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

Genes ◽  
2022 ◽  
Vol 13 (1) ◽  
pp. 116
Author(s):  
Skanda Rajasundaram ◽  
Rezbieara P. Rahman ◽  
Benjamin Woolf ◽  
Sizheng Steven Zhao ◽  
Dipender Gill
Keyword(s):  
Causal Effect ◽  
Association Studies ◽  
Signalling Pathways ◽  
Mendelian Randomisation ◽  
Therapeutic Effects ◽  
Genome Wide Association Studies ◽  
Inflammatory Conditions ◽  
Morning Cortisol ◽  
Progression Of Disease ◽  
Cortisol Levels

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.

scholarly journals Pulmonary function and risk of Alzheimer dementia: two-sample Mendelian randomization study

2020 ◽  
Author(s):  
Tom C. Russ ◽  
Sarah E. Harris ◽  
G. David Batty
Keyword(s):  
Pulmonary Function ◽  
Causal Effect ◽  
Association Studies ◽  
Forced Expiratory Volume ◽  
Health Concern ◽  
Mendelian Randomisation ◽  
Genome Wide Association Studies ◽  
Global Public Health ◽  
Alzheimer Dementia ◽  
Dementia Risk

ABSTRACTDementia is a major global public health concern and in addition to recognised risk factors there is emerging evidence that poorer pulmonary function is linked with subsequent dementia risk. However, it is unclear if this observed association is causal or whether it might result from confounding. Therefore, we present the first two-sample Mendelian randomisation study of the association between pulmonary function and Alzheimer dementia using the most recent genome-wide association studies to produce instrumental variables for both. We found no evidence of a causal effect of reduced Forced Expiratory Volume in 1 second (FEV1) or Forced Vital Capacity (FVC) on Alzheimer dementia risk (both P>0.35). However, the FEV1/FVC ratio was associated with Alzheimer dementia risk with, in fact, superior function predicting an increased dementia risk (OR 1.12, 95%CI 1.02-1.23; P=0.016) which may result from survivor bias. While we can conclude that there is no causal link between impaired pulmonary function and Alzheimer dementia, our study sheds less light on potential links with other types of dementia.

scholarly journals Evidence for causal effects of lifetime smoking on risk for depression and schizophrenia: a Mendelian randomisation study

2019 ◽  
Vol 50 (14) ◽  
pp. 2435-2443 ◽  
Author(s):  
Robyn E. Wootton ◽  
Rebecca C. Richmond ◽  
Bobby G. Stuijfzand ◽  
Rebecca B. Lawn ◽  
Hannah M. Sallis ◽  
...  
Keyword(s):  
Causal Effect ◽  
Association Studies ◽  
Smoking Initiation ◽  
Smoking Behaviour ◽  
Positive Control ◽  
Mendelian Randomisation ◽  
Genome Wide Association Studies ◽  
Weak Evidence ◽  
Smoking Duration ◽  
The Uk

AbstractBackgroundSmoking prevalence is higher amongst individuals with schizophrenia and depression compared with the general population. Mendelian randomisation (MR) can examine whether this association is causal using genetic variants identified in genome-wide association studies (GWAS).MethodsWe conducted two-sample MR to explore the bi-directional effects of smoking on schizophrenia and depression. For smoking behaviour, we used (1) smoking initiation GWAS from the GSCAN consortium and (2) we conducted our own GWAS of lifetime smoking behaviour (which captures smoking duration, heaviness and cessation) in a sample of 462690 individuals from the UK Biobank. We validated this instrument using positive control outcomes (e.g. lung cancer). For schizophrenia and depression we used GWAS from the PGC consortium.ResultsThere was strong evidence to suggest smoking is a risk factor for both schizophrenia (odds ratio (OR) 2.27, 95% confidence interval (CI) 1.67–3.08, p < 0.001) and depression (OR 1.99, 95% CI 1.71–2.32, p < 0.001). Results were consistent across both lifetime smoking and smoking initiation. We found some evidence that genetic liability to depression increases smoking (β = 0.091, 95% CI 0.027–0.155, p = 0.005) but evidence was mixed for schizophrenia (β = 0.022, 95% CI 0.005–0.038, p = 0.009) with very weak evidence for an effect on smoking initiation.ConclusionsThese 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 on mental health.

scholarly journals Investigating the potential effect of antihypertensive medication on psychiatric disorders: a mendelian randomisation study

2020 ◽  
Author(s):  
Solal Chauquet ◽  
Michael O’Donovan ◽  
James Walters ◽  
Naomi Wray ◽  
Sonia Shah
Keyword(s):  
Psychiatric Disorders ◽  
Drug Target ◽  
Drug Exposure ◽  
Causal Effect ◽  
Association Studies ◽  
Neuropsychiatric Symptoms ◽  
Potential Effect ◽  
Mendelian Randomisation ◽  
Genome Wide Association Studies ◽  
Increased Risk

ABSTRACTBackgroundThere is growing evidence from observational studies that drugs used for the prevention and treatment of CVD may cause, exacerbate, or relieve neuropsychiatric symptoms.AimUse Mendelian randomisation (MR) analysis to investigate the potential effect of different antihypertensive drugs on schizophrenia, bipolar disorder and major depressive disorder.MethodsWe conduct two sample MR using expression quantitative trait loci (eQTLs) for antihypertensive drug target genes as genetic instruments, together with summary data from published genome-wide association studies, to investigate the causal effect of changes in drug target gene expression (as proxies of drug exposure) on psychiatric disorders.ResultsA 1 standard deviation lower expression of the ACE gene in blood was associated with 4.0 mmHg (95% CI = 2.7 – 5.3) lower systolic blood pressure, but increased risk of schizophrenia (OR (95% CI) = 1.75 (1.28 – 2.38)). A concordant direction of effect was observed with ACE expression in brain tissue.ConclusionsFindings suggest an adverse effect of lower ACE expression on schizophrenia risk. This warrants further investigation to determine if lowering ACE activity for treatment of hypertension using ACE inhibitors (particularly centrally-acting drugs) may worsen symptoms in patients with schizophrenia, and whether there is any association between ACE inhibitor use and risk of (mainly late-onset) schizophrenia.

scholarly journals Mendelian randomisation study of smoking exposure in relation to breast cancer risk

2021 ◽  
Author(s):  
Hanla A. Park ◽  
Sonja Neumeyer ◽  
Kyriaki Michailidou ◽  
Manjeet K. Bolla ◽  
Qin Wang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Causal Effect ◽  
Association Studies ◽  
Sensitivity Analyses ◽  
Mendelian Randomisation ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Smoking Exposure

Abstract Background Despite a modest association between tobacco smoking and breast cancer risk reported by recent epidemiological studies, it is still equivocal whether smoking is causally related to breast cancer risk. Methods We applied Mendelian randomisation (MR) to evaluate a potential causal effect of cigarette smoking on breast cancer risk. Both individual-level data as well as summary statistics for 164 single-nucleotide polymorphisms (SNPs) reported in genome-wide association studies of lifetime smoking index (LSI) or cigarette per day (CPD) were used to obtain MR effect estimates. Data from 108,420 invasive breast cancer cases and 87,681 controls were used for the LSI analysis and for the CPD analysis conducted among ever-smokers from 26,147 cancer cases and 26,072 controls. Sensitivity analyses were conducted to address pleiotropy. Results Genetically predicted LSI was associated with increased breast cancer risk (OR 1.18 per SD, 95% CI: 1.07–1.30, P = 0.11 × 10–2), but there was no evidence of association for genetically predicted CPD (OR 1.02, 95% CI: 0.78–1.19, P = 0.85). The sensitivity analyses yielded similar results and showed no strong evidence of pleiotropic effect. Conclusion Our MR study provides supportive evidence for a potential causal association with breast cancer risk for lifetime smoking exposure but not cigarettes per day among smokers.

scholarly journals Genetic correlation and causal relationships between cardio-metabolic traits and Lung function Impairment

2020 ◽  
Author(s):  
Matthias Wielscher ◽  
Andre FS Amaral ◽  
Diana van der Plaat ◽  
Louise V Wain ◽  
Sylvain Sebert ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Lung Function ◽  
Genetic Correlation ◽  
Large Scale ◽  
Causal Effect ◽  
Association Studies ◽  
Metabolic Health ◽  
Mendelian Randomisation ◽  
Genome Wide Association Studies ◽  
Metabolic Traits

Background: Associations of low lung function with features of poor cardio-metabolic health have been reported. It is, however, unclear whether these co-morbidities reflect causal associations, shared genetic heritability or are confounded by environmental factors. Methods We performed three analyses: 1) cardio-metabolic health to lung function association tests in NFBC1966, 2) cross trait LD score regression to compare genetic backgrounds and 3) Mendelian Randomization (MR) analysis to assess the causal effect of cardio-metabolic traits and disease on lung function, and vice versa (bidirectional MR). Genetic associations were obtained from UK Biobank data or published large-scale genome-wide association studies (N > 82,000). Results We observed negative genetic correlation between lung function and cardio-metabolic traits and diseases. In Mendelian Randomisation analysis (MR) we found associations between Type 2 Diabetes instruments and FVC as well as FEV1/FVC. BMI instruments were associated to all lung function traits and CRP instruments to FVC. These genetic association provide evidence for a causal effect of cardio-metabolic traits on lung function. Multivariable MR suggested independence of these causal effects from other tested cardio-metabolic traits and diseases. Analysis of lung function specific SNPs revealed a potential causal effect of FEV1/FVC on blood pressure. Conclusions: The present study overcomes many limitations of observational studies by using Mendelian Randomisation. We provide evidence for an independent causal effect of T2D, CRP and BMI on lung function with some of the T2D effect on lung function being mediated by CRP. Furthermore, this analysis suggests a potential causal effect of FEV1/FVC on blood pressure. Our detailed analysis of the interplay between cardio-metabolic traits and impaired lung function provides the opportunity to improve the quality of existing intervention strategies.

scholarly journals The role of obesity in female reproductive conditions: A Mendelian Randomisation Study

2021 ◽  
Author(s):  
Samvida S. Venkatesh ◽  
Teresa Ferreira ◽  
Stefania Benonisdottir ◽  
Nilufer Rahmioglu ◽  
Christian M. Becker ◽  
...  
Keyword(s):  
Causal Effect ◽  
Association Studies ◽  
Overweight And Obesity ◽  
Additive Models ◽  
Mendelian Randomisation ◽  
Genome Wide Association Studies ◽  
Reproductive Disorders ◽  
Metabolic Hormones ◽  
Genetic Components ◽  
Increased Risk

Background: Obesity is observationally associated with altered risk of many female reproductive conditions. These include polycystic ovary syndrome (PCOS), abnormal uterine bleeding, endometriosis, infertility, and pregnancy-related disorders. However, the roles and mechanisms of obesity in the aetiology of reproductive disorders remain unclear. Methods and Findings: We estimated observational and genetically predicted causal associations between obesity, metabolic hormones, and female reproductive conditions using logistic regression, generalised additive models, and Mendelian randomisation (two-sample, non-linear, and multivariable) applied to data from UK Biobank and publicly available genome-wide association studies (GWAS). Body mass index (BMI), waist-hip ratio (WHR), and WHR adjusted for BMI (WHRadjBMI) were observationally (odds ratios (ORs) = 1.02 - 1.87 per 1 S.D. obesity trait) and causally (ORs = 1.06 - 2.09) associated with uterine fibroids (UF), PCOS, heavy menstrual bleeding (HMB), and pre-eclampsia. Causal effect estimates of WHR and WHRadjBMI, but not BMI, were attenuated compared to their observational counterparts. Genetically predicted visceral adipose tissue mass was causal for the development of HMB, PCOS, and pre-eclampsia (ORs = 1.01 - 3.38). Increased waist circumference also posed a higher causal risk (ORs = 1.16 - 1.93) for the development of these disorders and UF than did increased hip circumference (ORs = 1.06 - 1.10). Leptin, fasting insulin, and insulin resistance each mediated between 20% - 50% of the total causal effect of obesity on pre-eclampsia. Reproductive conditions clustered based on shared genetic components of their aetiological relationships with obesity. Conclusions: In this first systematic, large-scale, genetics-based analysis of the aetiological relationships between obesity and female reproductive conditions, we found that common indices of overall and central obesity increased risk of reproductive disorders to heterogenous extents, mediated by metabolic hormones. Our results suggest exploring the mechanisms mediating the causal effects of overweight and obesity on gynaecological health to identify targets for disease prevention and treatment.

scholarly journals Shared genetic etiology between idiopathic pulmonary fibrosis and COVID-19 severity

2020 ◽  
Author(s):  
Joao Fadista ◽  
Luke M. Kraven ◽  
Juha Karjalainen ◽  
Shea J. Andrews ◽  
Frank Geller ◽  
...  
Keyword(s):  
Risk Factors ◽  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Genetic Correlation ◽  
Risk Allele ◽  
Causal Effect ◽  
Association Studies ◽  
Mendelian Randomisation ◽  
Genome Wide Association Studies ◽  
Increased Risk

Background. Idiopathic pulmonary fibrosis (IPF) is a complex lung disease, characterized by progressive lung scarring. Severe COVID-19 is associated with substantial pneumonitis and has a number of shared major risk factors with IPF. This study aimed to determine the genetic correlation between IPF and severe COVID-19 and assess a potential causal role of genetically increased risk of IPF on COVID-19 severity. Methods. We performed a Mendelian randomisation (MR) study for IPF causality in COVID-19. Genetic variants associated with IPF susceptibility (P<5x10-8) in previous genome-wide association studies (GWAS) were used as instrumental variables (IVs). Effect estimates of those IVs on COVID-19 severity were gathered from the GWAS meta-analysis by the COVID-19 Host Genetics Initiative. The genetic correlation between IPF and COVID-19 severity was estimated with linkage disequilibrium (LD) score regression. Findings. We detected a positive genetic correlation of IPF with COVID-19 severity (rg=0.31 [95% CI 0.04-0.57], P = 0.023). The MR estimates for severe COVID-19 did not reveal any genetic association (OR 1.05, [95% CI 0.92-1.20], P = 0.43). However, outlier analysis revealed that the IPF risk allele rs35705950 at MUC5B had a different effect compared with the other variants. When rs35705950 was excluded, MR results provided evidence that genetically increased risk of IPF has a causal effect on COVID-19 severity (OR 1.21, [95% CI 1.06-1.38], P = 4.24x10-3). Furthermore, the IPF risk-allele at MUC5B showed an apparent protective effect against COVID-19 hospitalization only in older adults (OR 0.86, [95% CI 0.73-1.00], P = 2.99x10-2) . Interpretation. The strongest genetic determinant of IPF, rs35705950 at MUC5B, seems to confer protection against COVID-19, whereas the combined effect of all other IPF risk loci seem to confer risk of COVID-19 severity. The observed effect of rs35705950 could either be due to protective effects of mucin over-production on the airways or a consequence of selection bias due to a patient group that is heavily enriched for the rs35705950 T undertaking strict self-isolation. Due to the diverse impact of IPF causal variants on SARS-CoV-2 infection, further investigation is needed to address this apparent paradox between variance at MUC5B and other IPF genetic risk factors.

scholarly journals Robust inference in summary data Mendelian randomisation via the zero modal pleiotropy assumption

2017 ◽  
Author(s):  
Fernando Pires Hartwig ◽  
George Davey Smith ◽  
Jack Bowden
Keyword(s):  
Instrumental Variable ◽  
Causal Effect ◽  
Association Studies ◽  
Mendelian Randomisation ◽  
Effect Estimate ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Weighted Median ◽  
Summary Data ◽  
Genetic Instruments

AbstractBackgroundMendelian randomisation (MR) is being increasingly used to strengthen causal inference in observational studies. Availability of summary data of genetic associations for a variety of phenotypes from large genome-wide association studies (GWAS) allows straightforward application of MR using summary data methods, typically in a two-sample design. In addition to the conventional inverse variance weighting (IVW) method, recently developed summary data MR methods, such as the MR-Egger and weighted median approaches, allow a relaxation of the instrumental variable assumptions.MethodsHere, a new method –the mode-based estimate (MBE) – is proposed to obtain a single causal effect estimate from multiple genetic instruments. The MBE is consistent when the largest number of similar (identical in infinite samples) individual-instrument causal effect estimates comes from valid instruments, even if the majority of instruments are invalid. We evaluate the performance of the method in simulations designed to mimic the two-sample summary data setting, and demonstrate its use by investigating the causal effect of plasma lipid fractions and urate levels on coronary heart disease risk.ResultsThe MBE presented less bias and type-I error rates than other methods under the null in many situations. Its power to detect a causal effect was smaller compared to the IVW and weighted median methods, but was larger than that of MR-Egger regression, with sample size requirements typically smaller than those available from GWAS consortia.ConclusionsThe MBE relaxes the instrumental variable assumptions, and should be used in combination with other approaches in a sensitivity analysis.Key MessagesSummary data Mendelian randomisation, typically in a two-sample setting, is being increasingly used due to the availability of summary association results from large genome- wide association studies.Mendelian randomisation analyses using multiple genetic instruments are prone to bias due to horizontal pleiotropy, especially when genetic instruments are selected based solely on statistical criteria.A causal effect estimate robust to horizontal pleiotropy can be obtained using the mode- based estimate (MBE).The MBE requires that the most common causal effect estimate is a consistent estimate of the true causal effect, even if the majority of instruments are invalid (i.e., the ZEro Modal Pleiotropy Assumption, or ZEMPA).Plotting the smoothed empirical density function is useful to explore the distribution of causal effect estimates, and to understand how the MBE is determined.

scholarly journals Smoking and the risk for bipolar disorder: evidence from a bidirectional Mendelian randomisation study

2019 ◽  
pp. 1-7 ◽  
Author(s):  
Jentien M. Vermeulen ◽  
Robyn E. Wootton ◽  
Jorien L. Treur ◽  
Hannah M. Sallis ◽  
Hannah J. Jones ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Risk Factor ◽  
Mental Health Problems ◽  
Causal Effect ◽  
Association Studies ◽  
Smoking Initiation ◽  
Smoking Prevention ◽  
Mendelian Randomisation ◽  
Genome Wide Association Studies ◽  
The Past

BackgroundThere 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.AimsWe conducted a bidirectional Mendelian randomisation (MR) study to investigate the direction and evidence for a causal nature of the relationship between smoking and bipolar disorder.MethodWe used publicly 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 analytical methods with different, orthogonal assumptions to triangulate results, including inverse-variance weighted (IVW), MR-Egger, MR-Egger SIMEX, weighted-median, weighted-mode and Steiger-filtered analyses.ResultsAcross 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 = 1.44 × 10−8, lifetime smoking ORIVW = 1.72, 95% CI 1.29–2.28, P = 1.8 × 10−4). The MR analyses of the effect of liability to bipolar disorder on smoking provided no clear evidence of a strong causal effect (smoking heaviness betaIVW = 0.028, 95% CI 0.003–0.053, P = 2.9 × 10−2).ConclusionsThese 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 bipolar disorder 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.Declaration of interestW.v.d.B received fees in the past 3 years from Indivior, C&amp;A Pharma, Opiant and Angelini. G.M.G. is a National Institute for Health Research (NIHR) Emeritus Senior Investigator, holds shares in P1vital and has served as consultant, advisor or CME speaker in the past 3 years for Allergan, Angelini, Compass Pathways, MSD, Lundbeck (/Otsuka and /Takeda), Medscape, Minervra, P1Vital, Pfizer, Sage, Servier, Shire and Sun Pharma.

scholarly journals Genetic correlation and causal relationships between cardio-metabolic traits and lung function impairment

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Matthias Wielscher ◽  
Andre F. S. Amaral ◽  
Diana van der Plaat ◽  
Louise V. Wain ◽  
Sylvain Sebert ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Lung Function ◽  
Genetic Correlation ◽  
Causal Effect ◽  
Association Studies ◽  
Metabolic Health ◽  
Mendelian Randomisation ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Metabolic Traits

Abstract Background Associations of low lung function with features of poor cardio-metabolic health have been reported. It is, however, unclear whether these co-morbidities reflect causal associations, shared genetic heritability or are confounded by environmental factors. Methods We performed three analyses: (1) cardio-metabolic health to lung function association tests in Northern Finland Birth cohort 1966, (2) cross-trait linkage disequilibrium score regression (LDSC) to compare genetic backgrounds and (3) Mendelian randomisation (MR) analysis to assess the causal effect of cardio-metabolic traits and disease on lung function, and vice versa (bidirectional MR). Genetic associations were obtained from the UK Biobank data or published large-scale genome-wide association studies (N > 82,000). Results We observed a negative genetic correlation between lung function and cardio-metabolic traits and diseases. In Mendelian Randomisation analysis (MR), we found associations between type 2 diabetes (T2D) instruments and forced vital capacity (FVC) as well as FEV1/FVC. Body mass index (BMI) instruments were associated to all lung function traits and C-reactive protein (CRP) instruments to FVC. These genetic associations provide evidence for a causal effect of cardio-metabolic traits on lung function. Multivariable MR suggested independence of these causal effects from other tested cardio-metabolic traits and diseases. Analysis of lung function specific SNPs revealed a potential causal effect of FEV1/FVC on blood pressure. Conclusions The present study overcomes many limitations of observational studies by using Mendelian Randomisation. We provide evidence for an independent causal effect of T2D, CRP and BMI on lung function with some of the T2D effect on lung function being attributed to inflammatory mechanisms. Furthermore, this analysis suggests a potential causal effect of FEV1/FVC on blood pressure. Our detailed analysis of the interplay between cardio-metabolic traits and impaired lung function provides the opportunity to improve the quality of existing intervention strategies.

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