scholarly journals Compared Heritability of Chronotype Instruments in a Single Population Sample

2021 ◽  
pp. 074873042110304
Author(s):  
Mario A. Leocadio-Miguel ◽  
Francieli S. Ruiz ◽  
Sabrina S. Ahmed ◽  
Tâmara P. Taporoski ◽  
Andréa R. V. R. Horimoto ◽  
...  
Keyword(s):  
Clock Genes ◽  
Association Studies ◽  
Population Sample ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Self Evaluation ◽  
Evaluation Question ◽  
Significant Heritability ◽  
Family Based ◽  
Major Factors

It is well established that the oldest chronotype questionnaire, the morningness-eveningness questionnaire (MEQ), has significant heritability, and several associations have been reported between MEQ score and polymorphisms in candidate clock genes, a number of them reproducibly across populations. By contrast, there are no reports of heritability and genetic associations for the Munich chronotype questionnaire (MCTQ). Recent genome-wide association studies (GWAS) from large cohorts have reported multiple associations with chronotype as assessed by a single self-evaluation question. We have taken advantage of the availability of data from all these instruments from a single sample of 597 participants from the Brazilian Baependi Heart Study. The family-based design of the cohort allowed us to calculate the heritability (h2) for these measures. Heritability values for the best-fitted models were 0.37 for MEQ, 0.32 for MCTQ, and 0.28 for single-question chronotype (MEQ Question 19). We also calculated the heritability for the two major factors recently derived from MEQ, “Dissipation of sleep pressure” (0.32) and “Build-up of sleep pressure” (0.28). This first heritability comparison of the major chronotype instruments in current use provides the first quantification of the genetic component of MCTQ score, supporting its future use in genetic analysis. Our findings also suggest that the single chronotype question that has been used for large GWAS analyses captures a larger proportion of the dimensions of chronotype than previously thought.

scholarly journals Case–Parent Trio Studies in Cleft Lip and Palate

2020 ◽  
Vol 07 (03) ◽  
pp. 075-079
Author(s):  
Mahamad Irfanulla Khan ◽  
Prashanth CS
Keyword(s):  
Genetic Variants ◽  
Cleft Lip ◽  
Cleft Lip And Palate ◽  
Association Studies ◽  
Geographical Location ◽  
Genetic Association Studies ◽  
Population Based ◽  
Genome Wide Association Studies ◽  
Family Based ◽  
Study Designs

AbstractCleft lip with or without cleft palate (CL/P) is one of the most common congenital malformations in humans involving various genetic and environmental risk factors. The prevalence of CL/P varies according to geographical location, ethnicity, race, gender, and socioeconomic status, affecting approximately 1 in 800 live births worldwide. Genetic studies aim to understand the mechanisms contributory to a phenotype by measuring the association between genetic variants and also between genetic variants and phenotype population. Genome-wide association studies are standard tools used to discover genetic loci related to a trait of interest. Genetic association studies are generally divided into two main design types: population-based studies and family-based studies. The epidemiological population-based studies comprise unrelated individuals that directly compare the frequency of genetic variants between (usually independent) cases and controls. The alternative to population-based studies (case–control designs) includes various family-based study designs that comprise related individuals. An example of such a study is a case–parent trio design study, which is commonly employed in genetics to identify the variants underlying complex human disease where transmission of alleles from parents to offspring is studied. This article describes the fundamentals of case–parent trio study, trio design and its significances, statistical methods, and limitations of the trio studies.

scholarly journals Family-based gene-environment interaction using sequence kernel association test (FGE-SKAT) for complex quantitative traits

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chao-Yu Guo ◽  
Reng-Hong Wang ◽  
Hsin-Chou Yang
Keyword(s):  
Complex Traits ◽  
Association Studies ◽  
Association Test ◽  
Whole Genome Sequence ◽  
Environment Interaction ◽  
Genome Wide Association Studies ◽  
Whole Genome ◽  
Sequence Kernel Association Test ◽  
Gene Environment ◽  
Family Based

AbstractAfter the genome-wide association studies (GWAS) era, whole-genome sequencing is highly engaged in identifying the association of complex traits with rare variations. A score-based variance-component test has been proposed to identify common and rare genetic variants associated with complex traits while quickly adjusting for covariates. Such kernel score statistic allows for familial dependencies and adjusts for random confounding effects. However, the etiology of complex traits may involve the effects of genetic and environmental factors and the complex interactions between genes and the environment. Therefore, in this research, a novel method is proposed to detect gene and gene-environment interactions in a complex family-based association study with various correlated structures. We also developed an R function for the Fast Gene-Environment Sequence Kernel Association Test (FGE-SKAT), which is freely available as supplementary material for easy GWAS implementation to unveil such family-based joint effects. Simulation studies confirmed the validity of the new strategy and the superior statistical power. The FGE-SKAT was applied to the whole genome sequence data provided by Genetic Analysis Workshop 18 (GAW18) and discovered concordant and discordant regions compared to the methods without considering gene by environment interactions.

scholarly journals Penalized partial least squares for pleiotropy

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Camilo Broc ◽  
Therese Truong ◽  
Benoit Liquet
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Association Studies ◽  
A Priori ◽  
Simulated Data ◽  
Real Data ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Multiple Traits ◽  
Application Fields

Abstract Background The increasing number of genome-wide association studies (GWAS) has revealed several loci that are associated to multiple distinct phenotypes, suggesting the existence of pleiotropic effects. Highlighting these cross-phenotype genetic associations could help to identify and understand common biological mechanisms underlying some diseases. Common approaches test the association between genetic variants and multiple traits at the SNP level. In this paper, we propose a novel gene- and a pathway-level approach in the case where several independent GWAS on independent traits are available. The method is based on a generalization of the sparse group Partial Least Squares (sgPLS) to take into account groups of variables, and a Lasso penalization that links all independent data sets. This method, called joint-sgPLS, is able to convincingly detect signal at the variable level and at the group level. Results Our method has the advantage to propose a global readable model while coping with the architecture of data. It can outperform traditional methods and provides a wider insight in terms of a priori information. We compared the performance of the proposed method to other benchmark methods on simulated data and gave an example of application on real data with the aim to highlight common susceptibility variants to breast and thyroid cancers. Conclusion The joint-sgPLS shows interesting properties for detecting a signal. As an extension of the PLS, the method is suited for data with a large number of variables. The choice of Lasso penalization copes with architectures of groups of variables and observations sets. Furthermore, although the method has been applied to a genetic study, its formulation is adapted to any data with high number of variables and an exposed a priori architecture in other application fields.

scholarly journals Genetic Determinants of Paget’s Disease of Bone

2021 ◽  
Author(s):  
Navnit S. Makaram ◽  
Stuart H. Ralston
Keyword(s):  
Genetic Factors ◽  
Association Studies ◽  
Paget’S Disease ◽  
Paget's Disease ◽  
Paget’S Disease Of Bone ◽  
Genome Wide Association Studies ◽  
Paget's Disease Of Bone ◽  
Genome Wide ◽  
Family Based

Abstract Purpose of Review To provide an overview of the role of genes and loci that predispose to Paget’s disease of bone and related disorders. Recent Findings Studies over the past ten years have seen major advances in knowledge on the role of genetic factors in Paget’s disease of bone (PDB). Genome wide association studies have identified six loci that predispose to the disease whereas family based studies have identified a further eight genes that cause PDB. This brings the total number of genes and loci implicated in PDB to fourteen. Emerging evidence has shown that a number of these genes also predispose to multisystem proteinopathy syndromes where PDB is accompanied by neurodegeneration and myopathy due to the accumulation of abnormal protein aggregates, emphasising the importance of defects in autophagy in the pathogenesis of PDB. Summary Genetic factors play a key role in the pathogenesis of PDB and the studies in this area have identified several genes previously not suspected to play a role in bone metabolism. Genetic testing coupled to targeted therapeutic intervention is being explored as a way of halting disease progression and improving outcome before irreversible skeletal damage has occurred.

scholarly journals Genetic association studies of alterations in protein function expose recessive effects on cancer predisposition

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Nadav Brandes ◽  
Nathan Linial ◽  
Michal Linial
Keyword(s):  
Cancer Risk ◽  
Protein Function ◽  
Association Studies ◽  
Genetic Effects ◽  
Cancer Predisposition ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Functional Interpretation ◽  
Gene Damage ◽  
Genomic Regions

AbstractThe characterization of germline genetic variation affecting cancer risk, known as cancer predisposition, is fundamental to preventive and personalized medicine. Studies of genetic cancer predisposition typically identify significant genomic regions based on family-based cohorts or genome-wide association studies (GWAS). However, the results of such studies rarely provide biological insight or functional interpretation. In this study, we conducted a comprehensive analysis of cancer predisposition in the UK Biobank cohort using a new gene-based method for detecting protein-coding genes that are functionally interpretable. Specifically, we conducted proteome-wide association studies (PWAS) to identify genetic associations mediated by alterations to protein function. With PWAS, we identified 110 significant gene-cancer associations in 70 unique genomic regions across nine cancer types and pan-cancer. In 48 of the 110 PWAS associations (44%), estimated gene damage is associated with reduced rather than elevated cancer risk, suggesting a protective effect. Together with standard GWAS, we implicated 145 unique genomic loci with cancer risk. While most of these genomic regions are supported by external evidence, our results also highlight many novel loci. Based on the capacity of PWAS to detect non-additive genetic effects, we found that 46% of the PWAS-significant cancer regions exhibited exclusive recessive inheritance. These results highlight the importance of recessive genetic effects, without relying on familial studies. Finally, we show that many of the detected genes exert substantial cancer risk in the studied cohort determined by a quantitative functional description, suggesting their relevance for diagnosis and genetic consulting.

scholarly journals Heterogeneous Network Edge Prediction: A Data Integration Approach to Prioritize Disease-Associated Genes

2014 ◽  
Author(s):  
Daniel S Himmelstein ◽  
Sergio E Baranzini
Keyword(s):  
Data Integration ◽  
Protein Interactions ◽  
Heterogeneous Network ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Protein Coding ◽  
Multiple Node ◽  
Pathogenic Variants ◽  
Disease Associated Genes

The first decade of Genome Wide Association Studies (GWAS) has uncovered a wealth of disease-associated variants. Two important derivations will be the translation of this information into a multiscale understanding of pathogenic variants, and leveraging existing data to increase the power of existing and future studies through prioritization. We explore edge prediction on heterogeneous networks—graphs with multiple node and edge types—for accomplishing both tasks. First we constructed a network with 18 node types—genes, diseases, tissues, pathophysiologies, and 14 MSigDB (molecular signatures database)collections—and 19 edge types from high-throughput publicly-available resources. From this network composed of 40,343 nodes and 1,608,168 edges, we extracted features that describe the topology between specific genes and diseases. Next, we trained a model from GWAS associations and predicted the probability of association between each protein-coding gene and each of 29 well-studied complex diseases. The model, which achieved 132-fold enrichment in precision at 10% recall, outperformed any individual domain, highlighting the benefit of integrative approaches. We identified pleiotropy, transcriptional signatures of perturbations, pathways, and protein interactions as fundamental mechanisms explaining pathogenesis. Our method successfully predicted the results (with AUROC = 0.79) from a withheld multiple sclerosis (MS) GWAS despite starting with only 13 previously associated genes. Finally, we combined our network predictions with statistical evidence of association to propose four novel MS genes, three of which (JAK2, REL, RUNX3) validated on the masked GWAS. Furthermore, our predictions provide biological support highlighting REL as the causal gene within its gene-rich locus. Users can browse all predictions online (http://het.io). Heterogeneous network edge prediction effectively prioritized genetic associations and provides a powerful new approach for data integration across multiple domains.

Abstract 49: Adipose-Specific Knockout of Trib1 Reduces Plasma Lipids and Diet-Induced Insulin Resistance, and Increases Circulating Adiponectin

2017 ◽  
Vol 37 (suppl_1) ◽  
Author(s):  
Mikhaila A Smith ◽  
Jian Cui ◽  
Sumeet A Kheterpal ◽  
Daniel J Rader ◽  
Robert C Bauer
Keyword(s):  
Body Mass ◽  
Plasma Lipids ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Tissue Mass ◽  
Fed State ◽  
Plasma Adiponectin ◽  
Metabolic Role

Tribbles-1 (TRIB1) was recently identified through genome-wide association studies as a novel mediator of plasma lipids and coronary artery disease in humans. While subsequent in vivo mouse work confirmed a role for hepatic TRIB1 in these associations, little is known about metabolic roles for extra-hepatic Trib1. Interestingly, SNPs near the TRIB1 gene are significantly associated with circulating adiponectin levels in humans, suggesting a metabolic role for adipose TRIB1 . To further investigate this, we generated adipose-specific Trib1 KO mice (Trib1_ASKO) by crossing Trib1 cKO mice to transgenic Adiponectin-Cre mice. Chow-fed Trib1_ASKO mice exhibited no differences in adipose tissue mass and overall body mass as compared to control littermates (N=8/group). However, Trib1_ASKO mice had reduced total (-16.9%, p <0.01), HDL (-16.7%, p <0.01), and non-HDL cholesterol (-17.3%, p =0.068), as well as plasma triglycerides (-28.6%, p <0.001) as compared to WT mice. Trib1_ASKO mice also had increased plasma adiponectin levels, a finding more pronounced in female mice (+33.3%, p <0.001) than in males (+16.4%, p =0.072). Despite this increase, transcript levels of adipoQ were moderately decreased in Trib1_ASKO mice, suggesting a post-transcriptional mode of regulation. Transcript and protein levels of C/EBPα, the best described target of Trib1 and a key regulator of adipogenesis, remained unchanged. To further investigate the metabolic consequences of adipose-specific KO of Trib1 , WT and Trib1_ASKO mice were fed high-fat diet (HFD, 45% kCal fat) for 12 weeks to induce obesity. HFD-fed Trib1_ASKO mice had reduced fasting plasma glucose (-22.3%, p <0.05), insulin (-38.2%, p <0.05), and glucose tolerance (-19.8% AUC, p <0.05) compared to control mice. Body mass and fat mass of HFD-fed Trib1_ASKO mice remained unchanged from WT, and the reductions in plasma lipids and increase in plasma adiponectin persisted in the HFD-fed state. In summary, we present here the first in vivo validation of the human genetic association between TRIB1 and plasma adiponectin, and provide evidence suggesting that adipose TRIB1 contributes to the genetic associations observed in humans between TRIB1 and multiple metabolic parameters.

Timing of pubertal development and midlife blood pressure in men and women: A Mendelian randomization study

2021 ◽  
Author(s):  
Io Ieong Chan ◽  
Man Ki Kwok ◽  
C Mary Schooling
Keyword(s):  
Blood Pressure ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Pubertal Development ◽  
Sensitivity Analyses ◽  
Age At Menarche ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Pubertal Maturation ◽  
Pubertal Growth

Abstract Introduction Observational studies suggest earlier puberty is associated with higher adulthood blood pressure (BP), but these findings have not been replicated using Mendelian randomization (MR). We examined this question sex-specifically using larger genome-wide association studies (GWAS) with more extensive measures of pubertal timing. Methods We obtained genetic instruments proxying pubertal maturation (age at menarche (AAM) or voice breaking (AVB)) from the largest published GWAS. We applied them to summary sex-specific genetic associations with systolic and diastolic BP z-scores, and self-reported hypertension in women (n=194174) and men (n=167020) from the UK Biobank, using inverse-variance weighting meta-analysis. We conducted sensitivity analyses using other MR methods, including multivariable MR adjusted for childhood obesity proxied by body mass index (BMI). We used late pubertal growth as a validation outcome. Results AAM (beta per one-year later = -0.030 [95% confidence interval (CI) -0.055, -0.005] and AVB (beta -0.058 [95% CI -0.100, -0.015]) were inversely associated with systolic BP independent of childhood BMI, as were diastolic BP (-0.035 [95% CI -0.060, -0.009] for AAM and -0.046 [95% CI -0.089, -0.004] for AVB) and self-reported hypertension (odds ratios 0.89 [95% CI 0.84, 0.95] for AAM and 0.87 [95% CI 0.79, 0.96] for AVB). AAM and AVB were positively associated with late pubertal growth, as expected. The results were robust to sensitivity analysis using other MR methods. Conclusion Timing of pubertal maturation was associated with adulthood BP independent of childhood BMI, highlighting the role of pubertal maturation timing in midlife BP.

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