Daytime sleepiness, night sleep changes and ALS: a Mendelian randomization study

2020 ◽  
Author(s):  
Gan Zhang ◽  
Linjing Zhang ◽  
Tao Huang ◽  
Dongsheng Fan
Keyword(s):  
Sleep Duration ◽  
Daytime Sleepiness ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Sleep Efficiency ◽  
Genome Wide Association Studies ◽  
Night Sleep ◽  
Inverse Variance ◽  
Point Increase ◽  
Increased Risk

Abstract Background Observational studies have indicated that there is a high prevalence of daytime sleepiness and night sleep changes in amyotrophic lateral sclerosis (ALS). However, the actual relation between these symptoms and ALS remains unclear. We aimed to determine whether daytime sleepiness and night sleep changes have an effect on ALS. Methods We used 2-sample mendelian randomization to estimate the effects of daytime sleepiness, sleep efficiency, number of sleep episodes and sleep duration on ALS. Summary statistics we used was from resent and large genome-wide association studies on the traits we chosen (n = 85,670–452,071) and ALS (cases n = 20,806, controls n = 59,804). Inverse variance weighted method was used as the main method for assessing causality. Results A genetically predicted 1-point increase in the assessment of daytime sleepiness was significantly associated with an increased risk of ALS (inverse-variance-weighted (IVW) odds ratio = 2.70, 95% confidence interval (CI): 1.27–5.76; P = 0.010). ALS was not associated with a genetically predicted 1-SD increase in sleep efficiency (IVW 1.01, 0.64–1.58; P = 0.973), Number of sleep episodes (IVW 1.02, 0.80–1.30; P = 0.859) or sleep duration (IVW 1.00, 1.00–1.01; P = 0.250). Conclusions Our results provide novel evidence that daytime sleepiness causes an increase in the risk of ALS and indicate that daytime sleepiness may be inherent in preclinical and clinical ALS patients, rather than simply affected by potential influencing factors.

scholarly journals 454Relationships between sleep traits and metabolic profiles: evidence from multivariable regression and Mendelian randomization analyses

2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Neil Goulding ◽  
Maxime Bos ◽  
Diana van Heemst ◽  
Raymond Noordam ◽  
Deborah Lawlor
Keyword(s):  
Sleep Duration ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Association Studies ◽  
Inflammatory Marker ◽  
Genome Wide Association Studies ◽  
Inverse Variance ◽  
Multivariable Regression ◽  
Multivariable Analyses ◽  
Insomnia Symptoms

Abstract Background Sleep traits are associated with cardiometabolic disease. The aim of this study was to explore the causal effect of sleep traits (duration and insomnia) on multiple metabolic traits. Methods We used age, sex and BMI adjusted multivariable regression (N = 17,370) and two-sample summary statistic Mendelian randomization (MR) to examine effects of sleep duration and insomnia symptoms on ∼150 NMR metabolites. Multivariable analyses were conducted on data from nine European cohorts and meta-analysed. MR analyses utilised summary statistics from published genome-wide association studies (GWAS) of self-reported sleep traits (sample 1; N = 446,118 to 1,331,010) and from GWAS on NMR serum metabolites (sample 2; N = 38,618). We used inverse-variance weighted (IVW) for the main MR analyses and weighed median (WM) and MR-Egger to explore bias due to pleiotropy. Results MR IVW and multivariable analyses both suggest a positive effect of insomnia symptoms on glycoprotein acetyls (MR: 0.06 s.d. increase in mean concentration comparing any symptoms to none; p = 5.9e-4) and between total sleep duration and creatinine (MR: 0.16 s.d. increase per additional hour; p = 0.03). WM and MR-Egger analyses show consistent results. There was evidence for thirteen and eight effects of insomnia and duration in multivariable only and three and one, respectively, in MR only. Conclusions Insomnia symptoms lead to higher levels of an inflammatory marker (glycoprotein acetyls) and longer sleep duration leads to higher creatinine levels. Key messages We found no evidence of widespread metabolic disruption by sleep traits.

scholarly journals Evaluating the effects of alcohol and tobacco use on cardiovascular disease using multivariable Mendelian randomization

2019 ◽  
Author(s):  
Daniel B. Rosoff ◽  
George Davey Smith ◽  
Nehal Mehta ◽  
Toni-Kim Clarke ◽  
Falk W. Lohoff
Keyword(s):  
Risk Factors ◽  
Cardiovascular Disease ◽  
Alcohol Use ◽  
Tobacco Use ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Density Lipoprotein ◽  
Genome Wide Association Studies ◽  
Cvd Risk ◽  
Increased Risk

ABSTRACTAlcohol and tobacco use, two major modifiable risk factors for cardiovascular disease (CVD), are often consumed together. Using large publicly available genome-wide association studies (results from > 940,000 participants), we conducted two-sample multivariable Mendelian randomization (MR) to simultaneously assess the independent effects of alcohol and tobacco use on CVD risk factors and events. We found genetic instruments associated with increased alcohol use, controlling for tobacco use, associated with increased high-density-lipoprotein-cholesterol (HDL-C), decreased triglycerides, but not with coronary heart disease (CHD), myocardial infarction (MI), nor stroke; and instruments for increased tobacco use, controlling for alcohol use, associated with decreased HDL-C, increased triglycerides, and increased risk of CHD and MI. Exploratory analysis found associations with HDL-C, LDL-C, and intermediate-density-lipoprotein metabolites. Consistency of results across complementary methods accommodating different MR assumptions strengthened causal inference, providing strong genetic evidence for the causal effects of modifiable lifestyle risk factors on CVD risk.

scholarly journals Investigating genetic correlations and causal effects between caffeine consumption and sleep behaviours

2017 ◽  
Author(s):  
Jorien L. Treur ◽  
Mark Gibson ◽  
Amy E Taylor ◽  
Peter J Rogers ◽  
Marcus R Munafò
Keyword(s):  
Genetic Correlation ◽  
Sleep Duration ◽  
Genetic Variants ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Genetic Correlations ◽  
Causal Effects ◽  
Genome Wide Association Studies ◽  
Caffeine Consumption ◽  
Insomnia Complaints

AbstractStudy Objectives:Higher caffeine consumption has been linked to poorer sleep and insomnia complaints. We investigated whether these observational associations are the result of genetic risk factors influencing both caffeine consumption and poorer sleep, and/or whether they reflect (possibly bidirectional) causal effects.Methods:Summary-level data were available from genome-wide association studies (GWAS) on caffeine consumption (n=91,462), sleep duration, and chronotype (i.e., being a ‘morning’ versus an ‘evening’ person) (both n=128,266), and insomnia complaints (n=113,006). Linkage disequilibrium (LD) score regression was used to calculate genetic correlations, reflecting the extent to which genetic variants influencing caffeine consumption and sleep behaviours overlap. Causal effects were tested with bidirectional, two-sample Mendelian randomization (MR), an instrumental variable approach that utilizes genetic variants robustly associated with an exposure variable as an instrument to test causal effects. Estimates from individual genetic variants were combined using inverse-variance weighted meta-analysis, weighted median regression and MR Egger regression methods.Results:There was no clear evidence for genetic correlation between caffeine consumption and sleep duration (rg=0.000,p=0.998), chronotype (rg=0.086,p=0.192) or insomnia (rg=-0.034,p=0.700). Two-sample Mendelian randomization analyses did not support causal effects from caffeine consumption to sleep behaviours, or the other way around.Conclusions:We found no evidence in support of genetic correlation or causal effects between caffeine consumption and sleep. While caffeine may have acute effects on sleep when taken shortly before habitual bedtime, our findings suggest that a more sustained pattern of high caffeine consumption is likely associated with poorer sleep through shared environmental factors.

scholarly journals Inference of causal relationships between sleep-related traits and 1,527 phenotypes using genetic data

SLEEP ◽  
2020 ◽  
Author(s):  
Luis M García-Marín ◽  
Adrián I Campos ◽  
Nicholas G Martin ◽  
Gabriel Cuéllar-Partida ◽  
Miguel E Rentería
Keyword(s):  
Sleep Duration ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Causal Relationships ◽  
Physical And Mental Health ◽  
Related Factors ◽  
Study Objective ◽  
Genome Wide ◽  
Increased Risk ◽  
Level Statistics

Abstract Study Objective Sleep is essential for both physical and mental health, and there is a growing interest in understanding how different factors shape individual variation in sleep duration, quality and patterns, or confer risk for sleep disorders. The present study aimed to identify novel inferred causal relationships between sleep-related traits and other phenotypes, using a genetics-driven hypothesis-free approach not requiring longitudinal data. Methods We used summary-level statistics from genome-wide association studies and the latent causal variable (LCV) method to screen the phenome and infer causal relationships between seven sleep-related traits (insomnia, daytime dozing, easiness of getting up in the morning, snoring, sleep duration, napping, and morningness) and 1,527 other phenotypes. Results We identify 84 inferred causal relationships. Among other findings, connective tissue disorders increase insomnia risk and reduce sleep duration; depression-related traits increase insomnia and daytime dozing; insomnia, napping and snoring are affected by obesity and cardiometabolic traits and diseases; and working with asbestos, thinner, or glues may increase insomnia risk, possibly through an increased risk of respiratory disease or socio-economic related factors. Conclusion Overall, our results indicate that changes in sleep variables are predominantly the consequence, rather than the cause, of other underlying phenotypes and diseases. These insights could inform the design of future epidemiological and interventional studies in sleep medicine and research.

scholarly journals Software application profile: mrrobust—a tool for performing two-sample summary Mendelian randomization analyses

2018 ◽  
Vol 48 (3) ◽  
pp. 684-690 ◽  
Author(s):  
Wes Spiller ◽  
Neil M Davies ◽  
Tom M Palmer
Keyword(s):  
Mendelian Randomization ◽  
Association Studies ◽  
Estimation Methods ◽  
Genome Wide Association Studies ◽  
Software Application ◽  
Genome Wide ◽  
Inverse Variance ◽  
Randomization Analysis ◽  
Summary Data ◽  
Weighted Estimation

Abstract Motivation In recent years, Mendelian randomization analysis using summary data from genome-wide association studies has become a popular approach for investigating causal relationships in epidemiology. The mrrobust Stata package implements several of the recently developed methods. Implementation mrrobust is freely available as a Stata package. General features The package includes inverse variance weighted estimation, as well as a range of median, modal and MR-Egger estimation methods. Using mrrobust, plots can be constructed visualizing each estimate either individually or simultaneously. The package also provides statistics such as IGX2, which are useful in assessing attenuation bias in causal estimates. Availability The software is freely available from GitHub [https://raw.github.com/remlapmot/mrrobust/master/].

scholarly journals Association of 25 hydroxyvitamin D concentration with risk of COVID-19: a Mendelian randomization study

2020 ◽  
Author(s):  
Di Liu ◽  
Qiuyue Tian ◽  
Jie Zhang ◽  
Haifeng Hou ◽  
Wei Wang ◽  
...  
Keyword(s):  
Causal Relationship ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Sensitivity Analyses ◽  
Genome Wide Association Studies ◽  
Causal Association ◽  
Hydroxyvitamin D ◽  
Increased Risk ◽  
25Ohd Concentration ◽  
25 Hydroxyvitamin D

Background In observational studies, 25 hydroxyvitamin D (25OHD) concentration has been associated with an increased risk of Coronavirus disease 2019 (COVID-19). However, it remains unclear whether this association is causal. Methods We performed a two-sample Mendelian randomization (MR) to explore the causal relationship between 25OHD concentration and COVID-19, using summary data from the genome-wide association studies (GWASs) and using 25OHD concentration-related SNPs as instrumental variables (IVs). Results MR analysis did not show any evidence of a causal association of 25OHD concentration with COVID-19 susceptibility and severity (odds ratio [OR]=1.136, 95% confidence interval [CI] 0.988-1.306, P=0.074; OR=0.889, 95% CI 0.549-1.439, P=0.632). Sensitivity analyses using different instruments and statistical models yielded similar findings, suggesting the robustness of the causal association. No obvious pleiotropy bias and heterogeneity were observed. Conclusion The MR analysis showed that there might be no linear causal relationship of 25OHD concentration with COVID-19 susceptibility and severity.

scholarly journals Genetically Predicted Circulating Concentrations of Micronutrients and Risk of Amyotrophic Lateral Sclerosis: A Mendelian Randomization Study

2022 ◽  
Vol 12 ◽  
Author(s):  
Changqing Mu ◽  
Yating Zhao ◽  
Chen Han ◽  
Dandan Tian ◽  
Na Guo ◽  
...  
Keyword(s):  
Amyotrophic Lateral Sclerosis ◽  
Large Scale ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Inverse Variance ◽  
Effective Role ◽  
Copper Zinc ◽  
Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a progressive and devastating neurodegenerative disease with increasing incidence and high mortality, resulting in a considerable socio-economic burden. Till now, plenty of studies have explored the potential relationship between circulating levels of various micronutrients and ALS risk. However, the observations remain equivocal and controversial. Thus, we conducted a two-sample Mendelian randomization (MR) study to investigate the causality between circulating concentrations of 9 micronutrients, including retinol, folate acid, vitamin B12, B6 and C, calcium, copper, zinc as well as magnesium, and ALS susceptibility. In our analysis, several single nucleotide polymorphisms were collected as instrumental variables from large-scale genome-wide association studies of these 9 micronutrients. Then, inverse variance weighted (IVW) approach as well as alternative MR-Egger regression, weighted median and MR-pleiotropy residual sum and outlier (MR-PRESSO) analyses were performed to evaluate causal estimates. The results from IVW analysis showed that there was no causal relationship of 9 micronutrients with ALS risk. Meanwhile, the three complementary approaches obtained similar results. Thus, our findings indicated that supplementation of these 9 micronutrients may not play a clinically effective role in preventing the occurrence of ALS.

scholarly journals High Level of Uromodulin Increases the Risk of Hypertension: A Mendelian Randomization Study

2021 ◽  
Vol 8 ◽  
Author(s):  
Ruilian You ◽  
Lanlan Chen ◽  
Lubin Xu ◽  
Dingding Zhang ◽  
Haitao Li ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Causal Relationship ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Meta Analysis ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Inverse Variance ◽  
The Uk ◽  
High Level

Background: The association of uromodulin and hypertension has been observed in clinical studies, but not proven by a causal relationship. We conducted a two-sample Mendelian randomization (MR) analysis to investigate the causal relationship between uromodulin and blood pressure.Methods: We selected single nucleotide polymorphisms (SNPs) related to urinary uromodulin (uUMOD) and serum uromodulin (sUMOD) from a large Genome-Wide Association Studies (GWAS) meta-analysis study and research in PubMed. Six datasets based on the UK Biobank and the International Consortium for Blood Pressure (ICBP) served as outcomes with a large sample of hypertension (n = 46,188), systolic blood pressure (SBP, n = 1,194,020), and diastolic blood pressure (DBP, n = 1,194,020). The inverse variance weighted (IVW) method was performed in uUMOD MR analysis, while methods of IVW, MR-Egger, Weighted median, and Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) were utilized on sUMOD MR analysis.Results: MR analysis of IVM showed the odds ratio (OR) of the uUMOD to hypertension (“ukb-b-14057” and “ukb-b-14177”) is 1.04 (95% Confidence Interval (CI), 1.03-1.04, P < 0.001); the effect sizes of the uUMOD to SBP are 1.10 (Standard error (SE) = 0.25, P = 8.92E-06) and 0.03 (SE = 0.01, P = 2.70E-04) in “ieu-b-38” and “ukb-b-20175”, respectively. The β coefficient of the uUMOD to DBP is 0.88 (SE = 0.19, P = 4.38E-06) in “ieu-b-39” and 0.05 (SE = 0.01, P = 2.13E-10) in “ukb-b-7992”. As for the sUMOD, the OR of hypertension (“ukb-b-14057” and “ukb-b-14177”) is 1.01 (95% CI 1.01–1.02, all P < 0.001). The β coefficient of the SBP is 0.37 (SE = 0.07, P = 1.26E-07) in “ieu-b-38” and 0.01 (SE = 0.003, P = 1.04E-04) in “ukb-b-20175”. The sUMOD is causally associated with elevated DBP (“ieu-b-39”: β = 0.313, SE = 0.050, P = 3.43E-10; “ukb-b-7992”: β = 0.018, SE = 0.003, P = 8.41E-09).Conclusion: Our results indicated that high urinary and serum uromodulin levels are potentially detrimental in elevating blood pressure, and serve as a causal risk factor for hypertension.

scholarly journals The association between depression and metabolic syndrome and its components: a bidirectional two-sample Mendelian randomization study

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Min Zhang ◽  
Jing Chen ◽  
Zhiqun Yin ◽  
Lanbing Wang ◽  
Lihua Peng
Keyword(s):  
Metabolic Syndrome ◽  
Waist Circumference ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Fasting Blood Glucose ◽  
Density Lipoprotein ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Level Data ◽  
Inverse Variance

AbstractObservational studies suggested a bidirectional correlation between depression and metabolic syndrome (MetS) and its components. However, the causal associations between them remained unclear. We aimed to investigate whether genetically predicted depression is related to the risk of MetS and its components, and vice versa. We performed a bidirectional two-sample Mendelian randomization (MR) study using summary-level data from the most comprehensive genome-wide association studies (GWAS) of depression (n = 2,113,907), MetS (n = 291,107), waist circumference (n = 462,166), hypertension (n = 463,010) fasting blood glucose (FBG, n = 281,416), triglycerides (n = 441,016), high-density lipoprotein cholesterol (HDL-C, n = 403,943). The random-effects inverse-variance weighted (IVW) method was applied as the primary method. The results identified that genetically predicted depression was significantly positive associated with risk of MetS (OR: 1.224, 95% CI: 1.091–1.374, p = 5.58 × 10−4), waist circumference (OR: 1.083, 95% CI: 1.027–1.143, p = 0.003), hypertension (OR: 1.028, 95% CI: 1.016–1.039, p = 1.34 × 10−6) and triglycerides (OR: 1.111, 95% CI: 1.060–1.163, p = 9.35 × 10−6) while negative associated with HDL-C (OR: 0.932, 95% CI: 0.885–0.981, p = 0.007) but not FBG (OR: 1.010, 95% CI: 0.986–1.034, p = 1.34). No causal relationships were identified for MetS and its components on depression risk. The present MR analysis strength the evidence that depression is a risk factor for MetS and its components (waist circumference, hypertension, FBG, triglycerides, and HDL-C). Early diagnosis and prevention of depression are crucial in the management of MetS and its components.

scholarly journals Childhood obesity and multiple sclerosis: A Mendelian randomization study

2021 ◽  
pp. 135245852110017
Author(s):  
Adil Harroud ◽  
Ruth E Mitchell ◽  
Tom G Richardson ◽  
John A Morris ◽  
Vincenzo Forgetta ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Childhood Obesity ◽  
Mendelian Randomization ◽  
Pubertal Timing ◽  
Association Studies ◽  
Sensitivity Analyses ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Increased Risk ◽  
Age At Puberty

Background: Higher childhood body mass index (BMI) has been associated with an increased risk of multiple sclerosis (MS). Objective: To evaluate whether childhood BMI has a causal influence on MS, and whether this putative effect is independent from early adult obesity and pubertal timing. Methods: We performed Mendelian randomization (MR) using summary genetic data on 14,802 MS cases and 26,703 controls. Large-scale genome-wide association studies provided estimates for BMI in childhood ( n = 47,541) and adulthood ( n = 322,154). In multivariable MR, we examined the direct effects of each timepoint and further adjusted for age at puberty. Findings were replicated using the UK Biobank ( n = 453,169). Results: Higher genetically predicted childhood BMI was associated with increased odds of MS (odds ratio (OR) = 1.26/SD BMI increase, 95% confidence interval (CI): 1.07–1.50). However, there was little evidence of a direct effect after adjusting for adult BMI (OR = 1.03, 95% CI: 0.70–1.53). Conversely, the effect of adult BMI persisted independent of childhood BMI (OR = 1.43; 95% CI: 1.01–2.03). The addition of age at puberty did not alter the findings. UK Biobank analyses showed consistent results. Sensitivity analyses provided no evidence of pleiotropy. Conclusion: Genetic evidence supports an association between childhood obesity and MS susceptibility, mediated by persistence of obesity into early adulthood but independent of pubertal timing.

Sign in / Sign up

Export Citation Format

Share Document