Identifying the potential role of insomnia on multimorbidity: A Mendelian randomization phenome-wide association study in UK Biobank

Objectives: To identify the breadth of potential causal effects of insomnia on health outcomes and hence its possible role in multimorbidity. Design: Mendelian randomisation (MR) Phenome-wide association study (MR-PheWAS) with two-sample Mendelian randomisation follow-up. Setting: Individual data from UK Biobank and summary data from a number of genome-wide association studies. Participants: 336,975 unrelated white-British UK Biobank participants. Exposures: Standardised genetic risk of insomnia for the MR-PheWAS and genetically predicted insomnia for the two-sample MR follow-up, with insomnia instrumented by a genetic risk score (GRS) created from 129 single-nucleotide polymorphisms (SNPs). Main outcomes measures: 11,409 outcomes from UK Biobank extracted and processed by an automated pipeline (PHESANT). Potential causal effects (i.e., those passing a Bonferroni-corrected significance threshold) were followed up with two-sample MR in MR-Base, where possible. Results: 437 potential causal effects of insomnia were observed for a number of traits, including anxiety, stress, depression, mania, addiction, pain, body composition, immune, respiratory, endocrine, dental, musculoskeletal, cardiovascular and reproductive traits, as well as socioeconomic and behavioural traits. We were able to undertake two-sample MR for 71 of these 437 and found evidence of causal effects (with directionally concordant effect estimates across all analyses) for 25 of these. These included, for example, risk of anxiety disorders (OR=1.55 [95% confidence interval (CI): 1.30, 1.86] per category increase in insomnia), diseases of the oesophagus/stomach/duodenum (OR=1.32 [95% CI: 1.14, 1.53]) and spondylosis (OR=1.57 [95% CI: 1.22, 2.01]). Conclusion: Insomnia potentially causes a wide range of adverse health outcomes and behaviours. This has implications for developing interventions to prevent and treat a number of diseases in order to reduce multimorbidity and associated polypharmacy.

Polynomial Mendelian Radomization reveals widespread non-linear causal effects in the UK Biobank

Causal inference is a critical step in improving our understanding of biological processes and Mendelian randomisation (MR) has emerged as one of the foremost methods to efficiently interrogate diverse hypotheses using large-scale, observational data from biobanks. Although many extensions have been developed to address the three core assumptions of MR-based causal inference (relevance, exclusion restriction, and exchangeability), most approaches implicitly assume that any putative causal effect is linear. Here we propose PolyMR, an MR-based method which provides a polynomial approximation of an (arbitrary) causal function between an exposure and an outcome. We show that this method provides accurate inference of the shape and magnitude of causal functions with greater accuracy than existing methods. We applied this method to data from the UK Biobank, testing for effects between anthropometric traits and continuous health-related phenotypes and found most of these (84%) to have causal effects which deviate significantly from linear. These deviations ranged from slight attenuation at the extremes of the exposure distribution, to large changes in the magnitude of the effect across the range of the exposure (e.g. a 1 kg/m2 change in BMI having stronger effects on glucose levels if the initial BMI was higher), to non-monotonic causal relationships (e.g. the effects of BMI on cholesterol forming an inverted U shape). Finally, we show that the linearity assumption of the causal effect may lead to the misinterpretation of health risks at the individual level or heterogeneous effect estimates when using cohorts with differing average exposure levels.

Is there a causal relationship between executive function and liability to mental health and substance use? A Mendelian randomisation approach

Background: Executive function consists of several cognitive control processes that are able to regulate lower level processes. Poorer performance in tasks designed to test executive function is associated with a range of psychopathologies such as schizophrenia, major depressive disorder (MDD) and anxiety, as well as with smoking and alcohol consumption. Despite these well-documented associations, whether they reflect causal relationships, and if so in what direction, remains unclear. We aimed to establish whether there is a causal relationship between a latent factor for performance on multiple executive function tasks - which we refer to as common executive function (cEF) - and liability to schizophrenia, MDD, anxiety, smoking initiation, alcohol consumption, alcohol dependence and cannabis use disorder (CUD), and the directionality of any relationship observed. Methods: We used a two-sample bidirectional Mendelian randomisation (MR) approach using genome-wide association study (GWAS) summary data from large cohorts (N=17,310 to 848,460) to examine whether causal relationships exist, and if so in which direction. Results: We found evidence of a causal effect of increased cEF on reduced schizophrenia liability (IVW: OR=0.10; 95% CI 0.05 to 0.19; p-value=3.43x10-12), reduced MDD liability (IVW: OR=0.52; 95% CI 0.38 to 0.72; p-value=5.23x10-05), decreased drinks per week (IVW: β=-0.06; 95% CI -0.10 to -0.02; p-value=0.003), and reduced CUD liability (IVW: OR=0.27; 95% CI 0.12 to 0.61; p-value=1.58x10-03). We also found evidence of a causal effect of increased schizophrenia liability on decreased cEF (IVW: β=-0.04; 95% CI -0.04 to -0.03; p-value=3.25x10-27), as well as smoking initiation on decreased cEF (IVW: β=-0.06; 95%CI -0.09 to -0.03; p-value=6.11x10-05). Conclusion: Our results indicate a potential bidirectional causal relationship between a latent factor measure of executive function (cEF) and schizophrenia liability, a possible causal effect of increased cEF on reduced MDD liability, CUD liability, and alcohol consumption, and a possible causal effect of smoking initiation on decreased cEF. These results suggest that executive function should be considered as a potential risk factor for some mental health and substance use outcomes, and may also be impacted by mental health (particularly schizophrenia). Further studies are required to improve our understanding of the underlying mechanisms of these effects, but our results suggest that executive function may be a promising intervention target. These results may therefore inform the prioritisation of experimental medicine studies (e.g., of executive function interventions), for both mental health and substance use outcomes, to improve the likelihood of successful translation.

Circulating inflammatory cytokines and risk of five cancers: a Mendelian randomization analysis

Background Epidemiological and experimental evidence has linked chronic inflammation to cancer aetiology. It is unclear whether associations for specific inflammatory biomarkers are causal or due to bias. In order to examine whether altered genetically predicted concentration of circulating cytokines are associated with cancer development, we performed a two-sample Mendelian randomisation (MR) analysis. Methods Up to 31,112 individuals of European descent were included in genome-wide association study (GWAS) meta-analyses of 47 circulating cytokines. Single nucleotide polymorphisms (SNPs) robustly associated with the cytokines, located in or close to their coding gene (cis), were used as instrumental variables. Inverse-variance weighted MR was used as the primary analysis, and the MR assumptions were evaluated in sensitivity and colocalization analyses and a false discovery rate (FDR) correction for multiple comparisons was applied. Corresponding germline GWAS summary data for five cancer outcomes (breast, endometrial, lung, ovarian, and prostate), and their subtypes were selected from the largest cancer-specific GWASs available (cases ranging from 12,906 for endometrial to 133,384 for breast cancer). Results There was evidence of inverse associations of macrophage migration inhibitory factor with breast cancer (OR per SD = 0.88, 95% CI 0.83 to 0.94), interleukin-1 receptor antagonist with endometrial cancer (0.86, 0.80 to 0.93), interleukin-18 with lung cancer (0.87, 0.81 to 0.93), and beta-chemokine-RANTES with ovarian cancer (0.70, 0.57 to 0.85) and positive associations of monokine induced by gamma interferon with endometrial cancer (3.73, 1.86 to 7.47) and cutaneous T-cell attracting chemokine with lung cancer (1.51, 1.22 to 1.87). These associations were similar in sensitivity analyses and supported in colocalization analyses. Conclusions Our study adds to current knowledge on the role of specific inflammatory biomarker pathways in cancer aetiology. Further validation is needed to assess the potential of these cytokines as pharmacological or lifestyle targets for cancer prevention.

Thirteen Independent Genetic Loci Associated with Preserved Processing Speed in a Study of Cognitive Resilience in 330,097 Individuals in the UK Biobank

Cognitive resilience is the ability to withstand the negative effects of stress on cognitive functioning and is important for maintaining quality of life while aging. The UK Biobank does not have measurements of the same cognitive phenotype at distal time points. Therefore, we used education years (EY) as a proxy phenotype for past cognitive performance and current cognitive performance was based on processing speed. This represented an average time span of 40 years between past and current cognitive performance in 330,097 individuals. A confounding factor was that EY is highly polygenic and masked the genetics of resilience. To overcome this, we employed Genomics Structural Equation Modelling (GenomicSEM) to perform a genome-wide association study (GWAS)-by-subtraction using two GWAS, one GWAS of EY and resilience and a second GWAS of EY but not resilience, to generate a GWAS of Resilience. Using independent discovery and replication samples, we found 13 independent genetic loci for Resilience. Functional analyses showed enrichment in several brain regions and specific cell types. Gene-set analyses implicated the biological process “neuron differentiation”, the cellular component “synaptic part” and the “WNT signalosome”. Mendelian randomisation analysis showed a causative effect of white matter volume on cognitive resilience. These results may contribute to the neurobiological understanding of resilience.

Morning Cortisol and Circulating Inflammatory Cytokine Levels: A Mendelian Randomisation Study

Cortisol exerts a broad anti-inflammatory effect on the immune system. Inflammatory cytokines contribute to the molecular signalling pathways implicated in various autoimmune and inflammatory conditions. However, the mechanisms by which cortisol modulates such signalling pathways remain uncertain. Leveraging summary-level data from the CORtisol NETwork (CORNET, n = 25,314) and FINRISK (n = 8293) genome-wide association studies, we used two-sample Mendelian randomisation to investigate the causal effect of genetically proxied increased morning cortisol levels on 42 circulating cytokines. We found that increased genetically proxied morning cortisol levels were associated with reduced levels of IL-8 and increased levels of MIF. These results provide mechanistic insight into the immunomodulatory effects of endogenous cortisol and the therapeutic effects of exogenous corticosteroids. Clinically, our findings underline the therapeutic importance of steroids in inflammatory conditions where IL-8 and MIF play a central pathophysiological role in the onset and progression of disease.

Estimation of causal effects of a time-varying exposure at multiple time points through Multivariable Mendelian randomization

Mendelian Randomisation (MR) is a powerful tool in epidemiology to estimate the causal effect of an exposure on an outcome in the presence of unobserved confounding, by utilising genetic variants as instrumental variables (IVs) for the exposure. The effects obtained from MR studies are often interpreted as the lifetime effect of the exposure in question. However, the causal effects of many exposures are thought to vary throughout an individual's lifetime and there may be periods during which an exposure has more of an effect on a particular outcome. Multivariable MR (MVMR) is an extension of MR that allows for multiple, potentially highly related, exposures to be included in an MR estimation. MVMR estimates the direct effect of each exposure on the outcome conditional on all of the other exposures included in the estimation. We explore the use of MVMR to estimate the direct effect of a single exposure at different time points in an individual's lifetime on an outcome. We use simulations to illustrate the interpretation of the results from such analyses and the key assumptions required. We show that causal effects at different time periods can be estimated through MVMR when the association between the genetic variants used as instruments and the exposure measured at those time periods varies, however this estimation will not necessarily identify exact time periods over which an exposure has the most effect on the outcome. We illustrate the method through estimation of the causal effects of childhood and adult BMI on smoking behaviour.

Sleep Disordered Breathing, Obesity and Atrial Fibrillation: A Mendelian Randomisation Study

It remains unclear whether the association between obstructive sleep apnoea (OSA), a form of sleep-disordered breathing (SDB), and atrial fibrillation (AF) is causal or mediated by shared co-morbidities such as obesity. Existing observational studies are conflicting and limited by confounding and reverse causality. We performed Mendelian randomisation (MR) to investigate the causal relationships between SDB, body mass index (BMI) and AF. Single-nucleotide polymorphisms associated with SDB (n = 29) and BMI (n = 453) were selected as instrumental variables to investigate the effects of SDB and BMI on AF, using genetic association data on 55,114 AF cases and 482,295 controls. Primary analysis was conducted using inverse-variance weighted MR. Higher genetically predicted SDB and BMI were associated with increased risk of AF (OR per log OR increase in snoring liability 2.09 (95% CI 1.10–3.98), p = 0.03; OR per 1-SD increase in BMI 1.33 (95% CI 1.24–1.42), p < 0.001). The association between SDB and AF was not observed in sensitivity analyses, whilst associations between BMI and AF remained consistent. Similarly, in multivariable MR, SDB was not associated with AF after adjusting for BMI (OR 0.68 (95% CI 0.42–1.10), p = 0.12). Higher BMI remained associated with increased risk of AF after adjusting for OSA (OR 1.40 (95% CI 1.30–1.51), p < 0.001). Elevated BMI appears causal for AF, independent of SDB. Our data suggest that the association between SDB, in general, and AF is attributable to mediation or confounding from obesity, though we cannot exclude that more severe SDB phenotypes (i.e., OSA) are causal for AF.

Plasma adiponectin and risk of asthma: observational analysis, genetic Mendelian randomisation and meta-analysis

BackgroundAdiponectin, an adipocyte-secreted protein-hormone with inflammatory properties, has a potentially important role in the development and progression of asthma. Unravelling whether adiponectin is a causal risk factor for asthma is an important issue to clarify as adiponectin could be a potential novel drug target for the treatment of asthma.ObjectiveWe tested the hypothesis that plasma adiponectin is associated observationally and causally (using genetic variants as instrumental variables) with risk of asthma.MethodsIn the Copenhagen General Population Study, we did an observational analysis in 28 845 individuals (2278 asthma cases) with plasma adiponectin measurements, and a genetic one-sample Mendelian randomisation analysis in 94 868 individuals (7128 asthma cases) with 4 genetic variants. Furthermore, in the UK Biobank, we did a genetic two-sample Mendelian randomisation analysis in 462 933 individuals (53 598 asthma cases) with 12 genetic variants. Lastly, we meta-analysed the genetic findings.ResultsWhile a 1 unit log-transformed higher plasma adiponectin in the Copenhagen General Population Study was associated with an observational OR of 1.65 (95% CI 1.29 to 2.08) for asthma, the corresponding genetic causal OR was 1.03 (95% CI 0.75 to 1.42). The genetic causal OR for asthma in the UK Biobank was 1.00 (95% CI 0.99 to 1.00). Lastly, genetic meta-analysis confirmed lack of association between genetically high plasma adiponectin and causal OR for asthma.ConclusionObservationally, high plasma adiponectin is associated with increased risk of asthma; however, genetic evidence could not support a causal association between plasma adiponectin and asthma.

The absence of association between anorexia nervosa and smoking: converging evidence across two studies

Previous studies have found increased smoking prevalence amongst adults with anorexia nervosa (AN) compared to the general population. The current investigation explored bidirectional associations between AN and smoking behaviour (initiation and heaviness), to address questions surrounding causation. In Study One, logistic regression models with variance robust standard errors assessed longitudinal associations between AN and smoking, using data from adolescent participants of the Avon Longitudinal Study of Parents and Children (N = 5100). In Study Two, two-sample Mendelian randomisation (MR) tested possible causal effects using summary statistics from publicly available genome-wide association studies (GWAS). Study One provided no clear evidence for a predictive effect of AN on subsequent smoking behaviour, or for smoking heaviness/initiation predicting later AN. MR findings did not support causal effects between AN and smoking behaviour, in either direction. Findings do not support predictive or causal effects between AN and smoking behaviour. Previously reported associations may have been vulnerable to confounding, highlighting the possibility of smoking and AN sharing causal risk factors.