Biology subjects

Zammit, S.

Publications and source records attributed to Zammit, S..

5 recordsLinked to original sources

bioRxiv2019

Genetic association study of psychotic experiences in UK Biobank

Psychotic experiences, such as hallucinations and delusions, are reported by approximately 5%-10% of the general population, though only a small proportion of individuals develop psychotic disorders such as schizophrenia or bipolar disorder. Studying the genetic aetiology of psychotic experiences in the general population, and its relationship with the genetic aetiology of other disorders, may increase our understanding of their pathological significance. Using the population-based UK Biobank sample, we performed the largest genetic association study of psychotic experiences in individuals without a psychotic disorder. We conducted three genome-wide association studies (GWAS) for (i) any psychotic experience (6123 cases vs. 121,843 controls), (ii) distressing psychotic experiences (2143 cases vs. 121,843 controls), and (iii) multiple occurrence psychotic experiences (3337 cases vs. 121,843 controls). Analyses of polygenic risk scores (PRS), genetic correlation, and copy number variation (CNV) were conducted to assess whether genetic liability to psychotic experiences is shared with schizophrenia and/or other neuropsychiatric disorders and traits. GWAS analyses identified four loci associated with psychotic experiences including a locus in Ankyrin-3 (ANK3, OR=1.16, p=3.06 x 10-8) with any psychotic experience and a locus in cannabinoid receptor 2 gene (CNR2, OR=0.66, p=3.78x10-8) with distressing psychotic experiences. PRS analyses identified associations between psychotic experiences and genetic liability for schizophrenia, major depressive disorder, and bipolar disorder, and these associations were stronger for distressing psychotic experiences. Genetic correlation analysis identified significant genetic correlations between psychotic experiences and major depressive disorder, schizophrenia, autism spectrum disorder and a cross-disorder GWAS. Individuals reporting psychotic experiences had an increased burden of CNVs previously associated with schizophrenia (OR=2.04, p=2.49x10-4) and of those associated with neurodevelopmental disorders more widely (OR=1.75, p=1.41x10-3). In conclusion, we identified four genome-wide significant loci in the largest GWAS of psychotic experiences from the population-based UK Biobank sample and found support for a shared genetic aetiology between psychotic experiences and schizophrenia, but also major depressive disorder, bipolar disorder and neurodevelopmental disorders.

genetics↗

bioRxiv2019

Smoking and the risk for bipolar disorder: causal evidence from a bidirectional Mendelian randomization study

ImportanceThere is increasing evidence that smoking is a risk factor for severe mental illness, including bipolar disorder. Conversely, patients with bipolar disorder might smoke more (often) as a result of the psychiatric disorder. Research that investigates causality and the direction of the relationship between smoking and bipolar disorder has been lacking.\n\nObjectiveTo investigate the direction and causal nature of the relationship between smoking and bipolar disorder we conducted a bidirectional Mendelian randomization (MR) study.\n\nData sourcesPublicly available summary statistics from genome-wide association studies on bipolar disorder, smoking initiation, smoking heaviness, smoking cessation and lifetime smoking (i.e., a compound measure of heaviness, duration and cessation). We applied multiple analytical methods with different, orthogonal assumptions to triangulate results, including inverse-variance weighted (IVW), MR-Egger or Egger SIMEX, weighted median, weighted mode, and Steiger filtered analyses.\n\nResultsAcross different methods of MR, consistent evidence was found for a positive effect of smoking on the odds of bipolar disorder (smoking initiation ORIVW=1.46, 95% CI=1.28-1.66, P=1.44x10-8, lifetime smoking ORIVW=1.72, 95% CI=1.29-2.28, P=1.8x10-4). The MR analyses of the liability of bipolar disorder on smoking provided no clear evidence of a strong causal effect (smoking initiation betaIVW= -0.008, 95% CI= -0.026-0.009, P=0.35; P=0.94; smoking heaviness betaIVW=0.028, 95% CI= 0.003-0.053, P=2.9x10-2; smoking cessation ORIVW= 0.997, 95% CI= 0.981-1.014, P=0.74; lifetime smoking betaIVW= -0.001, 95%CI=-0.022-0.020, P=0.95).\n\nConclusionsThese findings suggest that smoking initiation and lifetime smoking are likely to be a causal risk factor for developing bipolar disorder. We found some evidence that liability to smoking increased smoking heaviness. Given that smoking is a modifiable risk factor, these findings further support investment into smoking prevention and treatment in order to reduce mental health problems in future generations.

neuroscience↗

bioRxiv2018

Causal effects of lifetime smoking on risk for depression and schizophrenia: Evidence from a Mendelian randomisation study

BackgroundSmoking prevalence is higher amongst individuals with schizophrenia and depression compared to the general population. Mendelian randomisation (MR) can examine whether this association is causal using genetic variants identified in genome-wide association studies (GWAS).\n\nMethodsWe conducted a GWAS of lifetime smoking behaviour (capturing smoking duration, heaviness and cessation) in a sample of 462,690 individuals from the UK Biobank, and validated the findings via two-sample MR analyses of positive control outcomes (e.g., lung cancer). Having established the validity of our instrument, we used bi-directional two-sample Mendelian randomisation to explore its effects on schizophrenia and depression.\n\nOutcomesThere was strong evidence to suggest smoking is a causal risk factor for both schizophrenia (OR = 2.27, 95% CI = 1.67 - 3.08, P < 0.001) and depression (OR = 1.99, 95% CI = 1.71 - 2.32, P < 0.001). We also found some evidence that genetic risk for both schizophrenia and depression cause increased lifetime smoking ({beta} = 0.022, 95% CI = 0.005 - 0.038, P = 0.009; {beta}= 0.091, 95% CI = 0.027 - 0.155, P = 0.005).\n\nInterpretationThese findings suggest that the association between smoking, schizophrenia and depression is due, at least in part, to a causal effect of smoking, providing further evidence for the detrimental consequences of smoking for mental health.\n\nFundingThis work was supported by the Medical Research Council Integrative Epidemiology Unit, the NIHR Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and the University of Bristol.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSThe association between smoking and mental health (especially schizophrenia and depression) is often assumed to be the result of self-medication (for example, to alleviate symptoms). However, more recent evidence has suggested that smoking might also be a risk factor for schizophrenia and depression. This alternative direction of effect is supported by meta-analyses and previous prospective observational evidence using related individuals to control for genetic and environmental confounding. However, observational evidence cannot completely account for confounding or the possibility of reverse causation. One way to get around these problems is Mendelian randomisation (MR). Previous MR studies of smoking and mental health have not shown an effect of smoking on depression and are inconclusive for the effects of smoking on schizophrenia. However, these studies have only looked at individual aspects of smoking behaviour and some studies required stratifying participants into smokers and non-smokers, reducing power.\n\nAdded value of this studyWe have developed a novel genetic instrument for lifetime smoking exposure which can be used within a two-sample MR framework, using publicly-available GWAS summary statistics. We were therefore able to test the bi-directional association between smoking with schizophrenia and depression to see if the effects are causal. We found strong evidence to suggest that smoking is a causal risk factor for both schizophrenia and depression. There was some evidence to suggest that risk of schizophrenia and depression increases lifetime smoking (consistent with the self-medication hypothesis) but the effects were stronger for depression than schizophrenia.\n\nImplications of all the available evidenceThis study was the first to demonstrate evidence for an effect of lifetime smoking exposure on risk of schizophrenia and depression within a causal inference framework. This emphasises the detrimental public health consequences of smoking, not just for physical health, but also to mental illness.

epidemiology↗

bioRxiv2018

The role of rare copy number variants in depression

The role of large, rare copy number variants (CNVs) in neurodevelopmental disorders is well-established,1-5 but their contribution to common psychiatric disorders, such as depression, remains unclear. We have previously shown that a substantial proportion of CNV enrichment in schizophrenia is explained by CNVs associated with neurodevelopmental disorders.6, 7 Depression shares genetic risk with schizophrenia8, 9 and is frequently comorbid with neurodevelopmental disorders10, 11, suggesting to us the hypothesis that if CNVs play a role in depression, neurodevelopmental CNVs are those most likely to be associated. We confirmed this in UK Biobank by showing that neurodevelopmental CNVs were associated with depression (24,575 cases, 5.87%; OR=1.36, 95% CI 1.22-1.51, p=1.61x10-8), whilst finding no evidence implicating other CNVs. Four individual neurodevelopmental CNVs increased risk of depression (1q21.1 duplication, PWS duplication, 16p13.11 deletion, 16p11.2 duplication). The association between neurodevelopmental CNVs and depression was partially explained by social deprivation but not by education attainment or physical illness.

neuroscience↗

bioRxiv2017

The molecular genetics of participation in the Avon Longitudinal Study of Parents and Children

BackgroundIt is often assumed that selection (including participation and dropout) does not represent an important source of bias in genetic studies. However, there is little evidence to date on the effect of genetic factors on participation.\n\nMethodsUsing data on mothers (N=7,486) and children (N=7,508) from the Avon Longitudinal Study of Parents and Children, we 1) examined the association of polygenic risk scores for a range of socio-demographic, lifestyle characteristics and health conditions related to continued participation, 2) investigated whether associations of polygenic scores with body mass index (BMI; derived from self-reported weight and height) and self-reported smoking differed in the largest sample with genetic data and a sub-sample who participated in a recent follow-up and 3) determined the proportion of variation in participation explained by common genetic variants using genome-wide data.\n\nResultsWe found evidence that polygenic scores for higher education, agreeableness and openness were associated with higher participation and polygenic scores for smoking initiation, higher BMI, neuroticism, schizophrenia, ADHD and depression were associated with lower participation. Associations between the polygenic score for education and self-reported smoking differed between the largest sample with genetic data (OR for ever smoking per SD increase in polygenic score:0.85, 95% CI:0.81,0.89) and sub-sample (OR:0.95, 95% CI:0.88,1.02). In genome-wide analysis, single nucleotide polymorphism based heritability explained 17-31% of variability in participation.\n\nConclusionsGenetic association studies, including Mendelian randomization, can be biased by selection, including loss to follow-up. Genetic risk for dropout should be considered in all analyses of studies with selective participation.

genetics↗