Causal Association between Periodontal Diseases and Cardiovascular Diseases

Observational studies have revealed that dental diseases such as periodontitis and dental caries increase the risk of cardiovascular diseases (CVDs). However, the causality between periodontal disease (PD) and CVDs is still not clarified. In the present study, two-sample Mendelian randomization (MR) studies were carried out to assess the association between genetic liability for periodontal diseases (dental caries and periodontitis) and major CVDs, including coronary artery disease (CAD), heart failure (HF), atrial fibrillation (AF), and stroke—including ischemic stroke as well as its three main subtypes—based on large-scale genome-wide association studies (GWASs). Our two-sample MR analyses did not provide evidence for dental caries and periodontitis as the causes of cardiovascular diseases; sensitivity analyses, including MR–Egger analysis and weighted median analysis, also supported this result. Gene functional annotation and pathway enrichment analyses indicated the common pathophysiology between cardiovascular diseases and periodontal diseases. The associations from observational studies may be explained by shared risk factors and comorbidities instead of direct consequences. This also suggests that addressing the common risk factors—such as reducing obesity and improving glucose tolerance—could benefit both conditions.

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Association of genetically predicted blood sucrose with coronary heart disease and its risk factors in Mendelian randomization

Scientific Reports ◽

10.1038/s41598-020-78685-5 ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Ting Zhang ◽

Shiu Lun Au Yeung ◽

C. Mary Schooling

Keyword(s):

Risk Factors ◽

Coronary Heart Disease ◽

Heart Disease ◽

Dental Caries ◽

Multiple Testing ◽

Mendelian Randomization ◽

Association Studies ◽

Sensitivity Analyses ◽

Genome Wide Association Studies ◽

Standard Deviation Increase

AbstractWe assessed the associations of genetically instrumented blood sucrose with risk of coronary heart disease (CHD) and its risk factors (i.e., type 2 diabetes, adiposity, blood pressure, lipids, and glycaemic traits), using two-sample Mendelian randomization. We used blood fructose as a validation exposure. Dental caries was a positive control outcome. We selected genetic variants strongly (P < 5 × 10–6) associated with blood sucrose or fructose as instrumental variables and applied them to summary statistics from the largest available genome-wide association studies of the outcomes. Inverse-variance weighting was used as main analysis. Sensitivity analyses included weighted median, MR-Egger and MR-PRESSO. Genetically higher blood sucrose was positively associated with the control outcome, dental caries (odds ratio [OR] 1.04 per log10 transformed effect size [median-normalized standard deviation] increase, 95% confidence interval [CI] 1.002–1.08, P = 0.04), but this association did not withstand allowing for multiple testing. The estimate for blood fructose was in the same direction. Genetically instrumented blood sucrose was not clearly associated with CHD (OR 1.01, 95% CI 0.997–1.02, P = 0.14), nor with its risk factors. Findings were similar for blood fructose. Our study found some evidence of the expected detrimental effect of sucrose on dental caries but no effect on CHD. Given a small effect on CHD cannot be excluded, further investigation with stronger genetic predictors is required.

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Lung function, COPD and cognitive function: a multivariable and two sample Mendelian randomization study

BMC Pulmonary Medicine ◽

10.1186/s12890-021-01611-6 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Daniel H. Higbee ◽

Raquel Granell ◽

Gibran Hemani ◽

George Davey Smith ◽

James W. Dodd

Keyword(s):

Risk Factors ◽

Cognitive Function ◽

Lung Function ◽

Observational Studies ◽

Mendelian Randomization ◽

Association Studies ◽

Limited Attention ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Shared Risk

Abstract Background Observational studies show an association between reduced lung function and impaired cognition. Cognitive dysfunction influences important health outcomes and is a precursor to dementia, but treatments options are currently very limited. Attention has therefore focused on identifying modifiable risk factors to prevent cognitive decline and preserve cognition. Our objective was to determine if lung function or risk of COPD causes reduced cognitive function using Mendelian randomization (MR). Methods Single nucleotide polymorphisms from genome wide association studies of lung function and COPD were used as exposures. We examined their effect on general cognitive function in a sample of 132,452 individuals. We then performed multivariable MR (MVMR), examining the effect of lung function before and after conditioning for covariates. Results We found only weak evidence that reduced lung function (Beta − 0.002 (SE 0.02), p-value 0.86) or increased liability to COPD (− 0.008 (0.008), p-value 0.35) causes lower cognitive function. MVMR found both reduced FEV1 and FVC do cause lower cognitive function, but that after conditioning for height (− 0.03 (0.03), p-value 0.29 and − 0.01 (0.03) p-value 0.62, for FEV1 and FVC respectively) and educational attainment (− 0.03 (0.03) p-value 0.33 and − 0.01 (0.02), p-value 0.35) the evidence became weak. Conclusion We did not find evidence that reduced lung function or COPD causes reduced cognitive function. Previous observational studies are probably affected by residual confounding. Research efforts should focus on shared risk factors for reduced lung function and cognition, rather than lung function alone as a modifiable risk factor.

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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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Identification and Analysis of Shared Risk Factors in Sepsis and High Mortality Risk COVID-19 Patients

10.1101/2020.05.05.20091918 ◽

2020 ◽

Cited By ~ 1

Author(s):

Sayoni Das ◽

Krystyna Taylor ◽

Matthew Pearson ◽

James Kozubek ◽

Marcin Pawlowski ◽

...

Keyword(s):

Risk Factors ◽

Disease Severity ◽

Association Studies ◽

Severe Disease ◽

Drug Repurposing ◽

Genome Wide Association Studies ◽

Uk Biobank ◽

Life Threatening ◽

Shared Risk ◽

The Impact

ABSTRACTBACKGROUNDCoronavirus disease 2019 (COVID-19) is a novel coronavirus strain disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The disease is highly transmissible and severe disease including viral sepsis has been reported in up to 16% of hospitalized cases. The admission characteristics associated with increased odds of hospital mortality among confirmed cases of COVID-19 include severe hypoxia, low platelet count, elevated bilirubin, hypoalbuminemia and reduced glomerular filtration rate. These symptoms correlate highly with severe sepsis cases. The diseases also share similar comorbidity risks including dementia, type 2 diabetes mellitus, coronary heart disease, hypertension and chronic renal failure. Sepsis has been observed in up to 59% of hospitalized COVID-19 patients.It is highly desirable to identify risk factors and novel therapy/drug repurposing avenues for late-stage severe COVID-19 patients. This would enable better protection of at-risk populations and clinical stratification of COVID-19 patients according to their risk for developing life threatening disease.METHODSAs there is currently insufficient data available for confirmed COVID-19 patients correlating their genomic profile, disease severity and outcome, co-morbidities and treatments as well as epidemiological risk factors (such as ethnicity, blood group, smoking, BMI etc.), a direct study of the impact of host genomics on disease severity and outcomes is not yet possible. We therefore ran a study on the UK Biobank sepsis cohort as a surrogate to identify sepsis associated signatures and genes, and correlated these with COVID-19 patients.Sepsis is itself a life-threatening inflammatory health condition with a mortality rate of approximately 20%. Like the initial studies for COVID-19 patients, standard genome wide association studies (GWAS) have previously failed to identify more than a handful of genetic variants that predispose individuals to developing sepsis.RESULTSWe used a combinatorial association approach to analyze a sepsis population derived from UK Biobank. We identified 70 sepsis risk-associated genes, which provide insights into the disease mechanisms underlying sepsis pathogenesis. Many of these targets can be grouped by common mechanisms of action such as endothelial cell dysfunction, PI3K/mTOR pathway signaling, immune response regulation, aberrant GABA and neurogenic signaling.CONCLUSIONThis study has identified 70 sepsis related genes, many of them for the first time, that can reasonably be considered to be potentially relevant to severe COVID-19 patients. We have further identified 59 drug repurposing candidates for 13 of these targets that can be used for the development of novel therapeutic strategies to increase the survival rate of patients who develop sepsis and potentially severe COVID-19.

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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

Translational Psychiatry ◽

10.1038/s41398-021-01325-7 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Jurjen J. Luykx ◽

Bochao D. Lin

Keyword(s):

Bipolar Disorder ◽

Psychiatric Disorders ◽

Observational Studies ◽

Mendelian Randomization ◽

Association Studies ◽

Neuropsychiatric Disorders ◽

Sensitivity Analyses ◽

Genome Wide Association Studies ◽

Genetic Liability ◽

Bidirectional Associations

AbstractObservational studies have suggested bidirectional associations between psychiatric disorders and COVID-19 phenotypes, but results of such studies are inconsistent. Mendelian Randomization (MR) may overcome the limitations of observational studies, e.g., unmeasured confounding and uncertainties about cause and effect. We aimed to elucidate associations between neuropsychiatric disorders and COVID-19 susceptibility and severity. To that end, 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 in January 2021). In single-variable Generalized Summary MR analysis, the most significant and only Bonferroni-corrected significant result was found for genetic liability to BIP-SCZ (a combined GWAS of bipolar disorder and schizophrenia as cases vs. controls) increasing risk of COVID-19 (OR = 1.17, 95% CI, 1.06–1.28). However, we found a significant, positive genetic correlation between BIP-SCZ and COVID-19 of 0.295 and could not confirm causal or horizontally pleiotropic effects using another method. No genetic liabilities to COVID-19 phenotypes increased the risk of (neuro)psychiatric disorders. In multivariable MR using both neuropsychiatric and a range of other phenotypes, only genetic instruments of BMI remained causally associated with COVID-19. All sensitivity analyses confirmed the results. In conclusion, while genetic liability to bipolar disorder and schizophrenia combined slightly increased COVID-19 susceptibility in one univariable analysis, other MR and multivariable analyses could only confirm genetic underpinnings of BMI to be causally implicated in COVID-19 susceptibility. Thus, using MR we found no consistent proof of genetic liabilities to (neuro)psychiatric disorders contributing to COVID-19 liability or vice versa, which is in line with at least two observational studies. Previously reported positive associations between psychiatric disorders and COVID-19 by others may have resulted from statistical models incompletely capturing BMI as a continuous covariate.

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Genomewide Association Studies in Cardiovascular Disease—An Update 2011

Clinical Chemistry ◽

10.1373/clinchem.2011.170431 ◽

2012 ◽

Vol 58 (1) ◽

pp. 92-103 ◽

Cited By ~ 47

Author(s):

Tanja Zeller ◽

Stefan Blankenberg ◽

Patrick Diemert

Keyword(s):

Risk Factors ◽

Cardiovascular Diseases ◽

Genetic Risk ◽

Association Studies ◽

Genetic Risk Factors ◽

Genome Wide Association Studies ◽

Search Terms ◽

Genome Wide ◽

Pubmed Search ◽

Genomewide Association

Abstract BACKGROUND Genomewide association studies have led to an enormous boost in the identification of susceptibility genes for cardiovascular diseases. This review aims to summarize the most important findings of recent years. CONTENT We have carefully reviewed the current literature (PubMed search terms: “genome wide association studies,” “genetic polymorphism,” “genetic risk factors,” “association study” in connection with the respective diseases, “risk score,” “transcriptome”). SUMMARY Multiple novel genetic loci for such important cardiovascular diseases as myocardial infarction, hypertension, heart failure, stroke, and hyperlipidemia have been identified. Given that many novel genetic risk factors lie within hitherto-unsuspected genes or influence gene expression, these findings have inspired discoveries of biological function. Despite these successes, however, only a fraction of the heritability for most cardiovascular diseases has been explained thus far. Forthcoming techniques such as whole-genome sequencing will be important to close the gap of missing heritability.

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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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Genetic Interactions Effects of Cardiovascular Disorder Using Computational Models: A Review

Current Biotechnology ◽

10.2174/2211550109999201008125800 ◽

2020 ◽

Vol 9 (3) ◽

pp. 177-191

Author(s):

Sridharan Priya ◽

Radha K. Manavalan

Keyword(s):

Coronary Artery Disease ◽

Coronary Artery ◽

Cardiovascular Diseases ◽

Computational Models ◽

Genetic Interaction ◽

Association Studies ◽

Genetic Interactions ◽

Computational Techniques ◽

Genome Wide Association Studies ◽

Artery Disease

Background: The diseases in the heart and blood vessels such as heart attack, Coronary Artery Disease, Myocardial Infarction (MI), High Blood Pressure, and Obesity, are generally referred to as Cardiovascular Diseases (CVD). The risk factors of CVD include gender, age, cholesterol/ LDL, family history, hypertension, smoking, and genetic and environmental factors. Genome- Wide Association Studies (GWAS) focus on identifying the genetic interactions and genetic architectures of CVD. Objective: Genetic interactions or Epistasis infer the interactions between two or more genes where one gene masks the traits of another gene and increases the susceptibility of CVD. To identify the Epistasis relationship through biological or laboratory methods needs an enormous workforce and more cost. Hence, this paper presents the review of various statistical and Machine learning approaches so far proposed to detect genetic interaction effects for the identification of various Cardiovascular diseases such as Coronary Artery Disease (CAD), MI, Hypertension, HDL and Lipid phenotypes data, and Body Mass Index dataset. Conclusion: This study reveals that various computational models identified the candidate genes such as AGT, PAI-1, ACE, PTPN22, MTHR, FAM107B, ZNF107, PON1, PON2, GTF2E1, ADGRB3, and FTO, which play a major role in genetic interactions for the causes of CVDs. The benefits, limitations, and issues of the various computational techniques for the evolution of epistasis responsible for cardiovascular diseases are exhibited.

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Multitrait genetic association analysis identifies 50 new risk loci for gastro-oesophageal reflux, seven new loci for Barrett’s oesophagus and provides insights into clinical heterogeneity in reflux diagnosis

Gut ◽

10.1136/gutjnl-2020-323906 ◽

2021 ◽

pp. gutjnl-2020-323906

Author(s):

Jue-Sheng Ong ◽

Jiyuan An ◽

Xikun Han ◽

Matthew H Law ◽

Priyanka Nandakumar ◽

...

Keyword(s):

Risk Factors ◽

Multiple Testing ◽

Association Studies ◽

Barrett’S Oesophagus ◽

Oesophageal Reflux ◽

Oesophageal Adenocarcinoma ◽

Specific Gene ◽

Genome Wide Association Studies ◽

Disease Heterogeneity ◽

Barrett's Oesophagus

ObjectiveGastro-oesophageal reflux disease (GERD) has heterogeneous aetiology primarily attributable to its symptom-based definitions. GERD genome-wide association studies (GWASs) have shown strong genetic overlaps with established risk factors such as obesity and depression. We hypothesised that the shared genetic architecture between GERD and these risk factors can be leveraged to (1) identify new GERD and Barrett’s oesophagus (BE) risk loci and (2) explore potentially heterogeneous pathways leading to GERD and oesophageal complications.DesignWe applied multitrait GWAS models combining GERD (78 707 cases; 288 734 controls) and genetically correlated traits including education attainment, depression and body mass index. We also used multitrait analysis to identify BE risk loci. Top hits were replicated in 23andMe (462 753 GERD cases, 24 099 BE cases, 1 484 025 controls). We additionally dissected the GERD loci into obesity-driven and depression-driven subgroups. These subgroups were investigated to determine how they relate to tissue-specific gene expression and to risk of serious oesophageal disease (BE and/or oesophageal adenocarcinoma, EA).ResultsWe identified 88 loci associated with GERD, with 59 replicating in 23andMe after multiple testing corrections. Our BE analysis identified seven novel loci. Additionally we showed that only the obesity-driven GERD loci (but not the depression-driven loci) were associated with genes enriched in oesophageal tissues and successfully predicted BE/EA.ConclusionOur multitrait model identified many novel risk loci for GERD and BE. We present strong evidence for a genetic underpinning of disease heterogeneity in GERD and show that GERD loci associated with depressive symptoms are not strong predictors of BE/EA relative to obesity-driven GERD loci.

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Bias in two-sample Mendelian randomization when using heritable covariable-adjusted summary associations

International Journal of Epidemiology ◽

10.1093/ije/dyaa266 ◽

2021 ◽

Author(s):

Fernando Pires Hartwig ◽

Kate Tilling ◽

George Davey Smith ◽

Deborah A Lawlor ◽

Maria Carolina Borges

Keyword(s):

Waist Circumference ◽

Genetic Variants ◽

Mendelian Randomization ◽

Causal Effect ◽

Association Studies ◽

Real Data ◽

Sensitivity Analyses ◽

Effect Estimate ◽

Genome Wide Association Studies ◽

Residual Confounding

Abstract Background Two-sample Mendelian randomization (MR) allows the use of freely accessible summary association results from genome-wide association studies (GWAS) to estimate causal effects of modifiable exposures on outcomes. Some GWAS adjust for heritable covariables in an attempt to estimate direct effects of genetic variants on the trait of interest. One, both or neither of the exposure GWAS and outcome GWAS may have been adjusted for covariables. Methods We performed a simulation study comprising different scenarios that could motivate covariable adjustment in a GWAS and analysed real data to assess the influence of using covariable-adjusted summary association results in two-sample MR. Results In the absence of residual confounding between exposure and covariable, between exposure and outcome, and between covariable and outcome, using covariable-adjusted summary associations for two-sample MR eliminated bias due to horizontal pleiotropy. However, covariable adjustment led to bias in the presence of residual confounding (especially between the covariable and the outcome), even in the absence of horizontal pleiotropy (when the genetic variants would be valid instruments without covariable adjustment). In an analysis using real data from the Genetic Investigation of ANthropometric Traits (GIANT) consortium and UK Biobank, the causal effect estimate of waist circumference on blood pressure changed direction upon adjustment of waist circumference for body mass index. Conclusions Our findings indicate that using covariable-adjusted summary associations in MR should generally be avoided. When that is not possible, careful consideration of the causal relationships underlying the data (including potentially unmeasured confounders) is required to direct sensitivity analyses and interpret results with appropriate caution.

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