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 Loss-of-Function Variants in the SYNPO2L Gene Are Associated With Atrial Fibrillation

2021 ◽  
Vol 8 ◽  
Author(s):  
Alexander Guldmann Clausen ◽  
Oliver Bundgaard Vad ◽  
Julie Husted Andersen ◽  
Morten Salling Olesen
Keyword(s):  
Atrial Fibrillation ◽  
Cardiac Myocyte ◽  
Association Studies ◽  
Structural Development ◽  
Genome Wide Association Studies ◽  
Loss Of Function ◽  
Genome Wide ◽  
Increased Risk ◽  
Rare Genetic Variants ◽  
And Function

Multiple genome-wide association studies (GWAS) have identified numerous loci associated with atrial fibrillation (AF). However, the genes driving these associations and how they contribute to the AF pathogenesis remains poorly understood. To identify genes likely to be driving the observed association, we searched the FinnGen study consisting of 12,859 AF cases and 73,341 controls for rare genetic variants predicted to cause loss-of-function. A specific splice site variant was found in the SYNPO2L gene, located in an AF associated locus on chromosome 10. This variant was associated with an increased risk of AF with a relatively high odds ratio of 3.5 (p = 9.9 × 10−8). SYNPO2L is an important gene involved in the structural development and function of the cardiac myocyte and our findings thus support the recent suggestions that AF can present as atrial cardiomyopathy.

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 Genetics and Epigenetics of Atrial Fibrillation

2020 ◽  
Vol 21 (16) ◽  
pp. 5717 ◽  
Author(s):  
Estefanía Lozano-Velasco ◽  
Diego Franco ◽  
Amelia Aranega ◽  
Houria Daimi
Keyword(s):  
Atrial Fibrillation ◽  
Regulatory Networks ◽  
Association Studies ◽  
Functional Characterization ◽  
The Elderly ◽  
Supraventricular Arrhythmia ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Transcriptional Regulatory ◽  
Transcriptional Regulatory Mechanisms

Atrial fibrillation (AF) is known to be the most common supraventricular arrhythmia affecting up to 1% of the general population. Its prevalence exponentially increases with age and could reach up to 8% in the elderly population. The management of AF is a complex issue that is addressed by extensive ongoing basic and clinical research. AF centers around different types of disturbances, including ion channel dysfunction, Ca2+-handling abnormalities, and structural remodeling. Genome-wide association studies (GWAS) have uncovered over 100 genetic loci associated with AF. Most of these loci point to ion channels, distinct cardiac-enriched transcription factors, as well as to other regulatory genes. Recently, the discovery of post-transcriptional regulatory mechanisms, involving non-coding RNAs (especially microRNAs), DNA methylation, and histone modification, has allowed to decipher how a normal heart develops and which modifications are involved in reshaping the processes leading to arrhythmias. This review aims to provide a current state of the field regarding the identification and functional characterization of AF-related epigenetic regulatory networks

scholarly journals Insights into Dyslexia Genetics Research from the Last Two Decades

2021 ◽  
Vol 12 (1) ◽  
pp. 27
Author(s):  
Florina Erbeli ◽  
Marianne Rice ◽  
Silvia Paracchini
Keyword(s):  
Language Disorder ◽  
Association Studies ◽  
Neurodevelopmental Disorder ◽  
Molecular Genetic ◽  
Genetic Research ◽  
Twin Studies ◽  
Genome Wide Association Studies ◽  
Genetics Research ◽  
Genome Wide ◽  
Genetic Risks

Dyslexia, a specific reading disability, is a common (up to 10% of children) and highly heritable (~70%) neurodevelopmental disorder. Behavioral and molecular genetic approaches are aimed towards dissecting its significant genetic component. In the proposed review, we will summarize advances in twin and molecular genetic research from the past 20 years. First, we will briefly outline the clinical and educational presentation and epidemiology of dyslexia. Next, we will summarize results from twin studies, followed by molecular genetic research (e.g., genome-wide association studies (GWASs)). In particular, we will highlight converging key insights from genetic research. (1) Dyslexia is a highly polygenic neurodevelopmental disorder with a complex genetic architecture. (2) Dyslexia categories share a large proportion of genetics with continuously distributed measures of reading skills, with shared genetic risks also seen across development. (3) Dyslexia genetic risks are shared with those implicated in many other neurodevelopmental disorders (e.g., developmental language disorder and dyscalculia). Finally, we will discuss the implications and future directions. As the diversity of genetic studies continues to increase through international collaborate efforts, we will highlight the challenges in advances of genetics discoveries in this field.

scholarly journals Genome-Wide Association Studies of Endometrial Cancer: Latest Developments and Future Directions

2019 ◽  
Vol 28 (7) ◽  
pp. 1095-1102 ◽  
Author(s):  
Tracy A. O'Mara ◽  
Dylan M. Glubb ◽  
Pik Fang Kho ◽  
Deborah J. Thompson ◽  
Amanda B. Spurdle
Keyword(s):  
Endometrial Cancer ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Future Directions ◽  
Genome Wide

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.

GWAS contribution to atrial fibrillation and atrial fibrillation-related stroke: pathophysiological implications

2019 ◽  
Vol 20 (10) ◽  
pp. 765-780 ◽  
Author(s):  
Diana Cruz ◽  
Ricardo Pinto ◽  
Margarida Freitas-Silva ◽  
José Pedro Nunes ◽  
Rui Medeiros
Keyword(s):  
Atrial Fibrillation ◽  
Genetic Variants ◽  
Complex Traits ◽  
Association Studies ◽  
Cardioembolic Stroke ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Genetic Determinants ◽  
Genome Wide ◽  
Genome Wide Significance

Atrial fibrillation (AF) and stroke are included in a group of complex traits that have been approached regarding of their study by susceptibility genetic determinants. Since 2007, several genome-wide association studies (GWAS) aiming to identify genetic variants modulating AF risk have been conducted. Thus, 11 GWAS have identified 26 SNPs (p < 5 × 10-2), of which 19 reached genome-wide significance (p < 5 × 10-8). From those variants, seven were also associated with cardioembolic stroke and three reached genome-wide significance in stroke GWAS. These associations may shed a light on putative shared etiologic mechanisms between AF and cardioembolic stroke. Additionally, some of these identified variants have been incorporated in genetic risk scores in order to elucidate new approaches of stroke prediction, prevention and treatment.

scholarly journals A Review of the Hereditary Component of Triple Negative Breast Cancer: High- and Moderate-Penetrance Breast Cancer Genes, Low-Penetrance Loci, and the Role of Nontraditional Genetic Elements

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Darrell L. Ellsworth ◽  
Clesson E. Turner ◽  
Rachel E. Ellsworth
Keyword(s):  
Breast Cancer ◽  
Triple Negative Breast Cancer ◽  
Large Scale ◽  
Triple Negative ◽  
Association Studies ◽  
African Ancestry ◽  
Genome Wide Association Studies ◽  
Genetic Elements ◽  
Genome Wide ◽  
Increased Risk

Triple negative breast cancer (TNBC), representing 10-15% of breast tumors diagnosed each year, is a clinically defined subtype of breast cancer associated with poor prognosis. The higher incidence of TNBC in certain populations such as young women and/or women of African ancestry and a unique pathological phenotype shared between TNBC and BRCA1-deficient tumors suggest that TNBC may be inherited through germline mutations. In this article, we describe genes and genetic elements, beyond BRCA1 and BRCA2, which have been associated with increased risk of TNBC. Multigene panel testing has identified high- and moderate-penetrance cancer predisposition genes associated with increased risk for TNBC. Development of large-scale genome-wide SNP assays coupled with genome-wide association studies (GWAS) has led to the discovery of low-penetrance TNBC-associated loci. Next-generation sequencing has identified variants in noncoding RNAs, viral integration sites, and genes in underexplored regions of the human genome that may contribute to the genetic underpinnings of TNBC. Advances in our understanding of the genetics of TNBC are driving improvements in risk assessment and patient management.

scholarly journals Animal Models of GWAS-Identified Type 2 Diabetes Genes

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Gabriela da Silva Xavier ◽  
Elisa A. Bellomo ◽  
James A. McGinty ◽  
Paul M. French ◽  
Guy A. Rutter
Keyword(s):  
Type 2 Diabetes ◽  
Animal Models ◽  
Mouse Models ◽  
Human Genetics ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Risk Genes ◽  
Genome Wide ◽  
Increased Risk

More than 65loci, encoding up to 500 different genes, have been implicated by genome-wide association studies (GWAS) as conferring an increased risk of developing type 2 diabetes (T2D). Whilst mouse models have in the past been central to understanding the mechanisms through which more penetrant risk genes for T2D, for example, those responsible for neonatal or maturity-onset diabetes of the young, only a few of those identified by GWAS, notablyTCF7L2andZnT8/SLC30A8, have to date been examined in mouse models. We discuss here the animal models available for the latter genes and provide perspectives for future, higher throughput approaches towards efficiently mining the information provided by human genetics.

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