Modifiable lifestyle factors and severe COVID-19 risk: a Mendelian randomisation study

Abstract Background Lifestyle factors including obesity and smoking are suggested to be correlated with increased risk of COVID-19 severe illness or related death. However, whether these relationships are causal is not well known; neither for the relationships between COVID-19 severe illness and other common lifestyle factors, such as physical activity and alcohol consumption. Methods Genome-wide significant genetic variants associated with body mass index (BMI), lifetime smoking, physical activity and alcohol consumption identified by large-scale genome-wide association studies (GWAS) of up to 941,280 individuals were selected as instrumental variables. Summary statistics of the genetic variants on severe illness of COVID-19 were obtained from GWAS analyses of up to 6492 cases and 1,012,809 controls. Two-sample Mendelian randomisation analyses were conducted. Results Both per-standard deviation (SD) increase in genetically predicted BMI and lifetime smoking were associated with about two-fold increased risks of severe respiratory COVID-19 and COVID-19 hospitalization (all P < 0.05). Per-SD increase in genetically predicted physical activity was associated with decreased risks of severe respiratory COVID-19 (odds ratio [OR] = 0.19; 95% confidence interval [CI], 0.05, 0.74; P = 0.02), but not with COVID-19 hospitalization (OR = 0.44; 95% CI 0.18, 1.07; P = 0.07). No evidence of association was found for genetically predicted alcohol consumption. Similar results were found across robust Mendelian randomisation methods. Conclusions Evidence is found that BMI and smoking causally increase and physical activity might causally decrease the risk of COVID-19 severe illness. This study highlights the importance of maintaining a healthy lifestyle in protecting from COVID-19 severe illness and its public health value in fighting against COVID-19 pandemic.

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Modifiable lifestyle factors and severe COVID-19 risk: Evidence from Mendelian randomization analysis

10.1101/2020.10.19.20215525 ◽

2020 ◽

Author(s):

Shuai Li

Keyword(s):

Physical Activity ◽

Alcohol Consumption ◽

Genetic Variants ◽

Mendelian Randomization ◽

Association Studies ◽

Lifestyle Factors ◽

Severe Illness ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Increased Risk

AbstractBackgroundLifestyle factors including obesity and smoking are suggested to be related to increased risk of COVID-19 severe illness or related death. However, little is known about whether these relationships are causal, or the relationships between COVID-19 severe illness and other lifestyle factors, such as alcohol consumption and physical activity.MethodsGenome-wide significant genetic variants associated with body mass index (BMI), lifetime smoking, alcohol consumption and physical activity identified by large-scale genome-wide association studies (GWAS) were selected as instrumental variables. GWAS summary statistics of these genetic variants for relevant lifestyle factors and severe illness of COVID-19 were obtained. Two-sample Mendelian randomization (MR) analyses were conducted.ResultsBoth genetically predicted BMI and lifetime smoking were associated with about 2-fold increased risks of severe respiratory COVID-19 and COVID-19 hospitalization (all P<0.05). Genetically predicted physical activity was associated with about 5-fold (95% confidence interval [CI], 1.4, 20.3; P=0.02) decreased risk of severe respiratory COVID-19, but not with COVID-19 hospitalization, though the majority of the 95% CI did not include one. No evidence of association was found for genetically predicted alcohol consumption, but associations were found when using pleiotropy robust methods.ConclusionEvidence is found that BMI and smoking causally increase and physical activity causally decreases the risk of COVID-19 severe illness. This study highlights the importance of maintaining a healthy lifestyle in protecting from COVID-19 severe illness and its public health value in fighting against COVID-19 pandemic.

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Body size and composition and site-specific cancers in UK Biobank: a Mendelian randomisation study

10.1101/2020.02.28.970459 ◽

2020 ◽

Cited By ~ 1

Author(s):

Mathew Vithayathil ◽

Paul Carter ◽

Siddhartha Kar ◽

Amy M. Mason ◽

Stephen Burgess ◽

...

Keyword(s):

Instrumental Variables ◽

Association Studies ◽

Genome Wide Association ◽

Mendelian Randomisation ◽

Genome Wide Association Studies ◽

Uk Biobank ◽

Site Specific ◽

Genome Wide ◽

Increased Risk ◽

The Uk

ABSTRACTObjectivesTo investigate the casual role of body mass index, body fat composition and height in cancer.DesignTwo stage mendelian randomisation studySettingPrevious genome wide association studies and the UK BiobankParticipantsGenetic instrumental variables for body mass index (BMI), fat mass index (FMI), fat free mass index (FFMI) and height from previous genome wide association studies and UK Biobank. Cancer outcomes from 367 586 participants of European descent from the UK Biobank.Main outcome measuresOverall cancer risk and 22 site-specific cancers risk for genetic instrumental variables for BMI, FMI, FFMI and height.ResultsGenetically predicted BMI (per 1 kg/m2) was not associated with overall cancer risk (OR 0.99; 95% confidence interval (CI) 0-98-1.00, p=0.105). Elevated BMI was associated with increased risk of stomach cancer (OR 1.15, 95% (CI) 1.05-1.26; p=0.003) and melanoma (OR 0.96, 95% CI 0.92-1.00; p=0.044). For sex-specific cancers, BMI was positively associated with uterine cancer (OR 1.08, 95% CI 1.01-1.14; p=0.015) but inversely associated with breast (OR 0.95, 95% CI 0.92-0.98; p=0.001), prostate (OR 0.95, 95% CI 0.92-0.99; p=0.007) and testicular cancer (OR 0.89, 95% CI 0.81-0.98; p=0.017). Elevated FMI (per 1 kg/m2) was associated with gastrointestinal cancer (stomach cancer OR 4.23, 95% CI 1.18-15.13, p=0.027; colorectal cancer OR 1.94, 95% CI 1.23-3.07; p=0.004). Increased height (per 1 standard deviation, approximately 6.5cm) was associated with increased risk of overall cancer (OR 1.06; 95% 1.04-1.09; p = 2.97×10-8) and most site-specific cancers with the strongest estimates for kidney, non-Hodgkin lymphoma, colorectal, lung, melanoma and breast cancer.ConclusionsThere is little evidence for BMI as a casual risk factor for cancer. BMI may have a causal role for sex-specific cancers, although with inconsistent directions of effect, and FMI for gastrointestinal malignancies. Elevated height is a risk factor for overall cancer and multiple site cancers.

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Evidence of shared genetic influences underlying schizophrenia and alcohol use disorder, but not alcohol consumption

10.1101/2020.10.27.20220186 ◽

2020 ◽

Author(s):

Emma C. Johnson ◽

Manav Kapoor ◽

Alexander S. Hatoum ◽

Hang Zhou ◽

Renato Polimanti ◽

...

Keyword(s):

Alcohol Consumption ◽

Alcohol Use ◽

Genetic Variants ◽

Alcohol Use Disorder ◽

Association Studies ◽

Genetic Correlations ◽

Genome Wide Association Studies ◽

Genetic Covariance ◽

Genome Wide ◽

Brain Tissues

AbstractBackgroundAlcohol use disorder (AUD) and schizophrenia (SCZ) frequently co-occur, and recent genome-wide association studies (GWAS) have identified significant genetic correlations between them. In parallel, mounting evidence from GWAS suggests that alcohol consumption is only weakly genetically correlated with SCZ, but this has not yet been systematically investigated.MethodsWe used the largest published GWAS for AUD (total cases = 77,822) and SCZ (total cases = 46,827) to systematically identify genetic variants that influence both disorders (in either the same or opposite direction of effect) as well as disorder-specific loci, and contrast our findings with GWAS data for drinks per week (DPW; N = 537,349) as a measure of alcohol consumption.ResultsWe identified 55 independent genome-wide significant SNPs with the same direction of effect on AUD and SCZ, 9 with robust opposite effects, and 99 with disorder-specific effects. We also found evidence for 12 genes whose pleiotropic associations with AUD and SCZ are consistent with mediation via gene expression in the prefrontal cortex. The genetic covariance between AUD and SCZ was concentrated in genomic regions functional in brain tissues (p = 0.001). The genetic correlation between DPW and SCZ (rg = 0.102, SE = 0.022) was significantly lower than that for AUD and SCZ (rg = 0.392, SE = 0.029; p-value of the difference = 9.3e-18), and the genetic covariance between DPW and SCZ was not enriched for any meaningful tissue-specific categories.ConclusionsOur findings provide a detailed view of genetic loci that influence risk of both AUD and SCZ, suggest that biological commonalities underlying genetic variants with an effect on both disorders are manifested in brain tissues, and provide further evidence that SCZ shares meaningful genetic overlap with AUD and not merely alcohol consumption.

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Genetic liability to insomnia in relation to cardiovascular diseases: a Mendelian randomisation study

European Journal of Epidemiology ◽

10.1007/s10654-021-00737-5 ◽

2021 ◽

Author(s):

Shuai Yuan ◽

Amy M. Mason ◽

Stephen Burgess ◽

Susanna C. Larsson

Keyword(s):

Cardiovascular Diseases ◽

Association Studies ◽

European Ancestry ◽

Mendelian Randomisation ◽

Genome Wide Association Studies ◽

Uk Biobank ◽

Genetic Liability ◽

Genome Wide ◽

Increased Risk ◽

The Uk

AbstractThe present study aimed to determine the associations between insomnia and cardiovascular diseases (CVDs) using Mendelian randomisation (MR) analysis. As instrumental variables, we used 208 independent single-nucleotide polymorphisms associated with insomnia at the genome-wide significance threshold in a meta-analysis of genome-wide association studies in the UK Biobank and 23andMe including a total of 397 959 self-reported insomnia cases and 933 057 non-cases. Summary-level data for nine CVDs were obtained from the UK Biobank including 367 586 individuals of European ancestry. After correction for multiple testing, genetic liability to insomnia was associated with higher odds of six CVDs, including peripheral arterial disease (odd ratio (OR) 1.22; 95% confidence interval (CI), 1.21, 1.33), heart failure (OR 1.21; 95% CI, 1.13, 1.30), coronary artery disease (OR 1.19; 95% CI, 1.14, 1.25), ischaemic stroke (OR 1.15; 95% CI, 1.06, 1.25), venous thromboembolism (OR 1.13; 95% CI, 1.07, 1.19) and atrial fibrillation (OR 1.10; 95% CI, 1.05, 1.15). There were suggestive associations for aortic valve stenosis (OR, 1.17; 95% CI, 1.04, 1.32) and haemorrhagic stroke (OR 1.14; 95% CI, 1.00, 1.29) but no association for abdominal aortic aneurysm (OR, 1.14, 95% CI, 0.98, 1.33). The patterns of associations remained with mild attenuation in multivariable MR analyses adjusting for genetically correlated phenotypes and potential mediators, including sleep duration, depression, body mass index, type 2 diabetes and smoking. The present MR study suggests potential causal associations of genetic liability to insomnia with increased risk of a broad range of CVDs.

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A multivariable Mendelian randomisation study exploring the direct effects of nicotine on health compared with the other constituents of tobacco smoke: Implications for e-cigarette use

10.1101/2021.01.12.21249493 ◽

2021 ◽

Author(s):

Jasmine N Khouja ◽

Eleanor Sanderson ◽

Robyn E Wootton ◽

Amy E Taylor ◽

Marcus R Munafò

Keyword(s):

Heart Rate ◽

Tobacco Smoke ◽

Association Studies ◽

Mendelian Randomisation ◽

Genome Wide Association Studies ◽

Direct Effects ◽

Uk Biobank ◽

Genome Wide ◽

Increased Risk ◽

Summary Data

AbstractObjectivesGiven the popularity of e-cigarettes, and the lack of longitudinal evidence regarding their safety, novel methods are required to explore potential health effects resulting directly from nicotine use. The aim of this study was to explore the direct effects of nicotine compared with the other constituents of tobacco smoke on health outcomes associated with smoking.DesignObservational study, using Mendelian randomisation and multivariable Mendelian randomisation analyses of summary data.SettingSummary data from two previous genome-wide association studies, and summary data generated from UK Biobank, a prospective cohort study.ParticipantsN = 337,010 individuals enrolled in UK Biobank, and a total of N = 341,882 individuals from two previous genome-wide association studies.Main outcome measuresWe explored the effect of cotinine levels (as a proxy for nicotine exposure) and smoking heaviness (to capture cigarette smoke exposure) on body mass index (BMI), chronic obstructive pulmonary disease (COPD), forced vital capacity (FVC), forced expiratory volume (FEV-1), coronary heart disease (CHD), and heart rate.ResultsIn multivariable Mendelian randomisation analyses, there was weak evidence to suggest that increased cotinine levels may cause increased heart rate among current smokers (β = 0.50 bpm, 95% CI −0.06 to 1.05). There was stronger evidence to suggest that increased smoking heaviness causes decreased BMI among current smokers (β = −1.81 kg/m2, 95% CI −2.64 to −0.98), as well as increased risk of COPD, decreased FEV-1 and FVC, and increased heart rate among ever and current smokers. We also found evidence to suggest that increased smoking heaviness causes increased risk of CHD among ever smokers.ConclusionsOur combined findings are consistent with smoking-related health outcomes being caused by exposure to the non-nicotine components of tobacco smoke.

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A Genome-Wide Association Study of spontaneous preterm birth in a European population

F1000Research ◽

10.12688/f1000research.2-255.v1 ◽

2013 ◽

Vol 2 ◽

pp. 255 ◽

Cited By ~ 3

Author(s):

Wilfred Wu ◽

Erin A S Clark ◽

Tracy A Manuck ◽

M Sean Esplin ◽

Michael W Varner ◽

...

Keyword(s):

Preterm Birth ◽

Genetic Variants ◽

Association Studies ◽

European Population ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Spontaneous Preterm Birth ◽

Genome Wide ◽

A Genome ◽

Increased Risk

Background: Preterm birth is defined as a birth prior to 37 completed weeks’ gestation. It affects more than 10% of all births worldwide, and is the leading cause of neonatal mortality in non-anomalous newborns. Even if the preterm newborn survives, there is an increased risk of lifelong morbidity. Despite the magnitude of this public health problem, the etiology of spontaneous preterm birth is not well understood. Previous studies suggest that genetics is an important contributing factor. We therefore employed a genome-wide association approach to explore possible fetal genetic variants that may be associated with spontaneous preterm birth.Methods: We obtained preterm birth phenotype and genotype data from the National Center for Biotechnology Information Genotypes and Phenotypes Database (study accession phs000103.v1.p1). This dataset contains participants collected by the Danish National Birth Cohort and includes 1000 preterm births and 1000 term births as controls. Whole genomes were genotyped on the Illumina Human660W-Quad_v1_A platform, which contains more than 500,000 markers. After data quality control, we performed genome-wide association studies for the 22 autosomal chromosomes.Results: No single nucleotide polymorphism reached genome-wide significance after Bonferroni correction for multiple testing.Conclusion: We found no evidence of genetic association with spontaneous preterm birth in this European population. Approaches that facilitate detection of both common and rare genetic variants, such as evaluation of high-risk pedigrees and genome sequencing, may be more successful in identifying genes associated with spontaneous preterm birth.

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Migraine: Genetic Variants and Clinical Phenotypes

Current Medicinal Chemistry ◽

10.2174/0929867325666180719120215 ◽

2019 ◽

Vol 26 (34) ◽

pp. 6207-6221 ◽

Cited By ~ 1

Author(s):

Innocenzo Rainero ◽

Alessandro Vacca ◽

Flora Govone ◽

Annalisa Gai ◽

Lorenzo Pinessi ◽

...

Keyword(s):

Genetic Variants ◽

Association Studies ◽

Mthfr Gene ◽

Genome Wide Association Studies ◽

Clinical Phenotypes ◽

Network Analyses ◽

Genome Wide ◽

Genomic Studies ◽

The Common ◽

The Relationship

Migraine is a common, chronic neurovascular disorder caused by a complex interaction between genetic and environmental risk factors. In the last two decades, molecular genetics of migraine have been intensively investigated. In a few cases, migraine is transmitted as a monogenic disorder, and the disease phenotype cosegregates with mutations in different genes like CACNA1A, ATP1A2, SCN1A, KCNK18, and NOTCH3. In the common forms of migraine, candidate genes as well as genome-wide association studies have shown that a large number of genetic variants may increase the risk of developing migraine. At present, few studies investigated the genotype-phenotype correlation in patients with migraine. The purpose of this review was to discuss recent studies investigating the relationship between different genetic variants and the clinical characteristics of migraine. Analysis of genotype-phenotype correlations in migraineurs is complicated by several confounding factors and, to date, only polymorphisms of the MTHFR gene have been shown to have an effect on migraine phenotype. Additional genomic studies and network analyses are needed to clarify the complex pathways underlying migraine and its clinical phenotypes.

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Editing GWAS: experimental approaches to dissect and exploit disease-associated genetic variation

Genome Medicine ◽

10.1186/s13073-021-00857-3 ◽

2021 ◽

Vol 13 (1) ◽

Author(s):

Shuquan Rao ◽

Yao Yao ◽

Daniel E. Bauer

Keyword(s):

Genome Editing ◽

Genetic Variants ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Functional Studies ◽

Functional Genetics ◽

Genome Wide ◽

Causal Variants ◽

Experimental Approaches

AbstractGenome-wide association studies (GWAS) have uncovered thousands of genetic variants that influence risk for human diseases and traits. Yet understanding the mechanisms by which these genetic variants, mainly noncoding, have an impact on associated diseases and traits remains a significant hurdle. In this review, we discuss emerging experimental approaches that are being applied for functional studies of causal variants and translational advances from GWAS findings to disease prevention and treatment. We highlight the use of genome editing technologies in GWAS functional studies to modify genomic sequences, with proof-of-principle examples. We discuss the challenges in interrogating causal variants, points for consideration in experimental design and interpretation of GWAS locus mechanisms, and the potential for novel therapeutic opportunities. With the accumulation of knowledge of functional genetics, therapeutic genome editing based on GWAS discoveries will become increasingly feasible.

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The Genetic Basis of Hypertriglyceridemia

Current Atherosclerosis Reports ◽

10.1007/s11883-021-00939-y ◽

2021 ◽

Vol 23 (8) ◽

Author(s):

Germán D. Carrasquilla ◽

Malene Revsbech Christiansen ◽

Tuomas O. Kilpeläinen

Keyword(s):

Genetic Basis ◽

Association Studies ◽

Cumulative Effect ◽

Genome Wide Association Studies ◽

Genetic Loci ◽

Risk Variants ◽

Genome Wide ◽

Severe Hypertriglyceridemia ◽

Increased Risk ◽

Polygenic Scores

Abstract Purpose of Review Hypertriglyceridemia is a common dyslipidemia associated with an increased risk of cardiovascular disease and pancreatitis. Severe hypertriglyceridemia may sometimes be a monogenic condition. However, in the vast majority of patients, hypertriglyceridemia is due to the cumulative effect of multiple genetic risk variants along with lifestyle factors, medications, and disease conditions that elevate triglyceride levels. In this review, we will summarize recent progress in the understanding of the genetic basis of hypertriglyceridemia. Recent Findings More than 300 genetic loci have been identified for association with triglyceride levels in large genome-wide association studies. Studies combining the loci into polygenic scores have demonstrated that some hypertriglyceridemia phenotypes previously attributed to monogenic inheritance have a polygenic basis. The new genetic discoveries have opened avenues for the development of more effective triglyceride-lowering treatments and raised interest towards genetic screening and tailored treatments against hypertriglyceridemia. Summary The discovery of multiple genetic loci associated with elevated triglyceride levels has led to improved understanding of the genetic basis of hypertriglyceridemia and opened new translational opportunities.

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Transcriptome-wide Mendelian randomization study prioritising novel tissue-dependent genes for glioma susceptibility

Scientific Reports ◽

10.1038/s41598-021-82169-5 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Jamie W. Robinson ◽

Richard M. Martin ◽

Spiridon Tsavachidis ◽

Amy E. Howell ◽

Caroline L. Relton ◽

...

Keyword(s):

Gene Expression ◽

Association Studies ◽

Tissue Expression ◽

Tissue Type ◽

Mendelian Randomisation ◽

Genome Wide Association Studies ◽

Causal Pathways ◽

Genome Wide ◽

Glioma Risk ◽

Brain Tissues

AbstractGenome-wide association studies (GWAS) have discovered 27 loci associated with glioma risk. Whether these loci are causally implicated in glioma risk, and how risk differs across tissues, has yet to be systematically explored. We integrated multi-tissue expression quantitative trait loci (eQTLs) and glioma GWAS data using a combined Mendelian randomisation (MR) and colocalisation approach. We investigated how genetically predicted gene expression affects risk across tissue type (brain, estimated effective n = 1194 and whole blood, n = 31,684) and glioma subtype (all glioma (7400 cases, 8257 controls) glioblastoma (GBM, 3112 cases) and non-GBM gliomas (2411 cases)). We also leveraged tissue-specific eQTLs collected from 13 brain tissues (n = 114 to 209). The MR and colocalisation results suggested that genetically predicted increased gene expression of 12 genes were associated with glioma, GBM and/or non-GBM risk, three of which are novel glioma susceptibility genes (RETREG2/FAM134A, FAM178B and MVB12B/FAM125B). The effect of gene expression appears to be relatively consistent across glioma subtype diagnoses. Examining how risk differed across 13 brain tissues highlighted five candidate tissues (cerebellum, cortex, and the putamen, nucleus accumbens and caudate basal ganglia) and four previously implicated genes (JAK1, STMN3, PICK1 and EGFR). These analyses identified robust causal evidence for 12 genes and glioma risk, three of which are novel. The correlation of MR estimates in brain and blood are consistently low which suggested that tissue specificity needs to be carefully considered for glioma. Our results have implicated genes yet to be associated with glioma susceptibility and provided insight into putatively causal pathways for glioma risk.

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