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(WCPG): Oral Abstracts ARTICLE IN PRESS JID: NEUPSY [m6+; October 3, 2018;8:33 ] European Neuropsychopharmacology (2018) 000, 1–44 www.elsevier.com/locate/euroneuro Abstracts of the 26th World Congress of Psychiatric Genetics (WCPG): Oral Abstracts Friday, October 12, 2018 Results: All PRS significantly predicted MDD status. When stratified by early and late onset, PRS for coronary artery disease, stroke, BMI, and type 2 diabetes also significantly predicted late onset MDD, with coronary artery disease, Oral Session: Depression BMI, and type 2 diabetes also predicting early onset MDD. 1:30 p.m. - 3:00 p.m. Significant genetic correlations were identified between MDD and the cardio-metabolic traits. I will also discuss find- 1 ings from age at onset stratified genetic correlations. GENETIC COMORBIDITY BETWEEN DEPRESSION AND Discussion: This study provides possible support for the vas- CARDIO-METABOLIC DISEASE, STRATIFIED BY AGE AT cular depression hypothesis by showing a genetic association ONSET between late onset MDD and cardio-metabolic traits. ∗ Saskia Hagenaars 1, , Jonathan Coleman 1, Disclosure: Nothing to disclose. 1 1 Helena Alexandra Gaspar , Karen Hodgson , The PGC MDD doi: 10.1016/j.euroneuro.2018.08.008 Consortium, METASTROKE Consortium 2, Gerome Breen 1, Cathryn Lewis 1 2 1 King’s College London DOES HIGH BMI IN THE ABSENCE OF METABOLIC 2 University of Virginia CONSEQUENCES CAUSE DEPRESSION? ∗ Background: The association between major depressive dis- Jess Tyrrell 1, , Anwar Mulugeta 2, Andrew Wood 1, order (MDD) and cardio-metabolic disease is well estab- Ang Zhou 2, Robin Beaumont 1, Marcus Tuke 1, lished. MDD increases the risk of cardio-metabolic disease Samuel Jones 1, Katherine Ruth 1, Hanieh Yaghootkar 1, onset and mortality, but cardio-metabolic disease itself can Cathryn Lewis 3, Tim Frayling 1, Elina Hypponen 2 also increase risk of developing MDD. However, the underly- ing mechanisms of the association between MDD and cardio- 1 University of Exeter metabolic disease remain elusive. A possible mechanism 2 University of South Australia may be represented by cerebrovascular disease and its risk 3 King’s College London factors predisposing MDD in later life, according to the ‘vas- cular depression’ hypothesis. Background: Depression is more common in obese than non- Methods: Polygenic risk score (PRS) analysis was used to ex- obese individuals, but the causal relationship between obe- amine how coronary artery disease, stroke, and type 2 dia- sity and depression is complex and uncertain. Previous stud- betes predict MDD status, stratified by early and late age ies have used Mendelian randomisation to provide evidence at onset in the Psychiatric Genomics Consortium and UK that higher body mass index (BMI) causes depression but Biobank (N early onset MDD ∼ 16K, late onset MDD ∼16K, have not tested whether this relationship is driven by the controls ∼67K). Genome-wide association studies were per- metabolic consequences of BMI or differs between men and formed with MDD cases stratified by early and late age at women. onset, in order to calculate genetic correlations between Methods: We performed a Mendelian randomisation study cardio-metabolic traits and early and late age at onset for using 48 791 individuals with depression and 291 995 con- MDD. trols in the UK Biobank to test for causal effects of higher BMI on depression. We used two genetic instruments, both 0924-977X ARTICLE IN PRESS JID: NEUPSY [m6+; October 3, 2018;8:33 ] 2 Abstracts representing higher BMI, but one with and one without its (0.87, s.e. = 0.04) with Wray et al (2018). This provided a adverse metabolic consequences, in an attempt to “un- total of 807,553 individuals (246,363 cases and 561,190 con- couple” the psychological component of obesity from the trols) with which to conduct the meta-analysis and further metabolic consequences. We further tested causal relation- downstream analyses. ships in men and women separately. Results: The genome-wide meta-analysis of the three con- Results: Higher BMI was strongly associated with higher odds tributing cohorts revealed a total of 118 independent sig- of depression, especially in women. Mendelian randomisa- nificant (P < 5 × 10 −8) variants associated with depres- tion provided evidence that higher BMI partly causes de- sion. The estimate of the heritability on the liability scale pression, with a genetically determined 1 SD higher BMI was 0.089 (0.003) with genetic correlations identified for (4.9 kg/m2) associated with higher odds of depression in 33 other traits, including bipolar disorder, schizophrenia, all individuals (Odds ratio (OR) 1.18 [95%CI: 1.09-1.28], smoking and triglyceride levels. We identified 269 genes and P = 0.00007) and women only (OR: 1.24 [95%CI: 1.11-1.39], 14 gene-sets that were significantly associated with depres- P = 0.0001). Meta-analysis with 45 591 depression cases and sion, including gene-sets involved in synaptic transmission. 97 647 controls, from the Psychiatric Genomics Consortium Discussion: This research presents the results from a rela- (PGC) strengthened the statistical confidence of the find- tively well-powered genetic analysis of depression, by com- ings in all individuals. Using a metabolically favourable adi- bining previous studies of the condition. A marked increase posity genetic risk score, and meta-analysing data from UK in the number of associated variants and genes was ob- Biobank and PGC, a genetically determined 1 SD higher BMI served which will enable additional comprehension of the (4.9 kg/m2) was associated with higher odds of depression underlying biological aetiology. The gene-sets identified as in all individuals (OR: 1.26 [95%CI: 1.06-1.50], P = 0.010. significant typically relate to brain function and may ulti- Discussion: Higher BMI, with and without its adverse mately allow us to identify the molecular mechanisms un- metabolic consequences, is likely to have a causal role in derlying genetic predisposition to depression. determining the likelihood of an individual developing de- pression. Disclosure: Nothing to disclose. doi: 10.1016/j.euroneuro.2018.08.010 Disclosure: Nothing to disclose. doi: 10.1016/j.euroneuro.2018.08.009 4 DETERMINING THE RELATIONSHIP BETWEEN CANNABIS 3 USE AND MAJOR DEPRESSION IN UK BIOBANK GENOME-WIDE META-ANALYSIS OF DEPRESSION Karen Hodgson ∗, Saskia Hagenaars, Kirstin Purves, ∗ David Howard 1, , Mark J. Adams 1, Toni-Kim Clarke 1, Helena Alexandra Gaspar, Kylie Glanville, Jonathan D. Hafferty 1, Jude Gibson 1, Jonathan Coleman, Marta Di Forti, Gerome Breen, Jonathan R.I. Coleman 2, Ian J. Deary 1, 23andMe Research Paul O’Reilly, Cathryn Lewis Team, Major Depressive Disorder Working Group, Daniel J. Smith 3, Patrick F. Sullivan 4, Naomi R. Wray 5, King’s College London Gerome Breen 2, Cathryn M. Lewis 2, Andrew M. McIntosh 1 Background: Cannabis is the most widely used drug world- 1 University of Edinburgh wide. With many countries engaged in debates about the 2 King’s College London legalisation of cannabis, it is important to fully understand 3 University of Glasgow any potential relationships between drug use and mental 4 University of North Carolina at Chapel Hill health outcomes. Psychosis is often the focus of work in 5 University Of Queensland this field, but cannabis use has also been linked with both depression and self-harm behaviours (Hodgson et al 2017, Background: Depression is a heritable and polygenic condi- Agrawal et al 2017, Smolkina et al 2017). Here, we take tion that causes extensive periods of disability and increases advantage of successful genome-wide association studies the risk of suicide. Previous genetic studies have identified for both cannabis use (Stringer et al 2016, Pasman et al a number of common risk variants which have increased in 2018) and depression (Wray et al 2018), to examine the re- number in line with increasing sample sizes. The availability lationships between these prevalent phenotypes with much of summary statistics from these studies represents an op- greater statistical power. Specifically, we determine the portunity to conduct the largest genome-wide meta-analysis phenotypic and genetic relationship of cannabis use with study of depression to date. depression and self-harm, within the population-based UK Methods: We examined the effect of 8,098,588 genetic vari- Biobank. ants on depression by performing a meta-analysis of the Methods: In UK Biobank, the mental health questionnaire summary statistics from the Hyde et al. (2016) analysis includes items assessing lifetime history of cannabis use, of 23andMe, the Wray et al. (2018) analysis of the Major depression and self-harm. Focusing on unrelated individu- Depressive Disorder Working Group of the Psychiatric Ge- als of European ancestry with high quality genotypic data nomics Consortium data, and the Howard et al. (2018) anal- available (n = 126,291), n = 28,282 report a life-time history ysis of UK Biobank. We used the broad depression phenotype of cannabis use, n = 30,075 report depression and n = 5,520 from UK Biobank which shares a high genetic correlation report self-harm. ARTICLE IN PRESS JID: NEUPSY [m6+; October 3, 2018;8:33 ] Abstracts 3 We examined the phenotypic relationships between these Background: Large, rare copy number variants (CNVs) are traits. Then, using LD score regression and polygenic risk associated with neurodevelopmental disorders but it is un- scoring with recently available summary statistics (Wray et clear whether such CNVs also contribute to the risk of de- al 2018, Stringer et al 2016), we tested the genetic relation- pression. A substantial proportion of the CNV enrichment ship between phenotypes. Finally using Mendelian Randomi- in schizophrenia is explained by CNVs associated with neu- sation, we test evidence for the causal direction of effects. rodevelopmental disorders. Depression shares genetic risk Results: Within UK Biobank, cannabis use is associated with schizophrenia and frequently occurs comorbid with with an increased likelihood of depression (OR = 1.64 95% neurodevelopmental disorders.
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