Associations of insomnia on pregnancy and perinatal outcomes: Findings from Mendelian randomization and conventional observational studies in up to 356,069 women

Background: Insomnia is common and associated with adverse pregnancy and perinatal outcomes in observational studies. Our aim was to test whether insomnia causes stillbirth, miscarriage, gestational diabetes, hypertensive disorders of pregnancy, perinatal depression, preterm birth, or low/high offspring birthweight (LBW/HBW). Methods and Findings: We used two-sample Mendelian randomization (MR) with 81 single nucleotide polymorphisms instrumenting for a lifelong predisposition to insomnia. We used data (N=356,069) from the UK Biobank, FinnGen, and three European birth cohorts (Avon Longitudinal Study of Parents and Children (ALSPAC), Born in Bradford, and Norwegian Mother, Father and Child Cohort Study). Main MR analyses used inverse variance weighting (IVW), with weighted median and MR-Egger as sensitivity analyses. We compared MR estimates with multivariable regression of insomnia in pregnancy on outcomes in ALSPAC (N=11,745). IVW showed evidence of an effect of genetic susceptibility to insomnia on miscarriage (odds ratio (OR): 1.60, 95% confidence interval (CI): 1.18, 2.17), perinatal depression (OR 3.56, 95% CI: 1.49, 8.54) and LBW (OR 3.17, 95% CI: 1.69, 5.96). For other outcomes IVW indicated potentially clinically important adverse effects of insomnia (OR range 1.20 to 2.43), but CIs were wide and included the null. Weighted median and MR Egger results were directionally consistent, except for MR-Egger for gestational diabetes, perinatal depression, and preterm birth. Multivariable regression showed associations of insomnia at 18 weeks of gestation with miscarriage (OR 1.30, 95% CI: 1.12, 1.51), stillbirth (OR 2.10, 95% CI: 1.20, 3.69), and perinatal depression (OR 2.96, 95% CI: 2.42, 3.63), but not with LBW (OR 0.92, 95% CI: 0.69, 1.24). Key limitations are potential horizontal pleiotropy and low statistical power in MR, and residual confounding in multivariable regression. Conclusions: There is evidence of causal effects of insomnia on miscarriage, perinatal depression, and LBW. We highlight the need for larger studies with genomic data and pregnancy outcomes.

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Leukocyte telomere length and amyotrophic lateral sclerosis: a Mendelian randomization study

10.21203/rs.3.rs-522773/v2 ◽

2021 ◽

Author(s):

Kailin Xia ◽

Linjing Zhang ◽

Gan Zhang ◽

Yajun Wang ◽

Tao Huang ◽

...

Keyword(s):

Amyotrophic Lateral Sclerosis ◽

Telomere Length ◽

Causal Relationship ◽

Mendelian Randomization ◽

Association Studies ◽

Sensitivity Analyses ◽

Genome Wide Association Studies ◽

Leukocyte Telomere Length ◽

Weighted Median ◽

Lateral Sclerosis

Abstract Background Observational studies have suggested that telomere length is associated with amyotrophic lateral sclerosis (ALS). However, it remains unclear whether this association is causal. We employed a two-sample Mendelian randomization (MR) approach to explore the causal relationship between leukocyte telomere length (LTL) and ALS based on the most cited and most recent and largest LTL genome-wide association studies (GWASs) that measured LTL with the Southern blot method (n = 9190) and ALS GWAS summary data (n = 80,610). We adopted the inverse variance weighted (IVW) method to examine the effect of LTL on ALS and used the weighted median method, simple median method, MR Egger method and MR PRESSO method to perform sensitivity analyses. Results We found that genetically determined longer LTL was inversely associated with the risk of ALS (OR = 0.846, 95% CI: 0.744–0.962, P = 0.011), which was mainly driven by rs940209 in the OBFC1 gene, suggesting a potential effect of OBFC1 on ALS. In sensitivity analyses, that was confirmed in MR Egger method (OR = 0.647,95% CI = 0.447–0.936, P = 0.050), and a similar trend was shown with the weighted median method (OR = 0.893, P = 0.201) and simple median method (OR = 0.935 P = 0.535). The MR Egger analyses did not suggest directional pleiotropy, showing an intercept of 0.025 (P = 0.168). Neither the influence of instrumental outliers nor heterogeneity was found. Conclusions Our results suggest that genetically predicted longer LTL has a causal relationship with a lower risk of ALS and underscore the importance of protecting against telomere loss in ALS.

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Causal relationships between genetically determined metabolites and human intelligence: A Mendelian randomization study

10.21203/rs.3.rs-29322/v3 ◽

2020 ◽

Author(s):

Jian Yang ◽

Binbin Zhao ◽

Li Qian ◽

Fengjie Gao ◽

Yanjuan Fan ◽

...

Keyword(s):

Complex Traits ◽

Mendelian Randomization ◽

Sensitivity Analyses ◽

Human Intelligence ◽

Causal Relationships ◽

Biological Mechanisms ◽

Inverse Variance ◽

Weighted Median ◽

Genetic And Environmental Factors ◽

Genetically Determined

Abstract Intelligence predicts important life and health outcomes, but the biological mechanisms underlying differences in intelligence are not yet understood. The use of genetically determined metabotypes (GDMs) to understand the role of genetic and environmental factors, and their interactions, in human complex traits has been recently proposed. However, this strategy has not been applied to human intelligence. Here we implemented a two-sample Mendelian randomization (MR) analysis using GDMs to assess the causal relationships between genetically determined metabolites and human intelligence. The standard inverse-variance weighted (IVW) method was used for the primary MR analysis and three additional MR methods (MR-Egger, weighted median, and MR-PRESSO) were used for sensitivity analyses. Using 25 genetic variants as instrumental variables (IVs), our study found that 5-oxoproline was associated with better performance in human intelligence tests (P IVW = 9 · 25×10 -5 ). The causal relationship was robust when sensitivity analyses were applied (P MR-Egger = 0 · 0001, P Weighted median = 6 · 29×10 -6 , P MR-PRESSO = 0 · 0007), and no evidence of horizontal pleiotropy was observed. Similarly, also dihomo-linoleate (20:2n6) and p-acetamidophenylglucuronide showed robust association with intelligence. Our study provides novel insight by integrating genomics and metabolomics to estimate causal effects of genetically determined metabolites on human intelligence, which help to understanding of the biological mechanisms related to human intelligence.

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Are psychiatric disorders risk factors for COVID-19 susceptibility and severity? a two-sample, bidirectional, univariable and multivariable Mendelian Randomization study

10.1101/2020.11.29.20240481 ◽

2020 ◽

Author(s):

Jurjen J. Luykx ◽

Bochao D. Lin

Keyword(s):

Bipolar Disorder ◽

Psychiatric Disorders ◽

Observational Studies ◽

Mendelian Randomization ◽

Neuropsychiatric Disorders ◽

Sensitivity Analyses ◽

Effect Estimate ◽

Genome Wide Association Studies ◽

Genetic Liability ◽

Increased Risk

AbstractImportanceObservational studies have suggested bidirectional associations between psychiatric disorders and COVID-19 phenotypes, but results of such studies are inconsistent. Mendelian Randomization (MR) may overcome limitations of observational studies, e.g. unmeasured confounding and uncertainties about cause and effect.ObjectiveTo elucidate associations between neuropsychiatric disorders and COVID-19 susceptibility and severity.MethodIn November, 2020, we applied a two-sample, bidirectional, univariable and multivariable MR design to genetic data from genome-wide association studies (GWASs) of neuropsychiatric disorders and COVID-19 phenotypes (released on 20 Oct. 2020). Our study population consisted of almost 2 million participants with either a (neuro)psychiatric disorder or data on COVID-19 status. Outcomes and exposures were anxiety, anxiety-and-stress related disorders, major depressive disorder, schizophrenia, bipolar disorder, schizophrenia-bipolar disorder combined (BIP-SCZ), and Alzheimer’s dementia on the one hand; and self-reported, confirmed, hospitalized, and very severe COVID-19 on the other.ResultsIn single-variable MR analysis the most significant and only Bonferroni-corrected significant result was found for BIP-SCZ (a combined anxiety of bipolar disorder and schizophrenia as cases vs. controls): the effect estimate was consistent with increased risk of COVID-19 (OR = 1.17, 95% CI, 1.06-1.28; p = 0.0012). Nominally significant univariable results were in line with slightly elevated risks of COVID-19 for genetic liabilities to bipolar disorder and schizophrenia. No COVID-19 phenotype consistently increased risk of (neuro)psychiatric disorders. In multivariable MR, bipolar disorder was the only phenotype showing a Bonferroni-corrected significant effect on a COVID-19 phenotype, namely severe COVID-19 (OR = 1.293; 95% CI, 1.095-1.527; p = 0.003). All sensitivity analyses confirmed the results.ConclusionsGenetic liability to bipolar disorder slightly increases COVID-19 susceptibility and severity. The contribution of bipolar disorder to these COVID-19 phenotypes was smaller than the odds ratios estimated by observational studies. Strength of association and direction of effect for genetic liability to schizophrenia were similar, albeit less significant. We found no consistent evidence of reverse effects, i.e. of genetic liability to COVID-19 on psychiatric disorders.

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Causal association of adipokines with osteoarthritis: a Mendelian randomization study

Rheumatology ◽

10.1093/rheumatology/keaa719 ◽

2020 ◽

Author(s):

Jiayao Fan ◽

Jiahao Zhu ◽

Lingling Sun ◽

Yasong Li ◽

Tianle Wang ◽

...

Keyword(s):

Mendelian Randomization ◽

Association Studies ◽

Genome Wide Association ◽

Sensitivity Analyses ◽

European Ancestry ◽

Genome Wide Association Studies ◽

Knee Oa ◽

Genome Wide ◽

A Genome ◽

Weighted Median

Abstract Objective This two-sample Mendelian randomization study aimed to delve into the effects of genetically predicted adipokine levels on OA. Methods Summary statistic data for OA originated from a meta-analysis of a genome-wide association study with an overall 50 508 subjects of European ancestry. Publicly available summary data from four genome-wide association studies were exploited to respectively identify instrumental variables of adiponectin, leptin, resistin, chemerin and retinol-blinding protein 4. Subsequently, Mendelian randomization analyses were conducted with inverse variance weighted (IVW), weighted median and Mendelian randomization-Egger regression. Furthermore, sensitivity analyses were then conducted to assess the robustness of our results. Results The positive causality between genetically predicted leptin level and risk of total OA was indicated by IVW [odds ratio (OR): 2.40, 95% CI: 1.13–5.09] and weighted median (OR: 2.94, 95% CI: 1.23–6.99). In subgroup analyses, evidence of potential harmful effects of higher level of adiponectin (OR: 1.28, 95% CI: 1.01–1.61 using IVW), leptin (OR: 3.44, 95% CI: 1.18–10.03 using IVW) and resistin (OR: 1.18, 95% CI: 1.03–1.36 using IVW) on risk of knee OA were acquired. However, the mentioned effects on risk of hip OA were not statistically significant. Slight evidence was identified supporting causality of chemerin and retinol-blinding protein 4 for OA. The findings of this study were verified by the results from sensitivity analysis. Conclusions An association between genetically predicted leptin level and risk of total OA was identified. Furthermore, association of genetically predicted levels of adiponectin, leptin and resistin with risk of knee OA were reported.

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Causal relationships between genetically determined metabolites and human intelligence: a Mendelian randomization study

Molecular Brain ◽

10.1186/s13041-021-00743-4 ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Jian Yang ◽

Binbin Zhao ◽

Li Qian ◽

Fengjie Gao ◽

Yanjuan Fan ◽

...

Keyword(s):

Complex Traits ◽

Mendelian Randomization ◽

Sensitivity Analyses ◽

Human Intelligence ◽

Causal Relationships ◽

Biological Mechanisms ◽

Inverse Variance ◽

Weighted Median ◽

Genetic And Environmental Factors ◽

Genetically Determined

AbstractIntelligence predicts important life and health outcomes, but the biological mechanisms underlying differences in intelligence are not yet understood. The use of genetically determined metabotypes (GDMs) to understand the role of genetic and environmental factors, and their interactions, in human complex traits has been recently proposed. However, this strategy has not been applied to human intelligence. Here we implemented a two-sample Mendelian randomization (MR) analysis using GDMs to assess the causal relationships between genetically determined metabolites and human intelligence. The standard inverse-variance weighted (IVW) method was used for the primary MR analysis and three additional MR methods (MR-Egger, weighted median, and MR-PRESSO) were used for sensitivity analyses. Using 25 genetic variants as instrumental variables (IVs), our study found that 5-oxoproline was associated with better performance in human intelligence tests (PIVW = 9.25 × 10–5). The causal relationship was robust when sensitivity analyses were applied (PMR-Egger = 0.0001, PWeighted median = 6.29 × 10–6, PMR-PRESSO = 0.0007), and repeated analysis yielded consistent result (PIVW = 0.0087). Similarly, also dihomo-linoleate (20:2n6) and p-acetamidophenylglucuronide showed robust association with intelligence. Our study provides novel insight by integrating genomics and metabolomics to estimate causal effects of genetically determined metabolites on human intelligence, which help to understanding of the biological mechanisms related to human intelligence.

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Mendelian randomization analysis of the association between human blood cell traits and uterine polyps

Scientific Reports ◽

10.1038/s41598-021-84851-0 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Shuliu Sun ◽

Yan Liu ◽

Lanlan Li ◽

Minjie Jiao ◽

Yufen Jiang ◽

...

Keyword(s):

Human Blood ◽

Genome Wide Association Study ◽

Mendelian Randomization ◽

Random Effect ◽

Sensitivity Analyses ◽

Endometrial Polyps ◽

Inverse Variance ◽

Weighted Median ◽

The Uk ◽

Uterine Polyps

AbstractHuman blood cells (HBCs) play essential roles in multiple biological processes but their roles in development of uterine polyps are unknown. Here we implemented a Mendelian randomization (MR) analysis to investigate the effects of 36 HBC traits on endometrial polyps (EPs) and cervical polyps (CPs). The random-effect inverse-variance weighted method was adopted as standard MR analysis and three additional MR methods (MR-Egger, weighted median, and MR-PRESSO) were used for sensitivity analyses. Genetic instruments of HBC traits was extracted from a large genome-wide association study of 173,480 individuals, while data for EPs and CPs were obtained from the UK Biobank. All samples were Europeans. Using genetic variants as instrumental variables, our study found that both eosinophil count (OR 0.85, 95% CI 0.79–0.93, P = 1.06 × 10−4) and eosinophil percentage of white cells (OR 0.84, 95% CI 0.77–0.91, P = 2.43 × 10−5) were associated with decreased risk of EPs. The results were robust in sensitivity analyses and no evidences of horizontal pleiotropy were observed. While we found no significant associations between HBC traits and CPs. Our findings suggested eosinophils might play important roles in the pathogenesis of EPs. Besides, out study provided novel insight into detecting uterine polyps biomarkers using genetic epidemiology approaches.

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Investigating the relationships between unfavourable habitual sleep and metabolomic traits: evidence from multi-cohort multivariable regression and Mendelian randomization analyses

BMC Medicine ◽

10.1186/s12916-021-01939-0 ◽

2021 ◽

Vol 19 (1) ◽

Author(s):

Maxime M. Bos ◽

Neil J. Goulding ◽

Matthew A. Lee ◽

Amy Hofman ◽

Mariska Bot ◽

...

Keyword(s):

Sleep Duration ◽

Mendelian Randomization ◽

Disease Risk ◽

Association Studies ◽

Sensitivity Analyses ◽

European Ancestry ◽

Genome Wide Association Studies ◽

Multivariable Regression ◽

Artery Disease ◽

Insomnia Symptoms

Abstract Background Sleep traits are associated with cardiometabolic disease risk, with evidence from Mendelian randomization (MR) suggesting that insomnia symptoms and shorter sleep duration increase coronary artery disease risk. We combined adjusted multivariable regression (AMV) and MR analyses of phenotypes of unfavourable sleep on 113 metabolomic traits to investigate possible biochemical mechanisms linking sleep to cardiovascular disease. Methods We used AMV (N = 17,368) combined with two-sample MR (N = 38,618) to examine effects of self-reported insomnia symptoms, total habitual sleep duration, and chronotype on 113 metabolomic traits. The AMV analyses were conducted on data from 10 cohorts of mostly Europeans, adjusted for age, sex, and body mass index. For the MR analyses, we used summary results from published European-ancestry genome-wide association studies of self-reported sleep traits and of nuclear magnetic resonance (NMR) serum metabolites. We used the inverse-variance weighted (IVW) method and complemented this with sensitivity analyses to assess MR assumptions. Results We found consistent evidence from AMV and MR analyses for associations of usual vs. sometimes/rare/never insomnia symptoms with lower citrate (− 0.08 standard deviation (SD)[95% confidence interval (CI) − 0.12, − 0.03] in AMV and − 0.03SD [− 0.07, − 0.003] in MR), higher glycoprotein acetyls (0.08SD [95% CI 0.03, 0.12] in AMV and 0.06SD [0.03, 0.10) in MR]), lower total very large HDL particles (− 0.04SD [− 0.08, 0.00] in AMV and − 0.05SD [− 0.09, − 0.02] in MR), and lower phospholipids in very large HDL particles (− 0.04SD [− 0.08, 0.002] in AMV and − 0.05SD [− 0.08, − 0.02] in MR). Longer total sleep duration associated with higher creatinine concentrations using both methods (0.02SD per 1 h [0.01, 0.03] in AMV and 0.15SD [0.02, 0.29] in MR) and with isoleucine in MR analyses (0.22SD [0.08, 0.35]). No consistent evidence was observed for effects of chronotype on metabolomic measures. Conclusions Whilst our results suggested that unfavourable sleep traits may not cause widespread metabolic disruption, some notable effects were observed. The evidence for possible effects of insomnia symptoms on glycoprotein acetyls and citrate and longer total sleep duration on creatinine and isoleucine might explain some of the effects, found in MR analyses of these sleep traits on coronary heart disease, which warrant further investigation.

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Carnitine and COVID-19 Susceptibility and Severity: A Mendelian Randomization Study

Frontiers in Nutrition ◽

10.3389/fnut.2021.780205 ◽

2021 ◽

Vol 8 ◽

Author(s):

Chunyu Li ◽

Ruwei Ou ◽

Qianqian Wei ◽

Huifang Shang

Keyword(s):

Causal Relationship ◽

Genome Wide Association Study ◽

Mendelian Randomization ◽

Sensitivity Analyses ◽

Nucleotide Polymorphisms ◽

Carnitine Level ◽

Standard Deviation Increase ◽

Inverse Variance ◽

Weighted Median ◽

Genetically Determined

Background: Carnitine, a potential substitute or supplementation for dexamethasone, might protect against COVID-19 based on its molecular functions. However, the correlation between carnitine and COVID-19 has not been explored yet, and whether there exists causation is unknown.Methods: A two-sample Mendelian randomization (MR) analysis was conducted to explore the causal relationship between carnitine level and COVID-19. Significant single nucleotide polymorphisms from genome-wide association study on carnitine (N = 7,824) were utilized as exposure instruments, and summary statistics of the susceptibility (N = 1,467,264), severity (N = 714,592) and hospitalization (N = 1,887,658) of COVID-19 were utilized as the outcome. The causal relationship was evaluated by multiplicative random effects inverse variance weighted (IVW) method, and further verified by another three MR methods including MR Egger, weighted median, and weighted mode, as well as extensive sensitivity analyses.Results: Genetically determined one standard deviation increase in carnitine amount was associated with lower susceptibility (OR: 0.38, 95% CI: 0.19–0.74, P: 4.77E−03) of COVID-19. Carnitine amount was also associated with lower severity and hospitalization of COVID-19 using another three MR methods, though the association was not significant using the IVW method but showed the same direction of effect. The results were robust under all sensitivity analyses.Conclusions: A genetic predisposition to high carnitine levels might reduce the susceptibility and severity of COVID-19. These results provide better understandings on the role of carnitine in the COVID-19 pathogenesis, and facilitate novel therapeutic targets for COVID-19 in future clinical trials.

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Periodontal disease increases the host susceptibility to COVID-19 and its severity: a Mendelian randomization study

Journal of Translational Medicine ◽

10.1186/s12967-021-03198-2 ◽

2021 ◽

Vol 19 (1) ◽

Author(s):

Yi Wang ◽

Hui Deng ◽

Yihuai Pan ◽

Lijian Jin ◽

Rongdang Hu ◽

...

Keyword(s):

Periodontal Disease ◽

Genome Wide Association Study ◽

Mendelian Randomization ◽

Host Susceptibility ◽

Sensitivity Analyses ◽

Nucleotide Polymorphisms ◽

Genome Wide ◽

Inverse Variance ◽

Weighted Median ◽

First Time

Abstract Background Emerging evidence shows that periodontal disease (PD) may increase the risk of Coronavirus disease 2019 (COVID-19) complications. Here, we undertook a two-sample Mendelian randomization (MR) study, and investigated for the first time the possible causal impact of PD on host susceptibility to COVID-19 and its severity. Methods Summary statistics of COVID-19 susceptibility and severity were retrieved from the COVID-19 Host Genetics Initiative and used as outcomes. Single nucleotide polymorphisms associated with PD in Genome-wide association study were included as exposure. Inverse-variance weighted (IVW) method was employed as the main approach to analyze the causal relationships between PD and COVID-19. Three additional methods were adopted, allowing the existence of horizontal pleiotropy, including MR-Egger regression, weighted median and weighted mode methods. Comprehensive sensitivity analyses were also conducted for estimating the robustness of the identified associations. Results The MR estimates showed that PD was significantly associated with significantly higher susceptibility to COVID-19 using IVW (OR = 1.024, P = 0.017, 95% CI 1.004–1.045) and weighted median method (OR = 1.029, P = 0.024, 95% CI 1.003–1.055). Furthermore, it revealed that PD was significantly linked to COVID-19 severity based on the comparison of hospitalization versus population controls (IVW, OR = 1.025, P = 0.039, 95% CI 1.001–1.049; weighted median, OR = 1.030, P = 0.027, 95% CI 1.003–1.058). No such association was observed in the cohort of highly severe cases confirmed versus those not hospitalized due to COVID-19. Conclusions We provide evidence on the possible causality of PD accounting for the susceptibility and severity of COVID-19, highlighting the importance of oral/periodontal healthcare for general wellbeing during the pandemic and beyond.

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Elucidation of a Causal Relationship Between Platelet Count and Hypertension: A Bi-Directional Mendelian Randomization Study

Frontiers in Cardiovascular Medicine ◽

10.3389/fcvm.2021.743075 ◽

2021 ◽

Vol 8 ◽

Author(s):

Po-Chun Chiu ◽

Amrita Chattopadhyay ◽

Meng-Chun Wu ◽

Tzu-Hung Hsiao ◽

Ching-Heng Lin ◽

...

Keyword(s):

Platelet Count ◽

Causal Relationship ◽

Mendelian Randomization ◽

Causal Effect ◽

Sensitivity Analyses ◽

Exact Nature ◽

Nucleotide Polymorphisms ◽

Single Nucleotide ◽

Inverse Variance ◽

Weighted Median

Hypertension has been reported as a major risk factor for diseases such as cardiovascular disease, and associations between platelet activation and risk for hypertension are well-established. However, the exact nature of causality between them remains unclear. In this study, a bi-directional Mendelian randomization (MR) analysis was conducted on 15,996 healthy Taiwanese individuals aged between 30 and 70 years from the Taiwan Biobank, recorded between 2008 and 2015. The inverse variance weighted (IVW) method was applied to determine the causal relationship between platelet count and hypertension with single nucleotide polymorphisms as instrumental variables (IVs). Furthermore, to check for pleiotropy and validity of the IVs, sensitivity analyses were performed using the MR-Egger, weighted median and simple median methods. This study provided evidence in support of a positive causal effect of platelet count on the risk of hypertension (odds ratio: 1.149, 95% confidence interval: 1.131–1.578, P < 0.05), using the weighted median method. A significant causal effect of platelet count on hypertension was observed using the IVW method. No pleiotropy was observed. The causal effect of hypertension on platelet count was found to be non-significant. Therefore, the findings from this study provide evidence that higher platelet count may have a significant causal effect on the elevated risk of hypertension for the general population of Taiwan.

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