Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk.

Blood pressure is a heritable trait influenced by several biological pathways and responsive to environmental stimuli. Over one billion people worldwide have hypertension (≥140 mm Hg systolic blood pressure or  ≥90 mm Hg diastolic blood pressure). Even small increments in blood pressure are associated with an increased risk of cardiovascular events. This genome-wide association study of systolic and diastolic blood pressure, which used a multi-stage design in 200,000 individuals of European descent, identified sixteen novel loci: six of these loci contain genes previously known or suspected to regulate blood pressure (GUCY1A3-GUCY1B3, NPR3-C5orf23, ADM, FURIN-FES, GOSR2, GNAS-EDN3); the other ten provide new clues to blood pressure physiology. A genetic risk score based on 29 genome-wide significant variants was associated with hypertension, left ventricular wall thickness, stroke and coronary artery disease, but not kidney disease or kidney function. We also observed associations with blood pressure in East Asian, South Asian and African ancestry individuals. Our findings provide new insights into the genetics and biology of blood pressure, and suggest potential novel therapeutic pathways for cardiovascular disease prevention

Meta-analysis of genome-wide association studies for extraversion:Findings from the Genetics of Personality Consortium

Extraversion is a relatively stable and heritable personality trait associated with numerous psychosocial, lifestyle and health outcomes. Despite its substantial heritability, no genetic variants have been detected in previous genome-wide association (GWA) studies, which may be due to relatively small sample sizes of those studies. Here, we report on a large meta-analysis of GWA studies for extraversion in 63,030 subjects in 29 cohorts. Extraversion item data from multiple personality inventories were harmonized across inventories and cohorts. No genome-wide significant associations were found at the single nucleotide polymorphism (SNP) level but there was one significant hit at the gene level for a long non-coding RNA site (LOC101928162). Genome-wide complex trait analysis in two large cohorts showed that the additive variance explained by common SNPs was not significantly different from zero, but polygenic risk scores, weighted using linkage information, significantly predicted extraversion scores in an independent cohort. These results show that extraversion is a highly polygenic personality trait, with an architecture possibly different from other complex human traits, including other personality traits. Future studies are required to further determine which genetic variants, by what modes of gene action, constitute the heritable nature of extraversion

Cardiovascular risk scores in the prediction of subclinical atherosclerosis in young adults: evidence from the cardiovascular risk in a young Finns study

AIM: To study the utility of risk scores in the prediction of subclinical atherosclerosis in young adults. Methods AND Results: Participants were 2204 healthy Finnish adults aged 24-39 years in 2001 from a population-based follow-up study Cardiovascular Risk in Young Finns. We examined the performance of the Framingham, Reynolds, Systematic Coronary Risk Evaluation (SCORE), PROCAM, and Finrisk cardiovascular risk scores to predict subclinical atherosclerosis, that is carotid artery intima-media thickness (IMT) and plaque, carotid artery distensibility (CDist), and brachial artery flow-mediated dilatation (FMD) 6 years later. In a 6-year prediction of high IMT (highest decile or plaque), areas under the receiver operating characteristic curves (AUC) for baseline Finrisk (0.733), SCORE (0.726), PROCAM (0.712), and Reynolds (0.729) risk scores were similar as for Framingham risk score (0.728, P always ≥0.15). All risk scores had a similar discrimination in predicting low CDist (lowest decile) (0.652, 0.642, 0.639, 0.658, 0.652 respectively, P always ≥0.41). In the prediction of low FMD (lowest decile), Finrisk, PROCAM, Reynolds, and Framingham scores had similar AUCs (0.578, 0.594, 0.582, 0.568, P always ≥0.08) and SCORE discriminated slightly better (AUC=0.596, P<0.05). The prediction of subclinical outcomes was consistent when estimated from other statistical measures of discrimination, reclassification, and calibration. Conclusion: Cardiovascular disease risk scores had equal value in predicting subclinical atherosclerosis measured by IMT and CDist in young adults. SCORE was more accurate in predicting low FMD than Framingham risk score

Non-native and native shrubs have differing impacts on species diversity and composition of associated plant communities

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Lifestyle factors and site-specific risk of hip fracture in community dwelling older women – a 13-year prospective population-based cohort study

<p>Abstract</p> <p>Background</p> <p>Several risk factors are associated to hip fractures. It seems that different hip fracture types have different etiologies. In this study, we evaluated the lifestyle-related risk factors for cervical and trochanteric hip fractures in older women over a 13-year follow-up period.</p> <p>Methods</p> <p>The study design was a prospective, population-based study consisting of 1681 women (mean age 72 years). Seventy-three percent (n = 1222) participated in the baseline measurements, including medical history, leisure-time physical activity, smoking, and nutrition, along with body anthropometrics and functional mobility. Cox regression was used to identify the independent predictors of cervical and trochanteric hip fractures.</p> <p>Results</p> <p>During the follow-up, 49 cervical and 31 trochanteric fractures were recorded. The women with hip fractures were older, taller, and thinner than the women with no fractures (p < 0.05). Low functional mobility was an independent predictor of both cervical and trochanteric fractures (HR = 3.4, 95% CI 1.8-6.6, and HR = 5.3, 95% CI 2.5-11.4, respectively). Low baseline physical activity was associated with an increased risk of hip fracture, especially in the cervical region (HR = 2.5, 95% CI 1.3-4.9). A decrease in cervical fracture risk (p = 0.002) was observed with physically active individuals compared to their less active peers (categories: very low or low, moderate, and high). Moderate coffee consumption and hypertension decreased the risk of cervical fractures (HR = 0.4, 95% CI 0.2-0.8, for both), while smoking was a predisposing factor for trochanteric fractures (HR = 3.2, 95% CI 1.1-9.3).</p> <p>Conclusions</p> <p>Impaired functional mobility, physical inactivity, and low body mass may increase the risk for hip fractures with different effects at the cervical and trochanteric levels.</p

Three Levels of Ethical Influences on Selling Behavior and Performance: Synergies and Tensions

In general, the business ethics literature has treated the conceptual domains and outcomes of macro-level (industrial), meso-level (organizational), and micro-level (individual) ethical influence separately. However, this singular treatment ignores the synergies and tensions that can arise across these different types of ethical influence. Using sales as a research context, the current study argues that all three ethical frames of references are important in shaping employee behavior and performance and, as such, should be examined simultaneously. The findings show that industrial ethical climate and salesperson moral equity are positively associated with salesperson customer orientation. In addition, industrial and organizational ethical norms have a stronger joint effect on customer orientation than either ethical climate alone. More specifically, a more ethical organizational climate enhances the positive effects of the industrial ethical climate on customer orientation. Furthermore, whereas salesperson moral equity is significantly associated with salesperson customer orientation, strong moral equity beliefs in situations requiring adaptive selling result in weaker sales outcomes. This study concludes with a set of theoretical and actionable implications, as well as a discussion of future research avenues

Integrative approaches for large-scale transcriptome-wide association studies

Many genetic variants influence complex traits by modulating gene expression, thus altering the abundance of one or multiple proteins. Here we introduce a powerful strategy that integrates gene expression measurements with summary association statistics from large-scale genome-wide association studies (GWAS) to identify genes whose cis-regulated expression is associated with complex traits. We leverage expression imputation from genetic data to perform a transcriptome-wide association study (TWAS) to identify significant expression-trait associations. We applied our approaches to expression data from blood and adipose tissue measured in â 1/43,000 individuals overall. We imputed gene expression into GWAS data from over 900,000 phenotype measurements to identify 69 new genes significantly associated with obesity-related traits (BMI, lipids and height). Many of these genes are associated with relevant phenotypes in the Hybrid Mouse Diversity Panel. Our results showcase the power of integrating genotype, gene expression and phenotype to gain insights into the genetic basis of complex traits