scholarly journals Genetic architecture of early childhood growth phenotypes gives insights into their link with later obesity

2017 ◽  
Author(s):  
N. Maneka G. De Silva ◽  
Sylvain Sebert ◽  
Alexessander Couto Alves ◽  
Ulla Sovio ◽  
Shikta Das ◽  
...  
Keyword(s):  
Early Childhood ◽  
Genome Wide Association Study ◽  
Genetic Correlations ◽  
Subcutaneous Fat ◽  
Peak Height ◽  
Early Growth ◽  
Growth Patterns ◽  
Childhood Growth ◽  
Genome Wide ◽  
Meta Analyses

AbstractEarly childhood growth patterns are associated with adult metabolic health, but the underlying mechanisms are unclear. We performed genome-wide meta-analyses and follow-up in up to 22,769 European children for six early growth phenotypes derived from longitudinal data: peak height and weight velocities, age and body mass index (BMI) at adiposity peak (AP ~9 months) and rebound (AR ~5-6 years). We identified four associated loci (P< 5x10−8): LEPR/LEPROT with BMI at AP, FTO and TFAP2B with Age at AR and GNPDA2 with BMI at AR. The observed AR-associated SNPs at FTO, TFAP2B and GNPDA2 represent known adult BMI-associated variants. The common BMI at AP associated variant at LEPR/LEPROT was not associated with adult BMI but was associated with LEPROT gene expression levels, especially in subcutaneous fat (P<2x10−51). We identify strong positive genetic correlations between early growth and later adiposity traits, and analysis of the full discovery stage results for Age at AR revealed enrichment for insulin-like growth factor 1 (IGF-1) signaling and apolipoprotein pathways. This genome-wide association study suggests mechanistic links between early childhood growth and adiposity in later childhood and adulthood, highlighting these early growth phenotypes as potential targets for the prevention of obesity.

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.

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.

scholarly journals Genome-wide association study reveals a dynamic role of common genetic variation in infant and early childhood growth

2018 ◽  
Author(s):  
Øyvind Helgeland ◽  
Marc Vaudel ◽  
Petur B. Juliusson ◽  
Oddgeir Lingaas Holmen ◽  
Julius Juodakis ◽  
...  
Keyword(s):  
Early Childhood ◽  
Genetic Variation ◽  
Association Study ◽  
Genome Wide Association Study ◽  
Developmental Stages ◽  
Genome Wide Association ◽  
Transient Effect ◽  
Childhood Growth ◽  
Common Variation ◽  
Genome Wide

Infant and childhood growth are dynamic processes characterized by drastic changes in fat mass and body mass index (BMI) at distinct developmental stages. To elucidate how genetic variation influences these processes, we performed the first genome-wide association study (GWAS) of BMI measurements at 12 time points from birth to eight years of age (9,286 children, 74,105 measurements) in the Norwegian Mother and Child Cohort Study (MoBa) with replication in 5,235 children (41,502 measurements). We identified five loci associated with BMI at distinct developmental stages with different patterns of association. Notably, we identified a novel transient effect in the leptin receptor (LEPR) locus, with no effect at birth, increasing effect on BMI in infancy, peaking at 6-12 months (rs2767486, P6m = 2.0 × 10−21, β6m = 0.16) and little effect after age five. A similar transient effect was found near the leptin gene (LEP), peaking at 1.5 years of age (rs10487505, P1.5y = 1.3 × 10−8, β1.5y = 0.079). Both signals are protein quantitative trait loci (pQTLs) for soluble LEPR and LEP in plasma in adults and independent from signals associated with other adult traits mapped to the respective genes, suggesting novel key roles of common variation in the leptin signaling pathway for healthy infant growth. Hence, our longitudinal analysis uncovers a complex and dynamic influence of common variation on BMI during infant and early childhood growth, dominated by the LEP-LEPR axis in infancy.

scholarly journals Genomic analysis of diet composition finds novel loci and associations with health and lifestyle

2018 ◽  
Author(s):  
S Fleur W Meddens ◽  
Ronald de Vlaming ◽  
Peter Bowers ◽  
Casper AP Burik ◽  
Richard Karlsson Linnér ◽  
...  
Keyword(s):  
Genome Wide Association Study ◽  
Genetic Correlations ◽  
Caloric Intake ◽  
Genomic Analysis ◽  
Caloric Content ◽  
Genetic Associations ◽  
Neighborhood Poverty ◽  
Genome Wide ◽  
Meta Analyses

AbstractWe conducted genome-wide association study (GWAS) meta-analyses of relative caloric intake from fat, protein, carbohydrates and sugar in over 235,000 individuals. We identified 21 approximately independent lead SNPs. Relative protein intake exhibits the strongest relationships with poor health, including positive genetic associations with obesity, type 2 diabetes, and heart disease (rg ≈ 0.15 – 0.5). Relative carbohydrate and sugar intake have negative genetic correlations with waist circumference, waist-hip ratio, and neighborhood poverty (|rg| ≈ 0.1 – 0.3). Overall, our results show that the relative intake of each macronutrient has a distinct genetic architecture and pattern of genetic correlations suggestive of health implications beyond caloric content.

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 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.

Early childhood growth patterns and school-age respiratory resistance, fractional exhaled nitric oxide and asthma

2016 ◽  
Vol 27 (8) ◽  
pp. 854-860 ◽  
Author(s):  
Maribel Casas ◽  
Herman T. den Dekker ◽  
Claudia J. Kruithof ◽  
Irwin K. Reiss ◽  
Martine Vrijheid ◽  
...  
Keyword(s):  
Nitric Oxide ◽  
Early Childhood ◽  
Exhaled Nitric Oxide ◽  
Growth Patterns ◽  
School Age ◽  
Respiratory Resistance ◽  
Fractional Exhaled Nitric Oxide ◽  
Childhood Growth

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 Genome-wide association study meta-analysis of the Alcohol Use Disorder Identification Test (AUDIT) in two population-based cohorts (N=141,932)

2018 ◽  
Author(s):  
Sandra Sanchez-Roige ◽  
Abraham A. Palmer ◽  
Pierre Fontanillas ◽  
Sarah L. Elson ◽  
Mark J. Adams ◽  
...  
Keyword(s):  
Alcohol Use ◽  
Alcohol Dependence ◽  
Genome Wide Association Study ◽  
Meta Analysis ◽  
Genetic Correlations ◽  
Population Based ◽  
Major Depressive ◽  
Genome Wide ◽  
Disorder Identification ◽  
Dsm Iv

AbstractAlcohol use disorders (AUD) are common conditions that have enormous social and economic consequences. We obtained quantitative measures using the Alcohol Use Disorder Identification Test (AUDIT) from two population-based cohorts of European ancestry: UK Biobank (UKB; N=121,604) and 23andMe (N=20,328) and performed a genome-wide association study (GWAS) meta-analysis. We also performed GWAS for AUDIT items 1-3, which focus on consumption (AUDIT-C), and for items 4-10, which focus on the problematic consequences of drinking (AUDIT-P). The GWAS meta-analysis of AUDIT total score identified 10 associated risk loci. Novel associations localized to genes including JCAD and SLC39A13; we also replicated previously identified signals in the genes ADH1B, ADH1C, KLB, and GCKR. The dimensions of AUDIT showed positive genetic correlations with alcohol consumption (rg=0.76-0.92) and Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) alcohol dependence (rg=0.33-0.63). AUDIT-P and AUDIT-C showed significantly different patterns of association across a number of traits, including psychiatric disorders. AUDIT-P was positively genetically correlated with schizophrenia (rg=0.22, p=3.0×10−10), major depressive disorder (rg=0.26, p=5.6×10−3), and attention-deficit/hyperactivity disorder (ADHD; rg=0.23, p=1.1×10−5), whereas AUDIT-C was negatively genetically correlated with major depressive disorder (rg=−0.24, p=3.7×10−3) and ADHD (rg=−0.10, p=1.8×10−2). We also used the AUDIT data in the UKB to identify thresholds for dichotomizing AUDIT total score that optimize genetic correlations with DSM-IV alcohol dependence. Coding individuals with AUDIT total score of ≤4 as controls and ≥12 as cases produced a high genetic correlation with DSM-IV alcohol dependence (rg=0.82, p=3.2×10−6) while retaining most subjects. We conclude that AUDIT scores ascertained in population-based cohorts can be used to explore the genetic basis of both alcohol consumption and AUD.

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