and advisory support. MRI scanning facilities were provided by Burgess Diagnostics Ltd., Preston, UK. Graphia Professional is a software product of Kajeka Ltd., Edinburgh, UK. OsiriX Medical Imaging Software was developed by Pixmeo SARL, Bernex, Switzerland. Images of canine breeds were all downloaded via Wikimedia Commons and each modified to remove background image data. Attributions are as follows: AFGH (By SheltieBoy (Flickr: AKC Helena Fall Dog Show 2011) [CC BY 2.0 (https://creativecommons. org/licenses/by/2.0)]); BOX (By Flickr user boxercab (Flickr here) [CC BY 2.0 (https://creativecommons. org/licenses/by/2.0)]); CKCS (By M{\'a}rio Simoes (Flickr: Cavalier King Charles Spaniel) [CC BY 2.0 (https:// creativecommons.org/licenses/by/2.0)]); CHIH (Photo taken by en:User:Exdumpling in 2004 and uploaded to English Wikipedia as WhiteTanChihuahua.jpg claiming own work with PD-self license); FBUL (By The original uploader was EGILEO at Italian Wikipedia [CC BY 2.0 (https://creativecommons.org/licenses/by/2.0)]; DDBX (By X posid [CC0]); GREY (By FLickr user Scott Feldstein (Flickr here) [CC BY 2.0 (https://creativecommons. org/licenses/by/2.0)]); LAB (By Desaix83, d{\textquoteright}apr{\`e}s le travail de Chrizwheatley [Public domain]); Shiba Inu (By Takashiba at English Wikipedia [Public domain]); SPOO (By Inbalsigal [CC BY 3.0 (https://creativecommons. org/licenses/by/3.0)]). Photograph in Fig. 4h contributed by lead author. This work was supported by a Wellcome Trust Integrated Training Fellowship for Veterinarians (096409/Z/11/Z to N.M.R) and an MSD Animal Health Connect Bursary (to O.M.S.). T.C.F. is supported by the Roslin Institute Strategic Grant from the Biotechnology and Biological Sciences Research Council (BBSRC BB/P013732/1). Funding sources did not have any involvement in the study design; the collection, analysis and interpretation of data; writing of the report; or the decision to submit the article for publication. The corresponding author had full access to all of the data used in the study and is responsible for the decision to submit this work for publication. Publisher Copyright: {\textcopyright} 2019, The Author(s). Copyright: Copyright 2019 Elsevier B.V., All rights reserved.",

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AU - Rzechorzek, Nina M.

AU - Saunders, Olivia M.

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AU - Schwarz, Tobias

AU - Marioni-Henry, Katia

AU - Argyle, David J.

AU - Schoenebeck, Jeffrey J.

AU - Freeman, Tom C.

N1 - Funding Information: The authors gratefully acknowledge the Diagnostic Imaging Service and Dr. Darren Shaw of the Royal (Dick) School of Veterinary Studies for technical and advisory support. MRI scanning facilities were provided by Burgess Diagnostics Ltd., Preston, UK. Graphia Professional is a software product of Kajeka Ltd., Edinburgh, UK. OsiriX Medical Imaging Software was developed by Pixmeo SARL, Bernex, Switzerland. Images of canine breeds were all downloaded via Wikimedia Commons and each modified to remove background image data. Attributions are as follows: AFGH (By SheltieBoy (Flickr: AKC Helena Fall Dog Show 2011) [CC BY 2.0 (https://creativecommons. org/licenses/by/2.0)]); BOX (By Flickr user boxercab (Flickr here) [CC BY 2.0 (https://creativecommons. org/licenses/by/2.0)]); CKCS (By Mário Simoes (Flickr: Cavalier King Charles Spaniel) [CC BY 2.0 (https:// creativecommons.org/licenses/by/2.0)]); CHIH (Photo taken by en:User:Exdumpling in 2004 and uploaded to English Wikipedia as WhiteTanChihuahua.jpg claiming own work with PD-self license); FBUL (By The original uploader was EGILEO at Italian Wikipedia [CC BY 2.0 (https://creativecommons.org/licenses/by/2.0)]; DDBX (By X posid [CC0]); GREY (By FLickr user Scott Feldstein (Flickr here) [CC BY 2.0 (https://creativecommons. org/licenses/by/2.0)]); LAB (By Desaix83, d’après le travail de Chrizwheatley [Public domain]); Shiba Inu (By Takashiba at English Wikipedia [Public domain]); SPOO (By Inbalsigal [CC BY 3.0 (https://creativecommons. org/licenses/by/3.0)]). Photograph in Fig. 4h contributed by lead author. This work was supported by a Wellcome Trust Integrated Training Fellowship for Veterinarians (096409/Z/11/Z to N.M.R) and an MSD Animal Health Connect Bursary (to O.M.S.). T.C.F. is supported by the Roslin Institute Strategic Grant from the Biotechnology and Biological Sciences Research Council (BBSRC BB/P013732/1). Funding sources did not have any involvement in the study design; the collection, analysis and interpretation of data; writing of the report; or the decision to submit the article for publication. The corresponding author had full access to all of the data used in the study and is responsible for the decision to submit this work for publication. Publisher Copyright: © 2019, The Author(s). Copyright: Copyright 2019 Elsevier B.V., All rights reserved.

PY - 2019/12/31

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N2 - Structural ‘brain age’ is a valuable but complex biomarker for several brain disorders. The dog is an unrivalled comparator for neurological disease modeling, however canine brain morphometric diversity creates computational and statistical challenges. Using a data-driven approach, we explored complex interactions between patient metadata, brain morphometry, and neurological disease. Twenty-four morphometric parameters measured from 286 canine brain magnetic resonance imaging scans were combined with clinical parameters to generate 9,438 data points. Network analysis was used to cluster patients according to their brain morphometry profiles. An ‘aged-brain’ profile, defined by a small brain width and volume combined with ventriculomegaly, was revealed in the Boxer breed. Key features of this profile were paralleled in neutered female dogs which, relative to un-neutered females, had an 11-fold greater risk of developing brain tumours. Boxer dog and geriatric dog groups were both enriched for brain tumour diagnoses, despite a lack of geriatric Boxers within the cohort. Our findings suggest that advanced brain ageing enhances brain tumour risk in dogs and may be influenced by oestrogen deficiency—a risk factor for dementia and brain tumours in humans. Morphometric features of brain ageing in dogs, like humans, might better predict neurological disease risk than patient chronological age.

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Network analysis of canine brain morphometry links tumour risk to oestrogen deficiency and accelerated brain ageing

Abstract

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