586Effects of maternal circulating amino acids on offspring birthweight: a Mendelian randomisation analysis

Abstract Background It is suggested amino acids are critical for fetal growth, but analyses assessing causality are lacking. Mendelian randomisation (MR) can be used to examine causal effects under instrumental variable (IV) assumptions. Methods We conducted a two-sample MR study utilizing summary data from genome-wide association studies (GWAS) of amino acids (sample 1, n = 86,507) and of offspring birthweight (sample 2, combined UK Biobank and Early Growth Genetics Consortium, n = 406,063). Seventy-five independent single nucleotide polymorphisms (SNPs) robustly associated with 18 amino acids (p < 4.9 × 10-10) were used as genetic instruments. Wald ratio and inverse variance weighted methods were used in MR main analysis. Sensitivity analyses were performed to explore IV assumption violations. To explore whether there was consistency between SNP-amino acid associations in pregnancy and in the GWAS, the latter were compared to associations in the Born in Bradford cohort. Results There was evidence of positive causal effects of maternal alanine (51.9 g birthweight increase per SD increase in amino acid level, 95% CI: 24.2, 79.5), glutamine (51.3 g, 95% CI: 33.5, 69.0), glycine (10.4 g, 95% CI: 1.3, 19.6) and serine (27.1 g, 95% CI: 11.2, 43.0) on birthweight and inverse causal effects of maternal isoleucine (-109.7 g, 95% CI: -194.6, -24.9) and histidine (-41.1 g, 95% CI: -78.5, -3.7) on birthweight. Sensitivity analyses to explore reverse causality and bias due to horizontal pleiotropy supported our findings. Conclusions Some maternal circulating amino acids have causal effects on birthweight. Key messages MR can be extended to probe effects of maternal nutrition on offspring development.

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Cigarette smoking and schizophrenia: Mendelian randomisation study

The British Journal of Psychiatry ◽

10.1192/bjp.2020.116 ◽

2020 ◽

pp. 1-6

Author(s):

Jianhua Chen ◽

Ruirui Chen ◽

Siying Xiang ◽

Ningning Li ◽

Chengwen Gao ◽

...

Keyword(s):

Cigarette Smoking ◽

Association Studies ◽

Smoking Initiation ◽

Sensitivity Analyses ◽

Mendelian Randomisation ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Complex Behaviour ◽

Asian Populations ◽

Smoking Behaviours

Background The link between schizophrenia and cigarette smoking has been well established through observational studies. However, the cause–effect relationship remains unclear. Aims We conducted Mendelian randomisation analyses to assess any causal relationship between genetic variants related to four smoking-related traits and the risk of schizophrenia. Method We performed a two-sample Mendelian randomisation using summary statistics from genome-wide association studies (GWAS) of smoking-related traits and schizophrenia (7711 cases, 18 327 controls) in East Asian populations. Single nucleotide polymorphisms (SNPs) correlated with smoking behaviours (smoking initiation, smoking cessation, age at smoking initiation and quantity of smoking) were investigated in relation to schizophrenia using the inverse-variance weighted (IVW) method. Further sensitivity analyses, including Mendelian randomisation-Egger (MR-Egger), weighted median estimates and leave-one-out analysis, were used to test the consistency of the results. Results The associated SNPs for the four smoking behaviours were not significantly associated with schizophrenia status. Pleiotropy did not inappropriately affect the results. Conclusions Cigarette smoking is a complex behaviour in people with schizophrenia. Understanding factors underlying the observed association remains important; however, our findings do not support a causal role of smoking in influencing risk of schizophrenia.

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

British Journal of Cancer ◽

10.1038/s41416-021-01432-8 ◽

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.

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Type 2 Diabetes and Glycemic Traits Are Not Causal Factors of Osteoarthritis: A Two-Sample Mendelian Randomization Analysis

Frontiers in Genetics ◽

10.3389/fgene.2020.597876 ◽

2021 ◽

Vol 11 ◽

Author(s):

Zhiyong Cui ◽

Hui Feng ◽

Baichuan He ◽

Yong Xing ◽

Zhaorui Liu ◽

...

Keyword(s):

Type 2 Diabetes ◽

Mendelian Randomization ◽

Association Studies ◽

Causal Effects ◽

Sensitivity Analyses ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Knee Oa ◽

Increased Risk

BackgroundIt remains unclear whether an increased risk of type 2 diabetes (T2D) affects the risk of osteoarthritis (OA).MethodsHere, we used two-sample Mendelian randomization (MR) to obtain non-confounded estimates of the effect of T2D and glycemic traits on hip and knee OA. We identified single-nucleotide polymorphisms (SNPs) strongly associated with T2D, fasting glucose (FG), and 2-h postprandial glucose (2hGlu) from genome-wide association studies (GWAS). We used the MR inverse variance weighted (IVW), the MR–Egger method, the weighted median (WM), and the Robust Adjusted Profile Score (MR.RAPS) to reveal the associations of T2D, FG, and 2hGlu with hip and knee OA risks. Sensitivity analyses were also conducted to verify whether heterogeneity and pleiotropy can bias the MR results.ResultsWe did not find statistically significant causal effects of genetically increased T2D risk, FG, and 2hGlu on hip and knee OA (e.g., T2D and hip OA, MR–Egger OR = 1.1708, 95% CI 0.9469–1.4476, p = 0.1547). It was confirmed that horizontal pleiotropy was unlikely to bias the causality (e.g., T2D and hip OA, MR–Egger, intercept = −0.0105, p = 0.1367). No evidence of heterogeneity was found between the genetic variants (e.g., T2D and hip OA, MR–Egger Q = 30.1362, I2 < 0.0001, p = 0.6104).ConclusionOur MR study did not support causal effects of a genetically increased T2D risk, FG, and 2hGlu on hip and knee OA risk.

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Type 2 diabetes and glycemic traits are not causal factors of osteoarthritis: A two-sample Mendelian randomization analysis

10.21203/rs.3.rs-37242/v1 ◽

2020 ◽

Author(s):

Zhiyong Cui ◽

Hui Feng ◽

Baichuan He ◽

Yong Xing ◽

Zhaorui Liu ◽

...

Keyword(s):

Type 2 Diabetes ◽

Mendelian Randomization ◽

Association Studies ◽

Causal Effects ◽

Sensitivity Analyses ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Knee Oa ◽

Increased Risk

Abstract Background: It remains unclear whether an increased risk of type 2 diabetes (T2D) affects the risk of osteoarthritis (OA). Methods: Here, we used two-sample Mendelian randomization (MR) to obtain non-confounded estimates of the effect of T2D and glycemic traits on hip and knee OA. We identified single nucleotide polymorphisms (SNPs) strongly associated with T2D, fasting glucose (FG) and 2-hour postprandial glucose (2hGlu) from genome-wide association studies (GWAS) . We used MR inverse variance weighted (IVW), the MR-Egger method, the weighted median (WM) and Robust Adjusted Profile Score (MR.RAPS) to reveal the associations of T2D, FG and 2hGlu with hip and knee OA risk. Sensitivity analyses were also conducted to verify whether heterogeneity and pleiotropy can bias the MR results.Results: We did not find statistically significant causal effects of genetically increased T2D risk, FG and 2hGlu on hip and knee OA (e.g., T2D and hip OA, MR-Egger OR=0.9536, 95% CI 0.5585 to 1.6283, p=0.8629). It was confirmed that horizontal pleiotropy was unlikely to bias the causality (e.g., T2D and hip OA, MR-Egger, intercept=-0.0032, p=0.8518). No evidence of heterogeneity was found between the genetic variants (e.g., T2D and hip OA, MR-Egger Q=40.5481, I2=0.1368, p=0.2389). Conclusions: Our MR study did not support causal effects of a genetically increased T2D risk, FG and 2hGlu on hip and knee OA risk.

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Relationship between smoking and ALS: Mendelian randomisation interrogation of causality

Journal of Neurology Neurosurgery & Psychiatry ◽

10.1136/jnnp-2020-323316 ◽

2020 ◽

Vol 91 (12) ◽

pp. 1312-1315

Author(s):

Sarah Opie-Martin ◽

Robyn E Wootton ◽

Ashley Budu-Aggrey ◽

Aleksey Shatunov ◽

Ashley R Jones ◽

...

Keyword(s):

Association Studies ◽

Genome Wide Association ◽

Sensitivity Analyses ◽

Mendelian Randomisation ◽

P Value ◽

Genome Wide Association Studies ◽

Reverse Causality ◽

Genome Wide ◽

Inverse Variance ◽

A Genome

ObjectiveSmoking has been widely studied as a susceptibility factor for amyotrophic lateral sclerosis (ALS), but results are conflicting and at risk of confounding bias. We used the results of recently published large genome-wide association studies and Mendelian randomisation methods to reduce confounding to assess the relationship between smoking and ALS.MethodsTwo genome-wide association studies investigating lifetime smoking (n=463 003) and ever smoking (n=1 232 091) were identified and used to define instrumental variables for smoking. A genome-wide association study of ALS (20 806 cases; 59 804 controls) was used as the outcome for inverse variance weighted Mendelian randomisation, and four other Mendelian randomisation methods, to test whether smoking is causal for ALS. Analyses were bidirectional to assess reverse causality.ResultsThere was no strong evidence for a causal or reverse causal relationship between smoking and ALS. The results of Mendelian randomisation using the inverse variance weighted method were: lifetime smoking OR 0.94 (95% CI 0.74 to 1.19), p value 0.59; ever smoking OR 1.10 (95% CI 1 to 1.23), p value 0.05.ConclusionsUsing multiple methods, large sample sizes and sensitivity analyses, we find no evidence with Mendelian randomisation techniques that smoking causes ALS. Other smoking phenotypes, such as current smoking, may be suitable for future Mendelian randomisation studies

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Univariable and Multivariable Two-Sample Mendelian Randomization Investigating the Effects of Leisure Sedentary Behaviors on the Risk of Lung Cancer

Frontiers in Genetics ◽

10.3389/fgene.2021.742718 ◽

2021 ◽

Vol 12 ◽

Author(s):

Haoxin Peng ◽

Xiangrong Wu ◽

Yaokai Wen ◽

Yiyuan Ao ◽

Yutian Li ◽

...

Keyword(s):

Lung Cancer ◽

Computer Use ◽

Mendelian Randomization ◽

Causal Effect ◽

Association Studies ◽

Sensitivity Analyses ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Sedentary Behaviors ◽

Watching Tv

Background:Leisure sedentary behaviors (LSB) are widespread, and observational studies have provided emerging evidence that LSB play a role in the development of lung cancer (LC). However, the causal inference between LSB and LC remains unknown.Methods: We utilized univariable (UVMR) and multivariable two-sample Mendelian randomization (MVMR) analysis to disentangle the effects of LSB on the risk of LC. MR analysis was conducted with genetic variants from genome-wide association studies of LSB (408,815 persons from UK Biobank), containing 152 single-nucleotide polymorphisms (SNPs) for television (TV) watching, 37 SNPs for computer use, and four SNPs for driving, and LC from the International Lung Cancer Consortium (11,348 cases and 15,861 controls). Multiple sensitivity analyses were further performed to verify the causality.Results: UVMR demonstrated that genetically predisposed 1.5-h increase in LSB spent on watching TV increased the odds of LC by 90% [odds ratio (OR), 1.90; 95% confidence interval (CI), 1.44–2.50; p < 0.001]. Similar trends were observed for squamous cell lung cancer (OR, 1.97; 95%CI, 1.31–2.94; p = 0.0010) and lung adenocarcinoma (OR, 1.64; 95%CI 1.12–2.39; p = 0.0110). The causal effects remained significant after adjusting for education (OR, 1.97; 95%CI, 1.44–2.68; p < 0.001) and body mass index (OR, 1.86; 95%CI, 1.36–2.54; p < 0.001) through MVMR approach. No association was found between prolonged LSB spent on computer use and driving and LC risk. Genetically predisposed prolonged LSB was additionally correlated with smoking (OR, 1.557; 95%CI, 1.287–1.884; p < 0.001) and alcohol consumption (OR, 1.010; 95%CI, 1.004–1.016; p = 0.0016). Consistency of results across complementary sensitivity MR methods further strengthened the causality.Conclusion: Robust evidence was demonstrated for an independent, causal effect of LSB spent on watching TV in increasing the risk of LC. Further work is necessary to investigate the potential mechanisms.

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Personality, lifestyle and job satisfaction: causal association between neuroticism and job satisfaction using Mendelian randomisation in the UK biobank cohort

Translational Psychiatry ◽

10.1038/s41398-020-0691-3 ◽

2020 ◽

Vol 10 (1) ◽

Cited By ~ 1

Author(s):

Gull Rukh ◽

Junhua Dang ◽

Gaia Olivo ◽

Diana-Maria Ciuculete ◽

Mathias Rask-Andersen ◽

...

Keyword(s):

Physical Activity ◽

Job Satisfaction ◽

Association Studies ◽

Sensitivity Analyses ◽

Mendelian Randomisation ◽

Genome Wide Association Studies ◽

Single Variable ◽

Causal Association ◽

Uk Biobank ◽

The Uk

AbstractJob-related stress has been associated with poor health outcomes but little is known about the causal nature of these findings. We employed Mendelian randomisation (MR) approach to investigate the causal effect of neuroticism, education, and physical activity on job satisfaction. Trait-specific genetic risk score (GRS) based on recent genome wide association studies were used as instrumental variables (IV) using the UK Biobank cohort (N = 315,536). Both single variable and multivariable MR analyses were used to determine the effect of each trait on job satisfaction. We observed a clear evidence of a causal association between neuroticism and job satisfaction. In single variable MR, one standard deviation (1 SD) higher genetically determined neuroticism score (4.07 units) was associated with −0.31 units lower job satisfaction (95% confidence interval (CI): −0.38 to −0.24; P = 9.5 × 10−20). The causal associations remained significant after performing sensitivity analyses by excluding invalid genetic variants from GRSNeuroticism (β(95%CI): −0.28(−0.35 to −0.21); P = 3.4 x 10−15). Education (0.02; −0.08 to 0.12; 0.67) and physical activity (0.08; −0.34 to 0.50; 0.70) did not show any evidence for causal association with job satisfaction. When genetic instruments for neuroticism, education and physical activity were included together, the association of neuroticism score with job satisfaction was reduced by only −0.01 units, suggesting an independent inverse causal association between neuroticism score (P = 2.7 x 10−17) and job satisfaction. Our findings show an independent causal association between neuroticism score and job satisfaction. Physically active lifestyle may help to increase job satisfaction despite presence of high neuroticism scores. Our study highlights the importance of considering the confounding effect of negative personality traits for studies on job satisfaction.

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The relationship between cognitive function, Alzheimer's disease and sleep duration: A Mendelian randomisation study

10.1101/2020.09.08.20190611 ◽

2020 ◽

Author(s):

Antoine Salzmann ◽

Nishi Chaturvedi ◽

Victoria Garfield

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Reaction Time ◽

Cognitive Function ◽

Sleep Duration ◽

Association Studies ◽

Sensitivity Analyses ◽

Mendelian Randomisation ◽

Genome Wide Association Studies ◽

The Relationship

Objective: Sleep duration is associated with cognitive function and dementia. MR evidence to date, points towards a causal relationship in this direction. However, whether cognitive function or dementia may also cause problematic sleep duration remains unclear. Methods: We conducted summary-level Mendelian Randomisation (MR) analyses to estimate the causal association between general cognitive function, 'g' (177 SNPs), reaction time (44 SNPs), Alzheimer's disease (AD) (29 SNPs), and self-reported and objective sleep duration. Sensitivity analyses included: MR-Egger, Weighted median estimator and leave-one-out analyses. We used data from recently published cognitive function, AD and sleep duration genome wide association studies. Results: MR results showed that AD was associated with longer, (Beta=0.14, 95% CI=0.04;0.24), whilst 'g', and reaction time were associated with shorter (Beta=-0.06, 95% CI=-0.11;-0.01 and Beta=-0.15, 95% CI=-0.29;-0.01, respectively), objective sleep duration. No association was observed between our exposures and self-reported sleep duration. Interpretation: These results suggest a causative relationship between AD, 'g', reaction time and objective sleep duration, where AD is associated with longer sleep duration and 'g' and reaction time are associated with shorter sleep. This study furthers our understanding of the relationship between brain health and sleep duration and sheds light on the causal nature of these associations.

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Comparative analysis of mammal genomes unveils key genomic variability for human lifespan

10.1101/2021.02.09.430384 ◽

2021 ◽

Author(s):

X. Farré ◽

R. Molina ◽

F. Barteri ◽

P.R.H.J. Timmers ◽

P.K. Joshi ◽

...

Keyword(s):

Amino Acids ◽

Amino Acid ◽

Comparative Genomics ◽

Protein Evolution ◽

Association Studies ◽

Human Populations ◽

Genome Wide Association Studies ◽

Maximum Lifespan ◽

Mammal Species ◽

Human Lifespan

AbstractMammals vary 100-fold in their maximum lifespan. This enormous variation is the result of the adaptations of each species to their own biological trade-offs and ecological conditions. Comparative genomics studies have demonstrated that the genomic factors underlying the lifespans of species and the longevity of individuals are shared across the tree of life. Here, we set out to compare protein-coding regions across the mammalian phylogeny, aiming to detect individual amino acid changes shared by the most long-lived mammal species and genes whose rates of protein evolution correlate with longevity. We discovered a total of 2,737 amino acid changes in 2,004 genes that distinguish long- and short-lived mammals, significantly more than expected by chance (p=0.003). The detected genes belong to pathways involved in regulating lifespan, such as inflammatory response and hemostasis. Among them, a total 1,157 amino acids, located in 996 different genes, showed a significant association with maximum lifespan in a phylogenetically controlled test. Interestingly, most of the detected amino acids positions do not vary in extant human populations (>81.2%) or have allele frequencies below 1% (99.78%), Consequently, almost none could have been detected by Genome-Wide Association Studies (GWAS). Additionally, we identified four more genes whose rate of protein evolution correlated with longevity in mammals. Crucially, SNPs located in the detected genes explain a larger fraction of human lifespan heritability than expected by chance, successfully demonstrating for the first time that comparative genomics can be used to enhance the interpretation of human GWAS. Finally, we show that the human longevity-associated proteins coded by the detected genes are significantly more stable than the orthologous proteins from short-lived mammals, strongly suggesting that general protein stability is linked to increased lifespan.

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Depression and Osteoporosis: A Mendelian Randomization Study

Calcified Tissue International ◽

10.1007/s00223-021-00886-5 ◽

2021 ◽

Author(s):

Bin He ◽

Qiong Lyu ◽

Lifeng Yin ◽

Muzi Zhang ◽

Zhengxue Quan ◽

...

Keyword(s):

Observational Studies ◽

Mendelian Randomization ◽

Causal Effect ◽

Association Studies ◽

Meta Analysis ◽

Sensitivity Analyses ◽

European Ancestry ◽

Genome Wide Association Studies ◽

Reverse Causality ◽

Mineral Density

AbstractObservational studies suggest a link between depression and osteoporosis, but these may be subject to confounding and reverse causality. In this two-sample Mendelian randomization analysis, we included the large meta-analysis of genome-wide association studies for depression among 807,553 individuals (246,363 cases and 561,190 controls) of European descent, the large meta-analysis to identify genetic variants associated with femoral neck bone mineral density (FN-BMD), forearm BMD (FA-BMD) and lumbar spine BMD (LS-BMD) among 53,236 individuals of European ancestry, and the GWAS summary data of heel BMD (HE-BMD) and fracture among 426,824 individuals of European ancestry. The results revealed that genetic predisposition towards depression showed no causal effect on FA-BMD (beta-estimate: 0.091, 95% confidence interval [CI] − 0.088 to 0.269, SE:0.091, P value = 0.320), FN-BMD (beta-estimate: 0.066, 95% CI − 0.016 to 0.148, SE:0.042, P value = 0.113), LS-BMD (beta-estimate: 0.074, 95% CI − 0.029 to 0.177, SE:0.052, P value = 0.159), HE-BMD (beta-estimate: 0.009, 95% CI − 0.043 to 0.061, SE:0.027, P value = 0.727), or fracture (beta-estimate: 0.008, 95% CI − 0.071 to 0.087, SE:0.041, P value = 0.844). These results were also confirmed by multiple sensitivity analyses. Contrary to the findings of observational studies, our results do not reveal a causal role of depression in osteoporosis or fracture.

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