scholarly journals The Genetic Overlap Between Hair and Eye Color

2016 ◽  
Vol 19 (6) ◽  
pp. 595-599 ◽  
Author(s):  
Bochao D. Lin ◽  
Gonneke Willemsen ◽  
Abdel Abdellaoui ◽  
Meike Bartels ◽  
Erik A. Ehli ◽  
...  
Keyword(s):  
The Netherlands ◽  
Genome Wide Association Study ◽  
Population Sample ◽  
Genetic Correlations ◽  
Complex Trait ◽  
Eye Color ◽  
Red Hair ◽  
Dark Hair ◽  
Genome Wide ◽  
Blue Eyes

We identified the genetic variants for eye color by Genome-Wide Association Study (GWAS) in a Dutch Caucasian family-based population sample and examined the genetic correlation between hair and eye color using data from unrelated participants from the Netherlands Twin Register. With the Genome-wide Complex Trait Analysis software package, we found strong genetic correlations between various combinations of hair and eye colors. The strongest positive correlations were found for blue eyes with blond hair (0.87) and brown eyes with dark hair (0.71), whereas blue eyes with dark hair and brown eyes with blond hair showed the strongest negative correlations (-0.64 and -0.94, respectively). Red hair with green/hazel eyes showed the weakest correlation (-0.14). All analyses were corrected for age and sex, and we explored the effects of correcting for principal components (PCs) that represent ancestry and describe the genetic stratification of the Netherlands. When including the first three PCs as covariates, the genetic correlations between the phenotypes disappeared. This is not unexpected since hair and eye colors strongly indicate the ancestry of an individual. This makes it difficult to separate the effects of population stratification and the true genetic effects of variants on these particular phenotypes.

scholarly journals Genome-wide association study in almost 195,000 individuals identifies 50 previously unidentified genetic loci for eye color

2021 ◽  
Vol 7 (11) ◽  
pp. eabd1239
Author(s):  
Mark Simcoe ◽  
Ana Valdes ◽  
Fan Liu ◽  
Nicholas A. Furlotte ◽  
David M. Evans ◽  
...  
Keyword(s):  
Association Study ◽  
Genome Wide Association Study ◽  
Color Variation ◽  
Genome Wide Association ◽  
Nucleotide Polymorphisms ◽  
Melanin Pigmentation ◽  
Eye Color ◽  
Human Eye ◽  
Genome Wide ◽  
Genomic Regions

Human eye color is highly heritable, but its genetic architecture is not yet fully understood. We report the results of the largest genome-wide association study for eye color to date, involving up to 192,986 European participants from 10 populations. We identify 124 independent associations arising from 61 discrete genomic regions, including 50 previously unidentified. We find evidence for genes involved in melanin pigmentation, but we also find associations with genes involved in iris morphology and structure. Further analyses in 1636 Asian participants from two populations suggest that iris pigmentation variation in Asians is genetically similar to Europeans, albeit with smaller effect sizes. Our findings collectively explain 53.2% (95% confidence interval, 45.4 to 61.0%) of eye color variation using common single-nucleotide polymorphisms. Overall, our study outcomes demonstrate that the genetic complexity of human eye color considerably exceeds previous knowledge and expectations, highlighting eye color as a genetically highly complex human trait.

scholarly journals Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Vasiliki Lagou ◽  
◽  
Reedik Mägi ◽  
Jouke- Jan Hottenga ◽  
Harald Grallert ◽  
...  
Keyword(s):  
Genome Wide Association Study ◽  
Fasting Glucose ◽  
Genetic Correlations ◽  
Epidemiological Studies ◽  
Genetic Effects ◽  
Fasting Insulin ◽  
Sex Dimorphism ◽  
Waist To Hip Ratio ◽  
Genome Wide ◽  
Meta Analyses

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.

A Proteome-Wide Association Study Identified Candidate Human Brain Proteins Associated with Coffee Consumption

2021 ◽  
Author(s):  
Chun'e Li ◽  
Xiao Liang ◽  
Yumeng Jia ◽  
Yan Wen ◽  
Huijie Zhang ◽  
...  
Keyword(s):  
Human Brain ◽  
Association Study ◽  
Plasma Proteins ◽  
Genome Wide Association Study ◽  
Genetic Correlations ◽  
Coffee Consumption ◽  
Genetic Associations ◽  
Brain Proteins ◽  
Genome Wide ◽  
Brain Proteome

Abstract Background Increasing evidence suggests the association between caffeine and the brain and nervous system. However, there is limited research on the genetic associations between coffee consumption subtypes and brain proteome, plasma proteomes, and peripheral metabolites. Methods First, proteome-wide association study (PWAS) of coffee consumption subtypes was performed by integrating two independent genome-wide association study (GWAS) datasets (91,462–502,650 subjects) with two reference human brain proteomes (ROS/MAP and Banner), by using the FUSION pipeline. Second, transcriptome-wide association study (TWAS) analysis of coffee consumption subtypes was conducted by integrating the two gene expression weight references (RNAseq and splicing) of brain RNA-seq and the two GWAS datasets (91,462–502,650 subjects) of coffee consumption subtypes. Finally, we used the LD Score Regression (LDSC) analysis to evaluate the genetic correlations of coffee consumption subtypes with plasma proteomes and peripheral metabolites. Results For the traits related to coffee consumption, we identified 3 common PWAS proteins, such as MADD (P PWAS−Banner−dis=0.0114, P PWAS−ROS/MAP−rep =0.0489). In addition, 11 common TWAS genes were found in two cohorts, such as ARPC2 (P TWAS−splicing−dis =2063×10− 12, P TWAS−splicing−dis =1.25×10− 10, P TWAS−splicing−dis =1.24e-08, P TWAS−splicing−rep =3.25×10− 9 and P TWAS−splicing−rep =3.42×10− 13). Importantly, we have identified 8 common genes between PWAS and TWAS, such as ALDH2 (P PWAS−banner−rep =1.22×10− 22, PTWAS− splicing−dis = 4.54×10− 92). For the LDSC analysis of human plasma proteome, we identified 11 plasma proteins, such as CHL1 (P dis = 0.0151, P rep =0.0438). For the LDSC analysis of blood metabolites, 5 metabolites have been found, such as myo-inositol (P dis = 0.0073, P dis = 0.0152, P dis =0.0414, P rep =0.0216). Conclusions We identified several brain proteins and genes associated with coffee consumption subtypes. In addition, we also detected several candidate plasma proteins and metabolites related to these subtypes.

scholarly journals Genome-wide association study identifies 48 common genetic variants associated with handedness

2019 ◽  
Author(s):  
Gabriel Cuellar Partida ◽  
Joyce Y Tung ◽  
Nicholas Eriksson ◽  
Eva Albrecht ◽  
Fazil Aliev ◽  
...  
Keyword(s):  
Association Study ◽  
Genetic Variants ◽  
Complex Traits ◽  
Genome Wide Association Study ◽  
Genetic Correlations ◽  
Genome Wide Association ◽  
Left Handedness ◽  
Left Handed ◽  
Genome Wide ◽  
Common Genetic Variants

AbstractHandedness, a consistent asymmetry in skill or use of the hands, has been studied extensively because of its relationship with language and the over-representation of left-handers in some neurodevelopmental disorders. Using data from the UK Biobank, 23andMe and 32 studies from the International Handedness Consortium, we conducted the world’s largest genome-wide association study of handedness (1,534,836 right-handed, 194,198 (11.0%) left-handed and 37,637 (2.1%) ambidextrous individuals). We found 41 genetic loci associated with left-handedness and seven associated with ambidexterity at genome-wide levels of significance (P < 5×10−8). Tissue enrichment analysis implicated the central nervous system and brain tissues including the hippocampus and cerebrum in the etiology of left-handedness. Pathways including regulation of microtubules, neurogenesis, axonogenesis and hippocampus morphology were also highlighted. We found suggestive positive genetic correlations between being left-handed and some neuropsychiatric traits including schizophrenia and bipolar disorder. SNP heritability analyses indicated that additive genetic effects of genotyped variants explained 5.9% (95% CI = 5.8% – 6.0%) of the underlying liability of being left-handed, while the narrow sense heritability was estimated at 12% (95% CI = 7.2% – 17.7%). Further, we show that genetic correlation between left-handedness and ambidexterity is low (rg = 0.26; 95% CI = 0.08 – 0.43) implying that these traits are largely influenced by different genetic mechanisms. In conclusion, our findings suggest that handedness, like many other complex traits is highly polygenic, and that the genetic variants that predispose to left-handedness may underlie part of the association with some psychiatric disorders that has been observed in multiple observational studies.

scholarly journals GWAS with principal component analysis identifies a gene comprehensively controlling rice architecture

2019 ◽  
Vol 116 (42) ◽  
pp. 21262-21267 ◽  
Author(s):  
Kenji Yano ◽  
Yoichi Morinaka ◽  
Fanmiao Wang ◽  
Peng Huang ◽  
Sayaka Takehara ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Genome Wide Association Study ◽  
Crop Yields ◽  
Principal Component ◽  
Complex Trait ◽  
Component Analysis ◽  
Gene Encoding ◽  
Signal Suppression ◽  
Genome Wide ◽  
A Genome

Elucidation of the genetic control of rice architecture is crucial due to the global demand for high crop yields. Rice architecture is a complex trait affected by plant height, tillering, and panicle morphology. In this study, principal component analysis (PCA) on 8 typical traits related to plant architecture revealed that the first principal component (PC), PC1, provided the most information on traits that determine rice architecture. A genome-wide association study (GWAS) using PC1 as a dependent variable was used to isolate a gene encoding rice, SPINDLY (OsSPY), that activates the gibberellin (GA) signal suppression protein SLR1. The effect of GA signaling on the regulation of rice architecture was confirmed in 9 types of isogenic plant having different levels of GA responsiveness. Further population genetics analysis demonstrated that the functional allele of OsSPY associated with semidwarfism and small panicles was selected in the process of rice breeding. In summary, the use of PCA in GWAS will aid in uncovering genes involved in traits with complex characteristics.

scholarly journals An atlas of genetic correlations between psychiatric disorders and human blood plasma proteome

2020 ◽  
Vol 63 (1) ◽  
Author(s):  
Shiqiang Cheng ◽  
Fanglin Guan ◽  
Mei Ma ◽  
Lu Zhang ◽  
Bolun Cheng ◽  
...  
Keyword(s):  
Psychiatric Disorders ◽  
Plasma Proteins ◽  
Genome Wide Association Study ◽  
Genetic Relationships ◽  
Genetic Correlations ◽  
Tumor Necrosis Factor Receptor ◽  
Autism Spectrum ◽  
Human Blood Plasma ◽  
Plasma Proteome ◽  
Genome Wide

Abstract Background. Psychiatric disorders are a group of complex psychological syndromes with high prevalence. Recent studies observed associations between altered plasma proteins and psychiatric disorders. This study aims to systematically explore the potential genetic relationships between five major psychiatric disorders and more than 3,000 plasma proteins. Methods. The genome-wide association study (GWAS) datasets of attention deficiency/hyperactive disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), schizophrenia (SCZ) and major depressive disorder (MDD) were driven from the Psychiatric GWAS Consortium. The GWAS datasets of 3,283 human plasma proteins were derived from recently published study, including 3,301 study subjects. Linkage disequilibrium score (LDSC) regression analysis were conducted to evaluate the genetic correlations between psychiatric disorders and each of the 3,283 plasma proteins. Results. LDSC observed several genetic correlations between plasma proteins and psychiatric disorders, such as ADHD and lysosomal Pro-X carboxypeptidase (p value = 0.015), ASD and extracellular superoxide dismutase (Cu-Zn; p value = 0.023), BD and alpha-N-acetylgalactosaminide alpha-2,6-sialyltransferase 6 (p value = 0.007), MDD and trefoil factor 1 (p value = 0.011), and SCZ and insulin-like growth factor-binding protein 6 (p value = 0.011). Additionally, we detected four common plasma proteins showing correlation evidence with both BD and SCZ, such as tumor necrosis factor receptor superfamily member 1B (p value = 0.012 for BD, p value = 0.011 for SCZ). Conclusions. This study provided an atlas of genetic correlations between psychiatric disorders and plasma proteome, providing novel clues for pathogenetic and biomarkers, therapeutic studies of psychiatric disorders.

scholarly journals Single nucleotide polymorphism heritability and differential patterns of genetic overlap between inattention and four neurocognitive factors in youth

2020 ◽  
pp. 1-11
Author(s):  
Lauren Micalizzi ◽  
Leslie A. Brick ◽  
Marisa E. Marraccini ◽  
Chelsie E. Benca-Bachman ◽  
Rohan H.C. Palmer ◽  
...  
Keyword(s):  
Single Nucleotide Polymorphism ◽  
Executive Function ◽  
Social Cognition ◽  
Genome Wide Association Study ◽  
Population Sample ◽  
Nucleotide Polymorphism ◽  
Single Nucleotide ◽  
Genome Wide ◽  
Genetic Overlap ◽  
Complex Cognition

Abstract Theoretical models of attention-deficit/hyperactivity disorder implicate neurocognitive dysfunction, yet neurocognitive functioning covers a range of abilities that may not all be linked with inattention. This study (a) investigated the single nucleotide polymorphism (SNP) heritability (h2SNP) of inattention and aspects of neurocognitive efficiency (memory, social cognition, executive function, and complex cognition) based on additive genome-wide effects; (b) examined if there were shared genetic effects among inattention and each aspect of neurocognitive efficiency; and (c) conducted an exploratory genome-wide association study to identify genetic regions associated with inattention. The sample included 3,563 participants of the Philadelphia Neurodevelopmental Cohort, a general population sample aged 8–21 years who completed the Penn Neurocognitive Battery. Data on inattention was obtained with the Kiddie Schedule of Affective Disorders (adapted). Genomic relatedness matrix restricted maximum likelihood was implemented in genome-wide complex trait analysis. Analyses revealed significant h2SNP for inattention (20%, SE = 0.08), social cognition (13%, SE = 0.08), memory (17%, SE = 0.08), executive function (25%, SE = 0.08), and complex cognition (24%, SE = 0.08). There was a positive genetic correlation (0.67, SE = 0.37) and a negative residual covariance (−0.23, SE = 0.06) between inattention and social cognition. No SNPs reached genome-wide significance for inattention. Results suggest specificity in genetic overlap among inattention and different aspects of neurocognitive efficiency.

scholarly journals Analysis of genotype by environment interactions in a maize mapping population

2021 ◽  
Author(s):  
Asher I Hudson ◽  
Sarah G Odell ◽  
Pierre Dubreuil ◽  
Marie-Helene Tixier ◽  
Sebastien Praud ◽  
...  
Keyword(s):  
Genome Wide Association Study ◽  
Genetic Correlations ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
Crop Breeding ◽  
Genotype By Environment Interactions ◽  
Genotype By Environment ◽  
Genome Wide ◽  
A Genome ◽  
Genetic Covariances

Genotype by environment interactions are a significant challenge for crop breeding as well as being important for understanding the genetic basis of environmental adaptation. In this study, we analyzed genotype by environment interaction in a maize multi-parent advanced generation intercross population grown across five environments. We found that genotype by environment interactions contributed as much as genotypic effects to the variation in some agronomically important traits. In order to understand how genetic correlations between traits change across environments, we estimated the genetic variance-covariance matrix in each environment. Changes in genetic covariances between traits across environments were common, even among traits that show low genotype by environment variance. We also performed a genome-wide association study to identify markers associated with genotype by environment interactions but found only a small number of significantly associated markers, possibly due to the highly polygenic nature of genotype by environment interactions in this population.

scholarly journals An Atlas of Genetic Correlations across Human Diseases and Traits

2015 ◽  
Author(s):  
Brendan Bulik-Sullivan ◽  
Hilary K Finucane ◽  
Verneri Anttila ◽  
Alexander Gusev ◽  
Felix R Day ◽  
...  
Keyword(s):  
Anorexia Nervosa ◽  
Educational Attainment ◽  
Genetic Correlation ◽  
Complex Traits ◽  
Genome Wide Association Study ◽  
Genetic Correlations ◽  
Significant Snps ◽  
Modeling Framework ◽  
Genome Wide ◽  
Meta Analyses

Identifying genetic correlations between complex traits and diseases can provide useful etiological insights and help prioritize likely causal relationships. The major challenges preventing estimation of genetic correlation from genome-wide association study (GWAS) data with current methods are the lack of availability of individual genotype data and widespread sample overlap among meta-analyses. We circumvent these difficulties by introducing a technique for estimating genetic correlation that requires only GWAS summary statistics and is not biased by sample overlap. We use our method to estimate 300 genetic correlations among 25 traits, totaling more than 1.5 million unique phenotype measurements. Our results include genetic correlations between anorexia nervosa and schizophrenia/ body mass index and associations between educational attainment and several diseases. These results highlight the power of a polygenic modeling framework, since there currently are no genome-wide significant SNPs for anorexia nervosa and only three for educational attainment.

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