Magnitude and variability of structural brain abnormalities in neuropsychiatric disease: Protocol for a network meta-analysis of MRI studies

Robert McCutcheon; Toby Pillinger; George Welby; Luke Vano; Connor Cummings; Xin Guo; Toni Ann Heron; Orestis Efthimiou; Andrea Cipriani; Oliver Howes

doi:10.1136/ebmental-2020-300229

Original language	English
Article number	ebmental-2020-300229
Pages (from-to)	111-114
Number of pages	4
Journal	Evidence-Based Mental Health
Volume	24
Issue number	3
DOIs	https://doi.org/10.1136/ebmental-2020-300229
Accepted/In press	2021
Published	1 Aug 2021
Additional links	Link to publication in Scopus

Bibliographical note

Funding Information: Competing interests RAM, GW, LV, CC, XG, TAH and OE declare no competing interests. AC has received research and consultancy fees from INCiPiT (Italian Network for Paediatric Trials), CARIPLO Foundation and Angelini Pharma, outside the submitted work. TP has participated in speaker meetings organised by Sunovion, Lundbeck, and Otsuka. ODH has received investigator-initiated research funding from and/or participated in advisory/ speaker meetings organised by Astra-Zeneca, Autifony, BMS, Eli Lilly, Heptares, Jansenn, Lundbeck, Lyden-Delta, Otsuka, Servier, Sunovion, Rand and Roche. Neither Dr Howes or his family have been employed by or have holdings/ a financial stake in any biomedical company. Funding Information: Contributors RMC and TP participated in the conception, drafting, revising and final approval of this manuscript. GW, LV, CC, XG, TAH, OE, AC and OH participated in the revising and final approval of this manuscript Funding TP and RM are funded by the NIHR. OH is funded by Medical Research Council-UK (no. MC-A656-5QD30), Maudsley Charity (no. 666), Brain and BehaviorBehaviour Research Foundation, and Wellcome Trust (no. 094849/Z/10/Z) grants and the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London, and by NIHR. OE is supported by Ambizione grant No. 180 083 from the Swiss National Science Foundation (SNSF). AC is supported by the National Institute for Health Research (NIHR) Oxford Cognitive Health Clinical Research Facility, by an NIHR Research Professorship (grant RP-2017-08-ST2-006), by the NIHR Oxford and Thames Valley Applied Research Collaboration and by the NIHR Oxford Health Biomedical Research Centre (grant BRC-1215-20005). The views expressed are those of the authors and not necessarily those of the UK National Health Service, the NIHR, or the UK Department of Health. The funders had no role in the design of the protocol. Publisher Copyright: © 2021 BMJ Publishing Group. All rights reserved. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

Abstract

Introduction Structural MRI is the most frequently used method to investigate brain volume alterations in neuropsychiatric disease. Previous meta-Analyses have typically focused on a single diagnosis, thereby precluding transdiagnostic comparisons. Methods and analysis We will include all structural MRI studies of adults that report brain volumes for participants from at least two of the following diagnostic groups: healthy controls, schizophrenia, schizoaffective disorder, delusional disorder, psychotic depression, clinical high risk for psychosis, schizotypal personality disorder, psychosis unspecified, bipolar disorder, autism spectrum disorder, major depressive disorder, attention deficit hyperactivity disorder, obsessive compulsive disorder, post-Traumatic stress disorder, emotionally unstable personality disorder, 22q11 deletion syndrome, generalised anxiety disorder, social anxiety disorder, panic disorder, mixed anxiety and depression. Network meta-Analysis will be used to synthesise eligible studies. The primary analysis will examine standardised mean difference in average volume, a secondary analysis will examine differences in variability of volumes. Discussion This network meta-Analysis will provide a transdiagnostic integration of structural neuroimaging studies, providing researchers with a valuable summary of a large literature. PROSPERO registration number CRD42020221143.

King's College London

Research portal