scholarly journals Polygenic Architecture of Human Neuroanatomical Diversity

2020 ◽  
Vol 30 (4) ◽  
pp. 2307-2320
Author(s):  
Anne Biton ◽  
Nicolas Traut ◽  
Jean-Baptiste Poline ◽  
Benjamin S Aribisala ◽  
Mark E Bastin ◽  
...  
Keyword(s):  
Genetic Variance ◽  
Meta Analysis ◽  
Genetic Correlations ◽  
Global Scale ◽  
Phenotypic Variance ◽  
Environmental Correlations ◽  
Genomic Architecture ◽  
Snp Data ◽  
Environmental Causes ◽  
The Uk

Abstract We analyzed the genomic architecture of neuroanatomical diversity using magnetic resonance imaging and single nucleotide polymorphism (SNP) data from >26 000 individuals from the UK Biobank project and 5 other projects that had previously participated in the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) consortium. Our results confirm the polygenic architecture of neuroanatomical diversity, with SNPs capturing from 40% to 54% of regional brain volume variance. Chromosomal length correlated with the amount of phenotypic variance captured, r ~ 0.64 on average, suggesting that at a global scale causal variants are homogeneously distributed across the genome. At a local scale, SNPs within genes (~51%) captured ~1.5 times more genetic variance than the rest, and SNPs with low minor allele frequency (MAF) captured less variance than the rest: the 40% of SNPs with MAF <5% captured <one fourth of the genetic variance. We also observed extensive pleiotropy across regions, with an average genetic correlation of rG ~ 0.45. Genetic correlations were similar to phenotypic and environmental correlations; however, genetic correlations were often larger than phenotypic correlations for the left/right volumes of the same region. The heritability of differences in left/right volumes was generally not statistically significant, suggesting an important influence of environmental causes in the variability of brain asymmetry. Our code is available athttps://github.com/neuroanatomy/genomic-architecture.

scholarly journals Polygenic architecture of human neuroanatomical diversity

2019 ◽  
Author(s):  
Anne Biton ◽  
Nicolas Traut ◽  
Jean-Baptiste Poline ◽  
Benjamin S. Aribisala ◽  
Mark E. Bastin ◽  
...  
Keyword(s):  
Genetic Variance ◽  
Genetic Correlations ◽  
Global Scale ◽  
Phenotypic Variance ◽  
Environmental Correlations ◽  
Genomic Architecture ◽  
Snp Data ◽  
Causal Variants ◽  
Environmental Causes ◽  
The Uk

AbstractWe analysed the genomic architecture of neuroanatomical diversity using magnetic resonance imaging and single nucleotide polymorphism (SNP) data from >26,000 individuals from the UK Biobank project and 5 other projects that had previously participated in the ENIGMA consortium. Our results confirm the polygenic architecture of neuroanatomical diversity, with SNPs capturing from 40% to 54% of regional brain volume variance. Chromosomal length correlated with the amount of phenotypic variance captured, r∼0.64 on average, suggesting that at a global scale causal variants are homogeneously distributed across the genome. At a local scale, SNPs within genes (∼51%) captured ∼1.5 times more genetic variance than the rest; and SNPs with low minor allele frequency (MAF) captured less variance than the rest: the 40% of SNPs with MAF<5% captured <1/4th of the genetic variance. We also observed extensive pleiotropy across regions, with an average genetic correlation of rG∼0.45. Genetic correlations were similar to phenotypic and environmental correlations, however, genetic correlations were often larger than phenotypic correlations for the left/right volumes of the same region. The heritability of differences in left/right volumes was generally not statistically significant, suggesting an important influence of environmental causes in the variability of brain asymmetry. Our code is available at https://github.com/neuroanatomy/genomic-architecture.

scholarly journals Genetic and environmental architecture of conscientiousness in adolescence

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yusuke Takahashi ◽  
Anqing Zheng ◽  
Shinji Yamagata ◽  
Juko Ando
Keyword(s):  
Individual Differences ◽  
Effortful Control ◽  
Genetic Variance ◽  
Genetic Factors ◽  
Common Factor ◽  
Genetic Correlations ◽  
Self Control ◽  
Genetic Analyses ◽  
Environmental Correlations ◽  
Per Se

AbstractUsing a genetically informative design (about 2000 twin pairs), we investigated the phenotypic and genetic and environmental architecture of a broad construct of conscientiousness (including conscientiousness per se, effortful control, self-control, and grit). These four different measures were substantially correlated; the coefficients ranged from 0.74 (0.72–0.76) to 0.79 (0.76–0.80). Univariate genetic analyses revealed that individual differences in conscientiousness measures were moderately attributable to additive genetic factors, to an extent ranging from 62 (58–65) to 64% (61–67%); we obtained no evidence that shared environmental influences were observed. Multivariate genetic analyses showed that for the four measures used to assess conscientiousness, genetic correlations were stronger than the corresponding non-shared environmental correlations, and that a latent common factor accounted for over 84% of the genetic variance. Our findings suggest that individual differences in the four measures of conscientiousness are not distinguishable at both the phenotypic and behavioural genetic levels, and that the overlap was substantially attributable to genetic factors.

The incorporation of fertility indices in genetic improvement programmes

2001 ◽  
Vol 26 (1) ◽  
pp. 237-249 ◽  
Author(s):  
J.E. Pryce ◽  
R.F. Veerkamp
Keyword(s):  
Genetic Variance ◽  
Selection Index ◽  
Genetic Correlations ◽  
Live Weight ◽  
Parameter Estimates ◽  
Phenotypic Variance ◽  
Production Traits ◽  
Genetic Progress ◽  
Detection Rates ◽  
Days Open

AbstractIn recent years there has been considerable genetic progress in milk production. Yet, increases in yield have been accompanied by an apparent lengthening of calving intervals, days open, days to first heat and a decline in conception rates, which appears to be both at the genetic and phenotypic level. Fertility has a high relative economic value compared to production traits such as protein, making it attractive to include in a breeding programme. To do this there needs to be genetic variance in fertility. Measures of fertility calculated from service dates have a small genetic compared to phenotypic variance, hence heritability estimates are small, typically less than 5%, although coefficients of genetic variance are comparable to those of production traits. Heritabilities of commencement of luteal activity determined using progesterone profiles are generally higher, and have been reported as being from 0.16 to 0.28, which could be because of a more precise quantification of genetic variance, as management influences such as delaying insemination and heat detection rates are excluded. However, it might not be the use of progesterone profiles alone, as days to first heat observed by farm staff has a heritability of 0.15. The most efficient way to breed for improved fertility is to construct a selection index using the genetic and phenotypic parameter estimates of all traits of interest in addition to their respective economic values. Index traits for fertility could include measures such as calving interval, days open, days to first service, or days to first heat but there may also be alternative measures. Examples include traits related to energy balance, such as live weight and condition score (change), both of which have higher heritabilities than fertility measures and have genetic correlations of sufficient magnitude to make genetic progress by using them feasible. To redress the balance between fertility and production, some countries already publish genetic evaluations of fertility including: Denmark, Finland, France, Germany, Israel, The Netherlands, Norway and Sweden.

scholarly journals Unraveling the genetic and environmental relationship between well-being and depressive symptoms throughout the lifespan

2018 ◽  
Author(s):  
Bart Baselmans ◽  
Yayouk Willems ◽  
Toos van Beijsterveldt ◽  
Lannie Ligthart ◽  
Gonneke WIllemsen ◽  
...  
Keyword(s):  
Depressive Symptoms ◽  
Genetic Predisposition ◽  
Genetic Correlations ◽  
Well Being ◽  
Phenotypic Correlation ◽  
Substantial Part ◽  
Phenotypic Variance ◽  
Environmental Correlations ◽  
The Relationship ◽  
Two Sides

Whether well-being and depressive symptoms can be considered as two sides of the same coin is widely debated. The aim of this study was to gain insight into the etiology of the association between well-being and depressive symptoms across the lifespan. In a cohort-sequential design, including data from 43,427 twins between age 7 and 99, we estimated the association between well-being and depressive symptoms throughout the lifespan and assessed genetic and environmental contributions to the observed overlap. For both well-being (range 31% –45%) and depressive symptoms (range 50%-61%), genetic factors explained a substantial part of the phenotypic variance across the lifespan. Correlations between well-being and depressive symptoms across ages ranged from -.34 in childhood to -.49 in adulthood. In children and adults (aged &gt;27), environmental effects explained 51% to 59% of the phenotypic correlation, while for adolescents and young adults strong genetic influences (60%-77%) on the association were observed. Moderate to high genetic correlations (ranging from 0.60 to 0.70) were observed in adolescence and adulthood, while in childhood environmental correlations were substantial but genetic correlations small. These results suggest that environmental factors are important in explaining the relationship between well-being and depressive symptoms in childhood, while from adolescence onwards a genetic predisposition for higher well-being is indicative for a genetic predisposition for lower depressive symptoms, and vice versa. These results provided more insights into the etiological underpinnings of well-being and depressive symptoms, possibly allowing to articulate better strategies for health promotion and resource allocation in the future.

scholarly journals Genetic parameters, phenotypic, genotypic and environmental correlations and genetic variability on sunflower in the Brazilian Savannah

2017 ◽  
Vol 47 (8) ◽  
Author(s):  
Ellen Grippi Lira ◽  
Renato Fernando Amabile ◽  
Marcelo Fagioli ◽  
Ana Paula Leite Montalvão
Keyword(s):  
Genetic Variability ◽  
Genetic Parameters ◽  
Environmental Control ◽  
Genetic Correlations ◽  
Phenotypic Selection ◽  
Phenotypic Variance ◽  
Environmental Correlations ◽  
High Genetic Variability ◽  
Brazilian Savannah ◽  
Main Component

ABSTRACT: Sunflower (Helianthus annuus L.) is an annual crop that stands out for its production of high quality oil and for an efficient selection, being necessary to estimate the components of genetic and phenotypic variance. This study aimed to estimate genetic parameters, phenotypic, genotypic and environmental correlations and genetic variability on sunflower in the Brazilian Savannah, evaluating the characters grain yield (YIELD), days to start flowering (DFL) based on flowering date in R5, chapter length (CL), weight of a thousand achenes (WTA), plant height (H) and oil content (OilC) of 16 sunflower genotypes. The experiment was conducted at Embrapa Cerrados, Planaltina, DF, situated at 15º 35’ 30”S latitude, 47º 42’ 30”W longitude and 1.007m above sea level, in soil classified as dystroferric Oxisol. The experimental design used was a complete randomized block with four replicates. The nature for the effects of genotypes and blocks was fixed. Except for the character chapter length, genetic variance was the main component of the phenotypic variance among the genotypes, indicating high genetic variability and experimental efficiency with proper environmental control. In absolute terms, the genetic correlations were superior to phenotypic and environmental. The high values reported for heritability and selective accuracy indicated efficiency of phenotypic selection. Results showed high genetic variability among genotypes, which may contribute to the genetic improvement of sunflower.

Response to selection in Australian Merino sheep. VI. Inheritance of abnormal staple crimp; estimates of phenotypic and genetic parameters

1975 ◽  
Vol 26 (2) ◽  
pp. 375 ◽  
Author(s):  
N Jackson ◽  
RE Chapman
Keyword(s):  
Body Weight ◽  
Unit Area ◽  
Genetic Correlations ◽  
Fibre Diameter ◽  
Phenotypic Variance ◽  
Correlated Responses ◽  
Environmental Correlations ◽  
Merino Sheep ◽  
Phenotypic Correlations ◽  
Fibre Number

The heritability of abnormal crimp in wool at various ages and the genetic and phenotypic cotreiations of crimp abnormality with several wool and body characters were estimated for Peppin Merino sheep. When examined by half-sib analyses of variance, the heritability of abnormal crimp scored at ages less than 4.5 years was low, whereas abnormality at 5.5 years and older was highly inherited. Heritabilities estimated by intra-sire dam-daughter regression analyses with fewer degrees of freedom did not show such a clear-cut pattern, although the estimates tended to increase with age. The genetic correlations of crimp abnormality scores at ages up to 4.5 years with scores at older ages were mainly low. Crimp abnormality scores at most ages had genetic correlations with wool and body characters at 15–16 months of age as follows: strong positive with fibre diameter, weak positive with greasy and clean wool weight, wrinkle score and staple length, and weak negative with fibre number. Genetic correlations with body weight, percentage clean yield, face cover score and crimp frequency were inconsistent. The phenotypic variance of crimp abnormality increased with age, owing almost entirely to an increase in the additive genetic variance. The environmental variance was approximately the same at all ages. Phenotypic correlations among crimp abnormality scores were generally higher between scores at close ages, and particularly at older ages. Crimp abnormality scores at all ages had positive phenotypic correlations with fibre diameter and wrinkle score and negative correlations with fibre number per unit area of skin and percentage clean yield.Crimp abnormality at old ages also had positive phenotypic correlations with greasy and clean wool weights. Environmental correlations of crimp abnormality with greasy wool weight, clean wool weight body weight and fibre number per unit area of skin were negative, and those with percentage clean yield and fibre number positive. Predicted correlated responses in crimp abnormality differed in some respects from correlated responses observed previously in groups of Peppin Merino sheep selected for high and low values of percentage clean yield, clean wool weight, fibre number per unit area of skin and fibre diameter. Methods of selection of sheep which would be expected to reduce crimp abnormality are outlined.

Genetic Regulation of Plasma Levels of Vitamin K-dependent Proteins Involved in Hemostasis

2001 ◽  
Vol 85 (01) ◽  
pp. 88-92 ◽  
Author(s):  
Laura Almasy ◽  
John Blangero ◽  
William Stone ◽  
Montse Borrell ◽  
Teresa Urrutia ◽  
...  
Keyword(s):  
Vitamin K ◽  
Plasma Levels ◽  
Critical Role ◽  
Genetic Correlations ◽  
Decomposition Analysis ◽  
Protein S ◽  
P Value ◽  
Phenotypic Variance ◽  
Environmental Correlation ◽  
Environmental Correlations

SummaryVitamin K-dependent proteins play a critical role in hemostasis. We have analysed the genetic and environmental correlations between measures of several vitamin K-dependent proteins in 21 Spanish extended families, including 397 individuals. Plasma functional levels of factors II, VII, IX, X, protein C and functional protein S were assayed in an automated coagulometer. Antigenic levels of total and free protein S were measured using an ELISA method. A maximum likelihood-based covariance decomposition analysis was used to assess the heritability of each trait and the genetic and environmental correlations between all possible pairs. All of the plasma levels had a significant genetic component (heritability) ranging from 22% to 52% of the phenotypic variance. Among the 28 possible pairs of genetic correlations, 18 were significant at a level of p <0.05 and six exhibited a p-value between 0.05 and 0.10. Positive environmental correlation was observed for 25 of the pairs (p <0.05). We conclude that genetic effects account for a large proportion of the observed phenotypic variation in vitamin K-dependent proteins. Some of the genes appear to pleiotropically influence all of these traits, since most pairs of phenotypes exhibit significant genetic correlation. However, since these phenotypes show a high degree of environmental correlation, it is also likely that the same environmental factors influence them co-jointly.

scholarly journals Estimation of non-additive genetic variance in human complex traits from a large sample of unrelated individuals

2020 ◽  
Author(s):  
Valentin Hivert ◽  
Julia Sidorenko ◽  
Florian Rohart ◽  
Michael E Goddard ◽  
Jian Yang ◽  
...  
Keyword(s):  
Complex Traits ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Sampling Variance ◽  
Analysis Model ◽  
Additive Variance ◽  
Snp Data ◽  
Causal Variants ◽  
The Uk ◽  
Epistatic Variance

AbstractNon-additive genetic variance for complex traits is traditionally estimated from data on relatives. It is notoriously difficult to estimate without bias in non-laboratory species, including humans, because of possible confounding with environmental covariance among relatives. In principle, non-additive variance attributable to common DNA variants can be estimated from a random sample of unrelated individuals with genome-wide SNP data. Here, we jointly estimate the proportion of variance explained by additive , dominance and additive-by-additive genetic variance in a single analysis model. We first show by simulations that our model leads to unbiased estimates and provide new theory to predict standard errors estimated using either least squares or maximum likelihood. We then apply the model to 70 complex traits using 254,679 unrelated individuals from the UK Biobank and 1.1M genotyped and imputed SNPs. We found strong evidence for additive variance (average across traits . In contrast, the average estimate of across traits was 0.001, implying negligible dominance variance at causal variants tagged by common SNPs. The average epistatic variance across the traits was 0.058, not significantly different from zero because of the large sampling variance. Our results provide new evidence that genetic variance for complex traits is predominantly additive, and that sample sizes of many millions of unrelated individuals are needed to estimate epistatic variance with sufficient precision.

scholarly journals Genetic Susceptibility to Pneumonia: A GWAS Meta-Analysis Between the UK Biobank and FinnGen

2021 ◽  
pp. 1-10
Author(s):  
Adrian I. Campos ◽  
Pik Kho ◽  
Karla X. Vazquez-Prada ◽  
Luis M. García-Marín ◽  
Nicholas G. Martin ◽  
...  
Keyword(s):  
Individual Differences ◽  
Meta Analysis ◽  
Genetic Correlations ◽  
Sensitivity Analyses ◽  
Smoking History ◽  
Chromosome 15 ◽  
Uk Biobank ◽  
Common Genetic Variants ◽  
Small Effect Size ◽  
The Uk

Abstract Pneumonia is a respiratory condition with complex etiology. Host genetic variation is thought to contribute to individual differences in susceptibility and symptom manifestation. Here, we analyze pneumonia data from the UK Biobank (14,780 cases and 439,096 controls) and FinnGen (9980 cases and 86,519 controls) and perform a genomewide association study meta-analysis. We use gene-based tests, colocalization, genetic correlation, latent causal variable (LCV) and polygenic prediction in an independent Australian sample (N = 5595) to draw insights into the etiology of pneumonia risk. We identify two independent loci on chromosome 15 (lead single-nucleotide polymorphisms rs2009746 and rs76474922) to be associated with pneumonia (p < 5e−8). Gene-based tests revealed 18 genes in chromosomes 15, 16 and 9, including IL127, PBX3, ApoB receptor (APOBR) and smoking related genes CHRNA3/5, statistically associated with pneumonia. We observed genetic correlations between pneumonia and cardiorespiratory, psychiatric and inflammatory related traits. LCV analysis suggests a strong genetic causal relationship with cardiovascular health phenotypes. Polygenic risk scores for pneumonia significantly predicted self-reported pneumonia in an independent sample, albeit with a small effect size (OR = 1.11 95% CI [1.04, 1.19], p < .05). Sensitivity analyses suggested the associations in chromosome 15 are mediated by smoking history, but the associations in chromosomes 16 and 9, and polygenic prediction were robust to adjustment for smoking. Altogether, our results highlight common genetic variants, genes and potential pathways that contribute to individual differences in susceptibility to pneumonia, and advance our understanding of the genetic factors underlying heterogeneity in respiratory medical outcomes.

scholarly journals Variance-quantitative trait loci enable systematic discovery of gene-environment interactions for cardiometabolic serum biomarkers

2021 ◽  
Author(s):  
Kenneth E Westerman ◽  
Timothy D Majarian ◽  
Franco Giulianini ◽  
Dong-Keun Jang ◽  
Jose C Florez ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Meta Analysis ◽  
Health Study ◽  
Small Subset ◽  
Phenotypic Variance ◽  
Gene Environment ◽  
Genome Wide ◽  
Trait Loci ◽  
The Uk

Gene-environment interactions (GEIs) represent the modification of genetic effects by environmental exposures and are critical for understanding disease and informing personalized medicine. GEIs often induce differential phenotypic variance across genotypes; these variance-quantitative trait loci (vQTLs) can be prioritized in a two-stage GEI detection strategy to greatly reduce the computational and statistical burden and enable testing of a broader range of exposures. We performed genome-wide vQTL analysis for 20 serum cardiometabolic biomarkers by multi-ancestry meta-analysis of 350,016 unrelated participants in the UK Biobank, identifying 182 independent locus-biomarker pairs (p < 4.5x10-9). Most vQTLs were concentrated in a small subset (4%) of loci with genome-wide significant main effects, and 44% replicated (p < 0.05) in the Women's Genome Health Study (N = 23,294). Next, we tested each vQTL for interaction across 2,380 exposures, identifying 846 significant GEIs (p < 2.4x10-7). Specific examples demonstrated interaction of triglyceride-associated variants with distinct body mass- versus body fat-related exposures as well as genotype-specific associations between alcohol consumption and liver stress at the ADH1B gene. Our catalog of vQTLs and GEIs is publicly available in an online portal.

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