Identification of novel genome-wide associations for suicidality in UK Biobank, genetic correlation with psychiatric disorders and polygenic association with completed suicide

Strawbridge, R. J. et al. (2019) Identification of novel genome-wide associations for suicidality in UK Biobank, genetic correlation with psychiatric disorders and polygenic association with completed suicide. EBioMedicine, 41, pp. 517-525. (doi: 10.1016/j.ebiom.2019.02.005) (PMID:30745170) (PMCID:PMC6442001)

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Abstract

Background: Suicide is a major issue for global public health. Suicidality describes a broad spectrum of thoughts and behaviours, some of which are common in the general population. Although suicide results from a complex interaction of multiple social and psychological factors, predisposition to suicidality is at least partly genetic. Methods: Ordinal genome-wide association study of suicidality in the UK Biobank cohort comparing: ‘no suicidality’ controls (N = 83,557); ‘thoughts that life was not worth living’ (N = 21,063); ‘ever contemplated self-harm’ (N = 13,038); ‘act of deliberate self-harm in the past’ (N = 2498); and ‘previous suicide attempt’ (N = 2666). Outcomes: We identified three novel genome-wide significant loci for suicidality (on chromosomes nine, 11 and 13) and moderate-to-strong genetic correlations between suicidality and a range of psychiatric disorders, most notably depression (rg 0·81). Interpretation: These findings provide new information about genetic variants relating to increased risk of suicidal thoughts and behaviours. Future work should assess the extent to which polygenic risk scores for suicidality, in combination with non-genetic risk factors, may be useful for stratified approaches to suicide prevention at a population level.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Smith, Professor Daniel and Cullen, Dr Breda and Mackay, Professor Daniel and Langan-Martin, Dr Julie and Graham, Dr Nicholas and Ferguson, Ms Amy and Pearsall, Dr Robert and Lyall, Dr Laura and Bailey, Dr Mark and Niedzwiedz, Dr Claire and Shaw, Dr Richard and Ward, Dr Joey and Johnston, Ms Keira and Pell, Professor Jill and Lyall, Dr Donald and Strawbridge, Dr Rona
Authors: Strawbridge, R. J., Ward, J., Ferguson, A., Graham, N., Shaw, R. J., Cullen, B., Pearsall, R., Lyall, L. M., Johnston, K. J.A., Niedzwiedz, C. L., Pell, J. P., Mackay, D., Langan-Martin, J., Lyall, D. M., Bailey, M. E.S., and Smith, D. J.
College/School:College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > Mental Health and Wellbeing
College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > Public Health
College of Medical Veterinary and Life Sciences > School of Molecular Biosciences
Journal Name:EBioMedicine
Publisher:Elsevier
ISSN:2352-3964
ISSN (Online):2352-3964
Published Online:08 February 2019
Copyright Holders:Copyright © 2019 The Authors
First Published:First published in EBioMedicine 41:517-525
Publisher Policy:Reproduced under a Creative Commons License

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
3021310Understanding the excess risk of cardiometabolic disease in individuals with serious mental illnessJill PellMedical Research Council (MRC)MR/S003061/1HW - Public Health
632345MRC Doctoral Training Grant 2013/14, 2014/15 and 2015/16George BaillieMedical Research Council (MRC)MR/S003061/1MVLS GRADUATE SCHOOL
3021820A machine learning approach to understanding comorbidity between mental and physical health conditionsJill PellMedical Research Council (MRC)MR/R024774/1HW - Public Health
3029570Mental Health Data PathfinderDaniel SmithMedical Research Council (MRC)MC_PC_17217HW - Mental Health and Wellbeing