scholarly journals Modelling of time-to-events in an ambispective study: illustration with the analysis of ABO blood groups on venous thrombosis recurrence

2021 ◽  
Author(s):  
Gaëlle Munsch ◽  
Louisa Goumidi ◽  
Astrid van Hylckama Vlieg ◽  
Manal Ibrahim-Kosta ◽  
Maria Bruzelius ◽  
...  
Keyword(s):  
Risk Factors ◽  
Statistical Power ◽  
Association Studies ◽  
Blood Groups ◽  
Genome Wide Association Studies ◽  
Abo Blood Groups ◽  
Genome Wide ◽  
Increased Risk ◽  
Independent Risk Factors ◽  
Analyse Time

In studies of time-to-events, it is common to collect information about events that occurred before the inclusion in a prospective cohort. In an ambispective design, when the risk factors studied are independent of time, including both pre- and post-inclusion events in the analyses increases the statistical power but may lead to a selection bias. To avoid such a bias, we propose a survival analysis weighted by the inverse of the survival probability at the time of data collection about the events. This method is applied to the study of the association of ABO blood groups with the risk of venous thromboembolism (VT) recurrence in the MARTHA and MEGA cohorts. The former relying on an ambispective design and the latter on a standard prospective one. In the combined sample totalling 2,752 patients including 993 recurrences, compared with the O1 group, A1 has an increased risk (Hazard Ratio (HR) of 1.18, p=4.2x10-3), homogeneously in MARTHA and in MEGA. The same trend (HR=1.19, p=0.06) was observed for the less frequent A2 group. In conclusion, this work clarified the association of ABO blood groups with the risk of VT recurrence. Besides, the methodology proposed here to analyse time-independent risk factors of events in an ambispective design has an immediate field of application in the context of genome wide association studies.

Evaluation of genes associated with undescended testes as predictors of TGCT susceptibility.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 1539-1539
Author(s):  
Ariela Marshall ◽  
Stephanie L. Ciosek ◽  
Saran Vardhanabhuti ◽  
Nandita Mitra ◽  
David J. Vaughn ◽  
...  
Keyword(s):  
Risk Factors ◽  
Genetic Risk ◽  
Association Studies ◽  
Snp Array ◽  
Genetic Risk Factors ◽  
Genome Wide Association Studies ◽  
Undescended Testes ◽  
Genome Wide ◽  
Increased Risk ◽  
Genotype Information

1539 Background: Testicular germ cell tumors (TGCTs) are highly heritable. Cryptorchidism (undescended testes; UDT) is a strong risk factor for TGCT, with increased risk to both the ipsilateral and contralateral testes. However, recent genome-wide association studies (GWAS) identifying genetic variants associated with TGCT susceptibility have not found differences in genotype carriage between TGCT patients with and without UDT. We investigated the role of potential risk variants for UDT as risk factors for TGCT. Methods: 1300 SNPs in and around 25 gene regions with published associations with UDT were evaluated in 474 TGCT cases (45 with UDT) and 919 controls. Genotype information was available from the Affymetrix Genome-Wide Human SNP Array 6.0. Statistical analysis was performed using PLINK, and statistical significance was assessed by Fisher's Exact test. Results: Comparing TGCT cases with and without UDT, variants in the region of four genes (EPHB2, ESR1, SEMA3C, TGFBR3) were suggestively associated with UDT. When TGCT cases with UDT were compared with unaffected controls, the associations all met the required level of significance (p < 4 x 10-5). Only variation at ESR1 approached significance (P=0.0004) when TGCT cases and unaffected controls were compared. Conclusions: We identified variants at three genetic loci - SEMA3C, TGFBR3 and EPHB2 - that were significantly associated with UDT, but not with TGCT. The association of variation in EPHB2 and SEMA3C with UDT are novel findings. While associated with UDT, variation at ESR1 is also potentially associated with TGCT risk. These data continue to suggest that genetic risk factors for UDT are largely independent of those for TGCT. Thus, screening for TGCT could be targeted in a UDT population to those with genetic risk factors. Further studies should be done to investigate the genetic link between UDT and TGCT.

scholarly journals The Genetic Basis of Hypertriglyceridemia

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.

scholarly journals Common genetic variants with fetal effects on birth weight are enriched for proximity to genes implicated in rare developmental disorders

2021 ◽  
Author(s):  
Robin N Beaumont ◽  
Isabelle K Mayne ◽  
Rachel M Freathy ◽  
Caroline F Wright
Keyword(s):  
Birth Weight ◽  
Statistical Power ◽  
Developmental Disorders ◽  
Association Studies ◽  
Later Life ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Genome Wide ◽  
Common Genetic Variants ◽  
Causal Genes

Abstract Birth weight is an important factor in newborn survival; both low and high birth weights are associated with adverse later-life health outcomes. Genome-wide association studies (GWAS) have identified 190 loci associated with maternal or fetal effects on birth weight. Knowledge of the underlying causal genes is crucial to understand how these loci influence birth weight and the links between infant and adult morbidity. Numerous monogenic developmental syndromes are associated with birth weights at the extreme ends of the distribution. Genes implicated in those syndromes may provide valuable information to prioritize candidate genes at the GWAS loci. We examined the proximity of genes implicated in developmental disorders (DDs) to birth weight GWAS loci using simulations to test whether they fall disproportionately close to the GWAS loci. We found birth weight GWAS single nucleotide polymorphisms (SNPs) fall closer to such genes than expected both when the DD gene is the nearest gene to the birth weight SNP and also when examining all genes within 258 kb of the SNP. This enrichment was driven by genes causing monogenic DDs with dominant modes of inheritance. We found examples of SNPs in the intron of one gene marking plausible effects via different nearby genes, highlighting the closest gene to the SNP not necessarily being the functionally relevant gene. This is the first application of this approach to birth weight, which has helped identify GWAS loci likely to have direct fetal effects on birth weight, which could not previously be classified as fetal or maternal owing to insufficient statistical power.

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

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

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

scholarly journals Genetics of Atrial Fibrillation in 2020

2020 ◽  
Vol 127 (1) ◽  
pp. 21-33 ◽  
Author(s):  
Carolina Roselli ◽  
Michiel Rienstra ◽  
Patrick T. Ellinor
Keyword(s):  
Atrial Fibrillation ◽  
Complex Disease ◽  
Association Studies ◽  
Heart Rhythm ◽  
Genome Wide Association Studies ◽  
Future Directions ◽  
Genetics Research ◽  
Genome Wide ◽  
Increased Risk ◽  
Rhythm Disorder

Atrial fibrillation is a common heart rhythm disorder that leads to an increased risk for stroke and heart failure. Atrial fibrillation is a complex disease with both environmental and genetic risk factors that contribute to the arrhythmia. Over the last decade, rapid progress has been made in identifying the genetic basis for this common condition. In this review, we provide an overview of the primary types of genetic analyses performed for atrial fibrillation, including linkage studies, genome-wide association studies, and studies of rare coding variation. With these results in mind, we aim to highlighting the existing knowledge gaps and future directions for atrial fibrillation genetics research.

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

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

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

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