Genome-wide prediction methods for detecting genetic effects of donor chromosome segments in introgression populations

AbstractDifferences between sexes contribute to variation in the levels of fasting glucose and insulin. Epidemiological studies established a higher prevalence of impaired fasting glucose in men and impaired glucose tolerance in women, however, the genetic component underlying this phenomenon is not established. We assess sex-dimorphic (73,089/50,404 women and 67,506/47,806 men) and sex-combined (151,188/105,056 individuals) fasting glucose/fasting insulin genetic effects via genome-wide association study meta-analyses in individuals of European descent without diabetes. Here we report sex dimorphism in allelic effects on fasting insulin at IRS1 and ZNF12 loci, the latter showing higher RNA expression in whole blood in women compared to men. We also observe sex-homogeneous effects on fasting glucose at seven novel loci. Fasting insulin in women shows stronger genetic correlations than in men with waist-to-hip ratio and anorexia nervosa. Furthermore, waist-to-hip ratio is causally related to insulin resistance in women, but not in men. These results position dissection of metabolic and glycemic health sex dimorphism as a steppingstone for understanding differences in genetic effects between women and men in related phenotypes.

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Evidence of Shared Genome-Wide Additive Genetic Effects on Interpersonal Trauma Exposure and Generalized Vulnerability to Drug Dependence in a Population of Substance Users

Journal of Traumatic Stress ◽

10.1002/jts.22103 ◽

2016 ◽

Vol 29 (3) ◽

pp. 197-204 ◽

Cited By ~ 2

Author(s):

Rohan H. C. Palmer ◽

Nicole R. Nugent ◽

Leslie A. Brick ◽

Cinnamon L. Bidwell ◽

John E. McGeary ◽

...

Keyword(s):

Drug Dependence ◽

Trauma Exposure ◽

Interpersonal Trauma ◽

Genetic Effects ◽

Substance Users ◽

Genome Wide ◽

Additive Genetic Effects

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Genome-wide association meta-analysis of childhood and adolescent internalising symptoms

10.1101/2020.09.11.20175026 ◽

2020 ◽

Author(s):

Eshim S Jami ◽

Anke R Hammerschlag ◽

Hill F Ip ◽

Andrea G Allegrini ◽

Beben Benyamin ◽

...

Keyword(s):

Confidence Intervals ◽

Meta Analysis ◽

Genetic Correlations ◽

Genetic Effects ◽

Childhood Aggression ◽

Genome Wide Association ◽

Childhood And Adolescence ◽

Obsessive Compulsive ◽

Compulsive Disorder ◽

Genome Wide

Internalising symptoms in childhood and adolescence are as heritable as adult depression and anxiety, yet little is known of their molecular basis. This genome-wide association meta-analysis of internalising symptoms included repeated observations from 64,641 individuals, aged between 3 and 18. The N-weighted meta-analysis of overall internalising symptoms (INToverall) detected no genome-wide significant hits and showed low SNP heritability (1.66%, 95% confidence intervals 0.84-2.48%, Neffective=132,260). Stratified analyses showed rater-based heterogeneity in genetic effects, with self-reported internalising symptoms showing the highest heritability (5.63%, 95% confidence intervals 3.08-8.18%). Additive genetic effects on internalising symptoms appeared stable over age, with overlapping estimates of SNP heritability from early-childhood to adolescence. Gene-based analyses showed significant associations with three genes: WNT3 (p=1.13×10-06), CCL26 (p=1.88×10-06), and CENPO (p=2.54×10-06). Of these, WNT3 was previously associated with neuroticism, with which INToverall also shared a strong genetic correlation (rg=0.76). Genetic correlations were also observed with adult anxiety, depression, and the wellbeing spectrum (|rg|> 0.70), as well as with insomnia, loneliness, attention-deficit hyperactivity disorder, autism, and childhood aggression (range |rg|=0.42-0.60), whereas there were no robust associations with schizophrenia, bipolar disorder, obsessive-compulsive disorder, or anorexia nervosa. Overall, childhood and adolescent internalising symptoms share substantial genetic vulnerabilities with adult internalising disorders and other childhood psychiatric traits, which could explain both the persistence of internalising symptoms over time, and the high comorbidity amongst childhood psychiatric traits. Reducing phenotypic heterogeneity in childhood samples will be key in paving the way to future GWAS success.

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Genetic effect estimates in case-control studies when a continuous variable is omitted from the model

10.1101/756015 ◽

2019 ◽

Author(s):

Ying Sheng ◽

Chiung-Yu Huang ◽

Siarhei Lobach ◽

Lydia Zablotska ◽

Iryna Lobach ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Large Scale ◽

False Positive Rate ◽

Continuous Variable ◽

Genetic Effects ◽

Data Availability ◽

Conditional Density ◽

Link Type ◽

Genome Wide

ABSTRACTLarge-scale genome-wide analyses scans provide massive volumes of genetic variants on large number of cases and controls that can be used to estimate the genetic effects. Yet, the sets of non-genetic variables available in publicly available databases are often brief. It is known that omitting a continuous variable from a logistic regression model can result in biased estimates of odds ratios (OR) (e.g., Gail et al (1984), Neuhaus et al (1993), Hauck et al (1991), Zeger et al (1988)). We are interested to assess what information is needed to recover the bias in the OR estimate of genotype due to omitting a continuous variable in settings when the actual values of the omitted variable are not available. We derive two estimating procedures that can recover the degree of bias based on a conditional density of the omitted variable or knowing the distribution of the omitted variable. Importantly, our derivations show that omitting a continuous variable can result in either under- or over-estimation of the genetic effects. We performed extensive simulation studies to examine bias, variability, false positive rate, and power in the model that omits a continuous variable. We show the application to two genome-wide studies of Alzheimer’s disease.Data Availability StatementThe data that support the findings of this study are openly available in the Database of Genotypes and Phenotypes at [https://www.ncbi.nlm.nih.gov/projects/gap/cgibin/study.cgi?study_id=phs000372.v1.p1], reference number [phs000372.v1.p1] and at the Alzheimer’s Disease Neuroimaging Initiative http://adni.loni.usc.edu/.

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An Analysis of Polygenes Affecting Wing Shape on Chromosome 2 inDrosophila melanogaster

Genetics ◽

10.1093/genetics/159.3.1045 ◽

2001 ◽

Vol 159 (3) ◽

pp. 1045-1057 ◽

Cited By ~ 5

Author(s):

Kenneth Weber ◽

Robert Eisman ◽

Shawn Higgins ◽

Lisa Morey ◽

April Patty ◽

...

Keyword(s):

Drosophila Melanogaster ◽

Transposable Element ◽

Genetic Effects ◽

Wing Shape ◽

Pleiotropic Effects ◽

Phenotypic Variance ◽

Chromosome 2 ◽

Additive Effects ◽

Chromosome Segments ◽

Small Additive

AbstractGenetic effects on an index of wing shape on chromosome 2 of Drosophila melanogaster were mapped using isogenic recombinants with transposable element markers. At least 10 genes with small additive effects are dispersed evenly along the chromosome. Many interactions exist, with only small net effects in homozygous recombinants and little effect on phenotypic variance. Heterozygous chromosome segments show almost no dominance. Pleiotropic effects on leg shape are only minor. At first view, wing shape genes form a rather homogeneous class, but certain complexities remain unresolved.

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PREDICTION OF PHENOTYPIC AND GENOTYPIC VALUES BY BLUP/GWS AND NEURAL NETWORKS

Revista Caatinga ◽

10.1590/1983-21252018v31n301rc ◽

2018 ◽

Vol 31 (3) ◽

pp. 532-540 ◽

Cited By ~ 2

Author(s):

ALISSON ESDRAS COUTINHO ◽

DIOGO GONÇALVES NEDER ◽

MAIRYKON COÊLHO DA SILVA ◽

ELIANE CRISTINA ARCELINO ◽

SILVAN GOMES DE BRITO ◽

...

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Breeding Cycle ◽

Prediction Methods ◽

Best Linear Unbiased Predictor ◽

Entire Genome ◽

Genomic Breeding ◽

Breeding Values ◽

Genome Wide ◽

Best Linear Unbiased

ABSTRACT Genome-wide selection (GWS) uses simultaneously the effect of the thousands markers covering the entire genome to predict genomic breeding values for individuals under selection. The possible benefits of GWS are the reduction of the breeding cycle, increase in gains per unit of time, and decrease of costs. However, the success of the GWS is dependent on the choice of the method to predict the effects of markers. Thus, the objective of this work was to predict genomic breeding values (GEBV) through artificial neural networks (ANN), based on the estimation of the effect of the markers, compared to the Ridge Regression-Best Linear Unbiased Predictor/Genome Wide Selection (RR-BLUP/GWS). Simulations were performed by software R to provide correlations concerning ANN and RR-BLUP/GWS. The prediction methods were evaluated using correlations between phenotypic and genotypic values and predicted GEBV. The results showed the superiority of the ANN in predicting GEBV in simulations with higher and lower marker densities, with higher levels of linkage disequilibrium and heritability.

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Genome-wide exploration identifies sex-specific genetic effects of alleles upstream NPY to increase the risk of severe periodontitis in men

Journal Of Clinical Periodontology ◽

10.1111/jcpe.12317 ◽

2014 ◽

Vol 41 (12) ◽

pp. 1115-1121 ◽

Cited By ~ 29

Author(s):

Sandra Freitag-Wolf ◽

Henrik Dommisch ◽

Christian Graetz ◽

Yvonne Jockel-Schneider ◽

Inga Harks ◽

...

Keyword(s):

Genetic Effects ◽

Genome Wide ◽

Severe Periodontitis

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Education, Smoking, and Cohort Change: Forwarding a Multidimensional Theory of the Environmental Moderation of Genetic Effects

American Sociological Review ◽

10.1177/0003122418785368 ◽

2018 ◽

Vol 83 (4) ◽

pp. 802-832 ◽

Cited By ~ 17

Author(s):

Robbee Wedow ◽

Meghan Zacher ◽

Brooke M. Huibregtse ◽

Kathleen Mullan Harris ◽

Benjamin W. Domingue ◽

...

Keyword(s):

Environmental Conditions ◽

Genetic Effects ◽

Environment Interaction ◽

Birth Cohorts ◽

The United Kingdom ◽

Gene By Environment Interactions ◽

Genome Wide ◽

The Social ◽

Cohort Theory ◽

The Relationship

Sociologists interested in the effects of genes on complex social outcomes claim environmental conditions structure when and how genes matter, but they have only studied environmental moderation of genetic effects on single traits at a time (gene-by-environment interactions). In this article, we propose that the social environment can also transform the genetic link between two traits. Taking the relationship between educational attainment and smoking as an exemplary case, we use genome-wide methods to examine whether genetic variants linked to education are also linked to smoking, and whether the strength of this relationship varies across birth cohorts. Results suggest that the genetic relationship between education and smoking is stronger among U.S. adults born between 1974 and 1983 than among those born between 1920 and 1959. These results are supported by replication in additional data from the United Kingdom. Environmental conditions that differ across birth cohorts may result in the bundling of genetic effects on multiple outcomes, as anticipated by classic cohort theory. We introduce genetic correlation-by-environment interaction [(rG)xE] as a sociologically-informed model that will become especially useful as data for more well-powered analyses become available.

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