Advent Of Genome-wide Association Studies Research Articles

Predicting structure-targeted food bioactive compounds for middle-aged and elderly Asians with myocardial infarction: insights from genetic variations and bioinformatics-integrated deep learning analysis.

Myocardial infarction (MI) is a significant global health issue. Despite the advances in genome-wide association studies, a complete genetic and molecular understanding of MI is elusive and needs to be fully explored. This study aimed to elucidate the genetic framework of MI and explore the potential health benefits of natural compounds (NCs). The genetic architecture of MI was explored using data from the Korean Genome and Epidemiology Study. We pinpointed crucial protein-coding genes related to MI by multi-marker analysis of genomic annotation for gene-based analysis. The bioinformatics-integrated deep neural analysis of NCs (BioDeepNat), a novel disease discovery application, was utilized to assess the influence of NCs on MI-related target proteins and validated with molecular docking analysis. The BioDeepNat application revealed significant NCs on MI-related target proteins, such as E-resveratrol, epicatechin 3-gallate, and kaempferol. The E3 region of RNF213 protein with a point mutation (Arg4810Lys) had different binding energies with NCs, such as ursolic acid and olean-12-en-28-oic acid, compared to the wild type. However, ginsenosides, eleutheroside, oleanolic acid, and hederagenin showed similar binding energies to wild and mutated types of RNF213 protein. The predicted NCs were primarily sourced from foods such as common grapes and teas. Aromatic hydrocarbons are frequently observed as the prevalent functional groups with high binding affinity for NCs in a molecular docking analysis. In conclusion, the proteins encoded by these genes identified by gene-based analysis interacted with several NCs with health promotion found in day-to-day foods, particularly E-resveratrol and kaempferol. This understanding offers promising directions for precision nutrition strategies in MI.

The methodological and ethical concerns of genetic studies of same-sex sexual behavior.

Same-sex sexual behavior has long interested genetics researchers in part because, while there is evidence of heritability, the trait as typically defined is associated with fewer offspring. Investigations of this phenomenon began in the 1990s with linkage studies and continue today with the advent of genome-wide association studies. As this body of research grows, so does critical scientific and ethical review of it. Here, we provide a targeted overview of existing genetics studies on same-sex sexual behavior, highlight the ethical and scientific considerations of this nascent field, and provide recommendations developed by the authors to enhance social and ethical responsibility.

Genes Involved in Susceptibility to Obesity and Emotional Eating Behavior in a Romanian Population.

Obesity, a significant public health concern with high prevalence in both adults and children, is a complex disorder arising from the interaction of multiple genes and environmental factors. Advances in genome-wide association studies (GWAS) and sequencing technologies have identified numerous polygenic causes of obesity, particularly genes involved in hunger, satiety signals, adipocyte differentiation, and energy expenditure. This study investigates the relationship between six obesity-related genes (CLOCK, FTO, GHRL, LEP, LEPR, MC4R) and their impact on BMI, WC, HC, WHR, and emotional eating behavior in 220 Romanian adults. Emotional eating was assessed using the validated Emotional Eating Questionnaire (EEQ). Our analysis revealed significant variability in obesity-related phenotypes and emotional eating behaviors across different genotypes. Specifically, CLOCK/CC, FTO/AA, and LEP/AA genotypes were strongly associated with higher obesity metrics and emotional eating scores, while GHRL/TT and MC4R/CC were linked to increased BMI and WHR. The interplay between genetic predisposition and emotional eating behavior significantly influenced BMI and WHR, indicating a complex relationship between genetic and behavioral factors. This study, the first of its kind in Romania, provides a foundation for targeted interventions to prevent and reduce obesity and suggests potential strategies for gene expression modulation to mitigate the effects of emotional eating. Adopting a 'One Health' approach by creating an evidence base derived from both human and animal studies is crucial for understanding how to control obesity.

MR-GGI: accurate inference of gene–gene interactions using Mendelian randomization

BackgroundResearchers have long studied the regulatory processes of genes to uncover their functions. Gene regulatory network analysis is one of the popular approaches for understanding these processes, requiring accurate identification of interactions among the genes to establish the gene regulatory network. Advances in genome-wide association studies and expression quantitative trait loci studies have led to a wealth of genomic data, facilitating more accurate inference of gene–gene interactions. However, unknown confounding factors may influence these interactions, making their interpretation complicated. Mendelian randomization (MR) has emerged as a valuable tool for causal inference in genetics, addressing confounding effects by estimating causal relationships using instrumental variables. In this paper, we propose a new statistical method, MR-GGI, for accurately inferring gene–gene interactions using Mendelian randomization.ResultsMR-GGI applies one gene as the exposure and another as the outcome, using causal cis-single-nucleotide polymorphisms as instrumental variables in the inverse-variance weighted MR model. Through simulations, we have demonstrated MR-GGI's ability to control type 1 error and maintain statistical power despite confounding effects. MR-GGI performed the best when compared to other methods using the F1 score on the DREAM5 dataset. Additionally, when applied to yeast genomic data, MR-GGI successfully identified six clusters. Through gene ontology analysis, we have confirmed that each cluster in our study performs distinct functional roles by gathering genes with specific functions.ConclusionThese findings demonstrate that MR-GGI accurately inferences gene–gene interactions despite the confounding effects in real biological environments.

Causal relationship between blood metabolites and risk of five infections: a Mendelian randomization study

ObjectiveInfectious diseases continue to pose a significant threat in the field of global public health, and our understanding of their metabolic pathogenesis remains limited. However, the advent of genome-wide association studies (GWAS) offers an unprecedented opportunity to unravel the relationship between metabolites and infections.MethodsUnivariable and multivariable Mendelian randomization (MR) was commandeered to elucidate the causal relationship between blood metabolism and five high-frequency infection phenotypes: sepsis, pneumonia, upper respiratory tract infections (URTI), urinary tract infections (UTI), and skin and subcutaneous tissue infection (SSTI). GWAS data for infections were derived from UK Biobank and the FinnGen consortium. The primary analysis was conducted using the inverse variance weighted method on the UK Biobank data, along with a series of sensitivity analyses. Subsequently, replication and meta-analysis were performed on the FinnGen consortium data.ResultsAfter primary analysis and a series of sensitivity analyses, 17 metabolites were identified from UK Biobank that have a causal relationship with five infections. Upon joint analysis with the FinGen cohort, 7 of these metabolites demonstrated consistent associations. Subsequently, we conducted a multivariable Mendelian randomization analysis to confirm the independent effects of these metabolites. Among known metabolites, genetically predicted 1-stearoylglycerol (1-SG) (odds ratio [OR] = 0.561, 95% confidence interval [CI]: 0.403–0.780, P < 0.001) and 3-carboxy-4-methyl-5-propyl-2-furanpropanoate (CMPF) (OR = 0.780, 95%CI: 0.689–0.883, P < 0.001) was causatively associated with a lower risk of sepsis, and genetically predicted phenylacetate (PA) (OR = 1.426, 95%CI: 1.152–1.765, P = 0.001) and cysteine (OR = 1.522, 95%CI: 1.170–1.980, P = 0.002) were associated with an increased risk of UTI. Ursodeoxycholate (UDCA) (OR = 0.906, 95%CI: 0.829–0.990, P = 0.029) is a protective factor against pneumonia. Two unknown metabolites, X-12407 (OR = 1.294, 95%CI: 1.131–1.481, P < 0.001), and X-12847 (OR = 1.344, 95%CI: 1.152–1.568, P < 0.001), were also identified as independent risk factors for sepsis.ConclusionsIn this MR study, we demonstrated a causal relationship between blood metabolites and the risk of developing sepsis, pneumonia, and UTI. However, there was no evidence of a causal connection between blood metabolites and the risk of URTI or SSTI, indicating a need for larger-scale studies to further investigate susceptibility to certain infection phenotypes.

From gene-discovery to gene-tailored clinical management: 25 years of research in channelopathies and cardiomyopathies.

In the early nineties, few years before the birth of Europace, the clinical and scientific world of familial arrhythmogenic conditions was revolutionized by the identification of the first disease-causing genes. The explosion of genetic studies over a 15-year period led to the discovery of major disease-causing genes in practically all channelopathies and cardiomyopathies, bringing insight into the pathophysiological mechanisms of these conditions. The birth of next generation sequencing allowed a further step forward and other significant genes, as CALM1-3 in channelopathies and FLN C and TTN in cardiomyopathies were identified. Genotype-phenotype studies allowed the implementation of the genetic results in diagnosis, risk stratification, and therapeutic management with a different level of evidence in different arrhythmogenic conditions. The influence of common genetic variants, i.e. SNPs, on disease manifestation was proved in mid-twenties, and in the last 10 years with the advent of genome-wide association studies performed in familial arrhythmogenic diseases, the concept of polygenic risk score has been consolidated. Now, we are at the start of another amazing phase, i.e. the initiation of first gene therapy clinical trials.

The genetics of non-monogenic IBD.

Inflammatory bowel disease (IBD), with Crohn's disease and ulcerative colitis as main subtypes, is a prototypical multifactorial disease with both genetic and environmental factors involved. Genetically, IBD covers a wide spectrum from monogenic to polygenic forms. In polygenic disease, many genetic variants each contribute a small amount to disease risk. With the advent of genome-wide association studies (GWAS), it became possible to find these variants and corresponding genes, leading so far to the discovery of ca 240 loci associated with IBD. Together, these however explain only 20-25% of the heritability of IBD, leaving a large portion unaccounted for. This missing heritability might be hidden in common variants with even lower effect than the ones currently found through GWAS, but also in rare variants which can be found through large-scale sequencing studies or potentially in multiplex families. In this review, we will give an overview of the current knowledge about the genetics of non-monogenic IBD and how it differs from the monogenic form(s), and future perspectives. The history of IBD genetic studies from twin studies over linkage studies to GWAS, and finally large-scale sequencing studies and the revisiting of multiplex families will be discussed.

Polygenic risk for neuroticism is associated with externalizing symptoms in 2-year-old boys

Recent advances in genome-wide association studies have enabled the estimation of genetic risk of complex traits, including neuroticism, with polygenic risk scores (PRS). Neuroticism PRS has been associated with psychiatric disorders and symptoms in adults, but studies in children are scarce. We studied whether neuroticism PRS, and its subscales, worry PRS and depressive affect PRS, were associated with externalizing and internalizing symptoms in 2-year-olds. We also examined parental neuroticism PRSs' association with children's externalizing and internalizing symptoms and whether parental depressive symptoms mediated the effect. Participants from two Finnish birth cohorts, CHILD-SLEEP and FinnBrain Birth Cohort Study, who had DNA and data on Brief Infant-Toddler Social and Emotional Assessment (BITSEA) available were included in the study (N = 806 and N = 987, respectively). PRSs were calculated based on GWAS data from UK Biobank. Child's neuroticism PRS, and its subscale worry PRS, were positively associated with externalizing symptoms in 2-year-old boys, but not in girls. Mother's depressive symptoms mediated the association between maternal neuroticism PRS and externalizing and internalizing symptoms in boys, but not in girls. Our results suggest that neuroticism PRS, and its subscale worry PRS, are associated with externalizing symptoms in already as young as 2-year-old boys, and, that subclinical symptoms of maternal depression that are based on genetic disposition, have an effect on boy's internalizing and externalizing symptoms. As we did not find any associations in girls, our study supports the suggestion that girls and boys may differ in how genetic and environmental factors contribute to their development.

Advances in genome-wide association studies on obstructive sleep apnea hyponea syndrome

阻塞性睡眠呼吸暂停低通气综合征（OSAHS）是遗传因素与环境因素共同作用的一种复杂的多基因遗传病。近年来，已有多个研究从基因层面探讨OSAHS致病机制，全基因组关联分析（genome-wide association studies，GWAS）作为复杂疾病基因定位研究的技术方法已广泛应用于识别与疾病相关的基因变异位点，本文就OSAHS领域相关GWAS研究作一综述。.

Advances in genome-wide association study of pulmonary arterial hypertension

Pulmonary arterial hypertension (PAH) is a complex disease caused by multiple factors, including idiopathic PAH, heritable PAH, disease related PAH etc. Due to the high genetic heterogeneity, clinical characteristics and prognosis of PAH patients vary greatly. At present, the specific pathogenesis of PAH is unclear, and the diagnosis and treatment of PAH remain to be explored. Therefore, the study of genetic susceptibility to PAH is of great significance for understanding the occurrence and development of the disease. With the development of genome-wide association study (GWAS), a large number of genetic variations related to etiology, clinical manifestations, prognosis and treatment of PAH have been identified. This review summarizes the recent progress in the application of GWAS in the study of genetic susceptibility of PAH, and provides new insights for further exploration of the development and individualized management of PAH.

Construction and Application of Polygenic Risk Scores in Autoimmune Diseases.

Genome-wide association studies (GWAS) have identified hundreds of genetic variants associated with autoimmune diseases and provided unique mechanistic insights and informed novel treatments. These individual genetic variants on their own typically confer a small effect of disease risk with limited predictive power; however, when aggregated (e.g., via polygenic risk score method), they could provide meaningful risk predictions for a myriad of diseases. In this review, we describe the recent advances in GWAS for autoimmune diseases and the practical application of this knowledge to predict an individual’s susceptibility/severity for autoimmune diseases such as systemic lupus erythematosus (SLE) via the polygenic risk score method. We provide an overview of methods for deriving different polygenic risk scores and discuss the strategies to integrate additional information from correlated traits and diverse ancestries. We further advocate for the need to integrate clinical features (e.g., anti-nuclear antibody status) with genetic profiling to better identify patients at high risk of disease susceptibility/severity even before clinical signs or symptoms develop. We conclude by discussing future challenges and opportunities of applying polygenic risk score methods in clinical care.

Genome-wide association of polygenic risk extremes for Alzheimer's disease in the UK Biobank

In just over a decade, advances in genome-wide association studies (GWAS) have offered an approach to stratify individuals based on genetic risk for disease. Using recent Alzheimer's disease (AD) GWAS results as the base data, we determined each individual's polygenic risk score (PRS) in the UK Biobank dataset. Using individuals within the extreme risk distribution, we performed a GWAS that is agnostic of AD phenotype and is instead based on known genetic risk for disease. To interpret the functions of the new risk factors, we conducted phenotype analyses, including a phenome-wide association study. We identified 246 loci surpassing the significance threshold of which 229 were not reported in the base AD GWAS. These include loci that showed suggestive levels of association in the base GWAS and loci not previously suspected to be associated with AD. Among these, there are loci, such as IL34 and KANSL1, that have since been shown to be associated with AD in recent studies. We also show highly significant genetic correlations with multiple health-related outcomes that provide insights into prodromal symptoms and comorbidities. This is the first study to utilize PRS as a phenotype-agnostic group classification in AD genetic studies. We identify potential new loci for AD and detail phenotypic analysis of these PRS extremes.

An Overview of Genome-Wide Association Studies in Multiple Sclerosis

The common neurodegenerative disorder of the central nervous system is multiple sclerosis (MS). It progresses with autoimmune inflammation and demyelination. Molecular basis study of MS pathogenesis is a significant element of field research, leading to new prevention and treatment strategies by defining the genetic association, epigenetic, and environmental risks factor of MS that could provide a predictive method for estimating human predisposition to MS. From a genetic perspective, MS is a complex disorder due to the combination of genetic and non-genetic factors. The main histocompatibility complex (MHC) is the only universal genetic site associated with MS, and it has been approved for many years. The most common risk for MS in most populations is human leukocyte antigen (HLA) at 6p21. Before the advent of genome-wide association studies (GWASs) encouraging finding new susceptibility loci, other genetic factors in the MS remained uncommon. In this literature review, we summarized details, including references, abstracts, and full text of journal articles. These details were selected and obtained from virtual databases such as Medline and PubMed. Using the keywords and health descriptors in MS, GWAS, IL7R and HLA genes for published data from 2007 until 2019.So, the purpose of this research was to perform an analysis of recent progress in identifying genetic factors and gene polymorphism that affect the risk of MS and how these results explain the disease pathogenesis.

Diagnostic and therapeutic potential of exosomal miRNAs in Alzheimer's disease.

Diagnostic and therapeutic potential of exosomal miRNAs in Alzheimer's disease.

Genome-wide association analysis of type 2 diabetes in the EPIC-InterAct study

Type 2 diabetes (T2D) is a global public health challenge. Whilst the advent of genome-wide association studies has identified >400 genetic variants associated with T2D, our understanding of its biological mechanisms and translational insights is still limited. The EPIC-InterAct project, centred in 8 countries in the European Prospective Investigations into Cancer and Nutrition study, is one of the largest prospective studies of T2D. Established as a nested case-cohort study to investigate the interplay between genetic and lifestyle behavioural factors on the risk of T2D, a total of 12,403 individuals were identified as incident T2D cases, and a representative sub-cohort of 16,154 individuals was selected from a larger cohort of 340,234 participants with a follow-up time of 3.99 million person-years. We describe the results from a genome-wide association analysis between more than 8.9 million SNPs and T2D risk among 22,326 individuals (9,978 cases and 12,348 non-cases) from the EPIC-InterAct study. The summary statistics to be shared provide a valuable resource to facilitate further investigations into the genetics of T2D.

Genetic Determinants of Childhood Obesity.

Obesity represents a major health burden to both developed and developing countries. Furthermore, the incidence of obesity is increasing in children. Obesity contributes substantially to mortality in the United States by increasing the risk for type 2 diabetes, cardiovascular-related diseases, and other comorbidities. Despite environmental changes over past decades, including increases in high-calorie foods and sedentary lifestyles, there is very clear evidence of a genetic predisposition to obesity risk. Childhood obesity cases can be categorized in one of two ways: syndromic or non-syndromic. Syndromic obesity includes disorders such as Prader-Willi syndrome, Bardet-Biedl syndrome, and Alström syndrome. Non-syndromic cases of obesity can be further separated into rarer instances of monogenic obesity and much more common forms of polygenic obesity. The advent of genome-wide association studies (GWAS) and next-generation sequencing has driven significant advances in our understanding of the genetic contribution to childhood obesity. Many rare and common genetic variants have been shown to contribute to the heritability in obesity, although the molecular mechanisms underlying most of these variants remain unclear. An important caveat of GWAS efforts is that they do not strictly represent gene target discoveries, rather simply the uncovering of robust genetic signals. One clear example of this is with progress in understanding the key obesity signal harbored within an intronic region of the FTO gene. It has been shown that the non-coding region in which the variant actually resides in fact influences the expression of genes distal to FTO instead, specifically IRX3 and IRX5. Such discoveries suggest that associated non-coding variants can be embedded within or next to one gene, but commonly influence the expression of other, more distal effector genes. Advances in genetics and genomics are therefore contributing to a deeper understanding of childhood obesity, allowing for development of clinical tools and therapeutic agents.

Advances in genome-wide association study of chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD) is characterized by irreversible airflow obstruction and chronic airway inflammation, caused by a combination of environmental and genetic factors. It is the third leading cause of death worldwide. In recent years, researchers have applied the genome-wide association study (GWAS) and identified a large number of genetic variants associated with lung functions and potential drug targets for treating COPD. In this review, we summarize the results of GWAS studies and perform a review of the literature since 2007 to highlight the progress of GWAS on COPD. We discuss the challenges, the underlying mechanisms, and the possible drug targets, thereby providing insights on the pathogenesis and potential treatment strategies for COPD.

Genome-Wide Association Studies of CKD and Related Traits.

The past few years have seen major advances in genome-wide association studies (GWAS) of CKD and kidney function-related traits in several areas: increases in sample size from >100,000 to >1 million, enabling the discovery of >250 associated genetic loci that are highly reproducible; the inclusion of participants not only of European but also of non-European ancestries; and the use of advanced computational methods to integrate additional genomic and other unbiased, high-dimensional data to characterize the underlying genetic architecture and prioritize potentially causal genes and variants. Together with other large-scale biobank and genetic association studies of complex traits, these GWAS of kidney function-related traits have also provided novel insight into the relationship of kidney function to other diseases with respect to their genetic associations, genetic correlation, and directional relationships. A number of studies also included functional experiments using model organisms or cell lines to validate prioritized potentially causal genes and/or variants. In this review article, we will summarize these recent GWAS of CKD and kidney function-related traits, explain approaches for downstream characterization of associated genetic loci and the value of such computational follow-up analyses, and discuss related challenges along with potential solutions to ultimately enable improved treatment and prevention of kidney diseases through genetics.

Role and Regulation of Cytokinins in Plant Response to Drought Stress.

Cytokinins (CKs) are key phytohormones that not only regulate plant growth and development but also mediate plant tolerance to drought stress. Recent advances in genome-wide association studies coupled with in planta characterization have opened new avenues to investigate the drought-responsive expression of CK metabolic and signaling genes, as well as their functions in plant adaptation to drought. Under water deficit, CK signaling has evolved as an inter-cellular communication network which is essential to crosstalk with other types of phytohormones and their regulating pathways in mediating plant stress response. In this review, we revise the current understanding of CK involvement in drought stress tolerance. Particularly, a genetic framework for CK signaling and CK crosstalk with abscisic acid (ABA) in the precise monitoring of drought responses is proposed. In addition, the potential of endogenous CK alteration in crops towards developing drought-tolerant crops is also discussed.

Advances in genome-wide association studies of complex traits in rice.

Genome-wide association studies (GWAS), genetic surveys of the whole genome to detect variants associated with a trait in natural populations, are a powerful approach for dissecting complex traits. This genetic mapping approach has been applied in rice over the last 10years. During the last decade, GWAS was used to identify the loci underlying tens of rice traits, and several important genes were detected in GWAS and further confirmed in follow-up functional experiments. In this review, we present an overview of the whole process in a typical GWAS, including population design, genotyping, phenotyping and analysis methods. Recent advances in rice GWAS are also provided, including several examples of the functional characterization of candidate genes. The possible breakthroughs of rice GWAS in the next decade are discussed with regard to their application in breeding, the consideration of epistatic interactions and in-depth functional annotations of DNA elements and genetic variants throughout the rice genome.