scholarly journals Genetics of hypertension: discoveries from the bench to human populations

2014 ◽  
Vol 306 (1) ◽  
pp. F1-F11 ◽  
Author(s):  
Nora Franceschini ◽  
Thu H. Le
Keyword(s):  
Association Studies ◽  
Complex Trait ◽  
Experimental Models ◽  
Sodium Reabsorption ◽  
Human Populations ◽  
Genome Wide Association Studies ◽  
Blood Pressure Homeostasis ◽  
Genome Wide ◽  
Clinical Hypertension ◽  
Renal Sodium Reabsorption

Hypertension is a complex trait that is influenced by both heritable and environmental factors. The search for genes accounting for the susceptibility to hypertension has driven parallel efforts in human research and in research using experimental animals in controlled environmental settings. Evidence from rodent models of genetic hypertension and human Mendelian forms of hypertension and hypotension have yielded mechanistic insights into the pathways that are perturbed in blood pressure homeostasis, most of which converge at the level of renal sodium reabsorption. However, the bridging of evidence from these very diverse approaches to identify mechanisms underlying hypertension susceptibility and the translation of these findings to human populations and public health remain a challenge. Furthermore, findings from genome-wide association studies still require functional validation in experimental models. In this review, we highlight results and implications from key studies in experimental and clinical hypertension to date.

scholarly journals CAUSALdb: a database for disease/trait causal variants identified using summary statistics of genome-wide association studies

2019 ◽  
Author(s):  
Jianhua Wang ◽  
Dandan Huang ◽  
Yao Zhou ◽  
Hongcheng Yao ◽  
Huanhuan Liu ◽  
...  
Keyword(s):  
Fine Mapping ◽  
Genetic Variants ◽  
Association Studies ◽  
Complex Trait ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Genome Wide ◽  
Credible Sets ◽  
Causal Variants

Abstract Genome-wide association studies (GWASs) have revolutionized the field of complex trait genetics over the past decade, yet for most of the significant genotype-phenotype associations the true causal variants remain unknown. Identifying and interpreting how causal genetic variants confer disease susceptibility is still a big challenge. Herein we introduce a new database, CAUSALdb, to integrate the most comprehensive GWAS summary statistics to date and identify credible sets of potential causal variants using uniformly processed fine-mapping. The database has six major features: it (i) curates 3052 high-quality, fine-mappable GWAS summary statistics across five human super-populations and 2629 unique traits; (ii) estimates causal probabilities of all genetic variants in GWAS significant loci using three state-of-the-art fine-mapping tools; (iii) maps the reported traits to a powerful ontology MeSH, making it simple for users to browse studies on the trait tree; (iv) incorporates highly interactive Manhattan and LocusZoom-like plots to allow visualization of credible sets in a single web page more efficiently; (v) enables online comparison of causal relations on variant-, gene- and trait-levels among studies with different sample sizes or populations and (vi) offers comprehensive variant annotations by integrating massive base-wise and allele-specific functional annotations. CAUSALdb is freely available at http://mulinlab.org/causaldb.

scholarly journals Contributions of common genetic variants to risk of schizophrenia among individuals of African and Latino ancestry

2019 ◽  
Vol 25 (10) ◽  
pp. 2455-2467 ◽  
Author(s):  
Tim B. Bigdeli ◽  
◽  
Giulio Genovese ◽  
Penelope Georgakopoulos ◽  
Jacquelyn L. Meyers ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Association Studies ◽  
Large Fraction ◽  
African Ancestry ◽  
Common Variant ◽  
Human Populations ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Common Genetic Variants

Abstract Schizophrenia is a common, chronic and debilitating neuropsychiatric syndrome affecting tens of millions of individuals worldwide. While rare genetic variants play a role in the etiology of schizophrenia, most of the currently explained liability is within common variation, suggesting that variation predating the human diaspora out of Africa harbors a large fraction of the common variant attributable heritability. However, common variant association studies in schizophrenia have concentrated mainly on cohorts of European descent. We describe genome-wide association studies of 6152 cases and 3918 controls of admixed African ancestry, and of 1234 cases and 3090 controls of Latino ancestry, representing the largest such study in these populations to date. Combining results from the samples with African ancestry with summary statistics from the Psychiatric Genomics Consortium (PGC) study of schizophrenia yielded seven newly genome-wide significant loci, and we identified an additional eight loci by incorporating the results from samples with Latino ancestry. Leveraging population differences in patterns of linkage disequilibrium, we achieve improved fine-mapping resolution at 22 previously reported and 4 newly significant loci. Polygenic risk score profiling revealed improved prediction based on trans-ancestry meta-analysis results for admixed African (Nagelkerke’s R2 = 0.032; liability R2 = 0.017; P < 10−52), Latino (Nagelkerke’s R2 = 0.089; liability R2 = 0.021; P < 10−58), and European individuals (Nagelkerke’s R2 = 0.089; liability R2 = 0.037; P < 10−113), further highlighting the advantages of incorporating data from diverse human populations.

scholarly journals Signals of polygenic adaptation on height have been overestimated due to uncorrected population structure in genome-wide association studies

2018 ◽  
Author(s):  
Mashaal Sohail ◽  
Robert M. Maier ◽  
Andrea Ganna ◽  
Alex Bloemendal ◽  
Alicia R. Martin ◽  
...  
Keyword(s):  
Population Structure ◽  
Association Studies ◽  
Meta Analysis ◽  
Human Populations ◽  
Genome Wide Association Studies ◽  
Multiple Traits ◽  
Large Numbers ◽  
Genome Wide ◽  
Polygenic Adaptation ◽  
The Uk

AbstractGenetic predictions of height differ among human populations and these differences are too large to be explained by genetic drift. This observation has been interpreted as evidence of polygenic adaptation. Differences across populations were detected using SNPs genome-wide significantly associated with height, and many studies also found that the signals grew stronger when large numbers of subsignificant SNPs were analyzed. This has led to excitement about the prospect of analyzing large fractions of the genome to detect subtle signals of selection and claims of polygenic adaptation for multiple traits. Polygenic adaptation studies of height have been based on SNP effect size measurements in the GIANT Consortium meta-analysis. Here we repeat the height analyses in the UK Biobank, a much more homogeneously designed study. Our results show that polygenic adaptation signals based on large numbers of SNPs below genome-wide significance are extremely sensitive to biases due to uncorrected population structure.

scholarly journals Multi-breed Genetic Parameters and Genome-wide Association Studies for Mortality Rate at Birth in Pigs

2021 ◽  
Author(s):  
Meijing An ◽  
Guangliang Zhou ◽  
Yang Li ◽  
Tao Xiang ◽  
Yunlong Ma ◽  
...  
Keyword(s):  
Mortality Rate ◽  
Genetic Parameters ◽  
Association Studies ◽  
Genetic Correlations ◽  
Complex Trait ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Gene Expressions ◽  
Genome Wide ◽  
Piglet Mortality

Abstract Background Piglet mortality is an economically important complex trait that impacts sow prolificacy in the pig industry. The genetic parameters estimations and genome-wide association studies will help us to better understand the genetic fundamentals of piglet mortality. However, compared with other economically important traits, a little breakthrough in the genetic analyses of the trait has been achieved. Results In this study, we used multi-breed data sets from Yorkshire, Landrace, and Duroc sows and characterized the genetic and genomic properties of mortality rate at birth by treating each parity as a different trait. The heritability of mortality rate from parity I to III were estimated to be 0.0630, 0.1031, and 0.1140, respectively. The phenotypic and genetic correlations with its component traits were all positive with ranges from 0.0897 to 0.9054, and 0.2388 to 0.9999, respectively. Integrating the results, we identified 21 loci that were detected at least by two tools from standard MLM, FarmCPU, BLINK and mrMLM, and these loci were annotated to 22 genes. The annotations revealed that the gene expressions were associated with the reproductive system, nervous system, digestive system, and embryonic development, which are reasonably related to the piglet mortality. Conclusions In brief, the genetic properties of piglet mortality at birth were reported. These findings are expected to provide much information for understanding the genetic and genomic fundamentals of farrowing mortality and also identify candidate molecular markers for breeding practice.

scholarly journals Cross-species alcohol dependence-associated gene networks: Co-analysis of mouse brain gene expression and human genome-wide association data

2018 ◽  
Author(s):  
Kristin M. Mignogna ◽  
Silviu A. Bacanu ◽  
Brien P. Riley ◽  
Aaron R. Wolen ◽  
Michael F. Miles
Keyword(s):  
Gene Expression ◽  
Alcohol Dependence ◽  
Mouse Brain ◽  
Gene Networks ◽  
Association Studies ◽  
Complex Trait ◽  
Genome Wide Association ◽  
Model Organisms ◽  
Genome Wide Association Studies ◽  
Genome Wide

AbstractGenome-wide association studies on alcohol dependence, by themselves, have yet to account for the estimated heritability of the disorder and provide incomplete mechanistic understanding of this complex trait. Integrating brain ethanol-responsive gene expression networks from model organisms with human genetic data on alcohol dependence could aid in identifying dependence-associated genes and functional networks in which they are involved. This study used a modification of the Edge-Weighted Dense Module Searching for genome-wide association studies (EW-dmGWAS) approach to co-analyze whole-genome gene expression data from ethanol-exposed mouse brain tissue, human protein-protein interaction databases and alcohol dependence-related genome-wide association studies. Results revealed novel ethanol-regulated and alcohol dependence-associated gene networks in prefrontal cortex, nucleus accumbens, and ventral tegmental area. Three of these networks were overrepresented with genome-wide association signals from an independent dataset. These networks were significantly overrepresented for gene ontology categories involving several mechanisms, including actin filament-based activity, transcript regulation, Wnt and Syndecan-mediated signaling, and ubiquitination. Together, these studies provide novel insight for brain mechanisms contributing to alcohol dependence.

scholarly journals PheLiGe: an interactive database of billions of human genotype–phenotype associations

2020 ◽  
Vol 49 (D1) ◽  
pp. D1347-D1350 ◽  
Author(s):  
Tatiana I Shashkova ◽  
Eugene D Pakhomov ◽  
Denis D Gorev ◽  
Lennart C Karssen ◽  
Peter K Joshi ◽  
...  
Keyword(s):  
Biological Function ◽  
Association Studies ◽  
Complex Trait ◽  
Easy Access ◽  
Genome Wide Association Studies ◽  
Web Interface ◽  
Regional Patterns ◽  
Protein Levels ◽  
Genome Wide ◽  
Causal Genes

Abstract Genome-wide association studies have provided a vast array of publicly available SNP × phenotype association results. However, they are often in disparate repositories and formats, making downstream analyses difficult and time consuming. PheLiGe (https://phelige.com) is a database that provides easy access to such results via a web interface. The underlying database currently stores &gt;75 billion genotype–phenotype associations from 7347 genome-wide and 1.2 million region-wide (e.g. cis-eQTL) association scans. The web interface allows for investigation of regional genotype-phenotype associations across many phenotypes, giving insights into the biological function affected by the variant in question. Furthermore, PheLiGe can compare regional patterns of association between different traits. This analysis can ascertain whether a co-association is due to pleiotropy or linkage. Moreover, comparison of association patterns for a complex trait of interest and gene expression and protein levels can implicate causal genes.

scholarly journals Quantifying genetic heterogeneity between continental populations for human height and body mass index

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jing Guo ◽  
Andrew Bakshi ◽  
Ying Wang ◽  
Longda Jiang ◽  
Loic Yengo ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Complex Traits ◽  
Association Studies ◽  
Significant Snps ◽  
Complex Trait ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Population Difference ◽  
Genome Wide

AbstractGenome-wide association studies (GWAS) in samples of European ancestry have identified thousands of genetic variants associated with complex traits in humans. However, it remains largely unclear whether these associations can be used in non-European populations. Here, we seek to quantify the proportion of genetic variation for a complex trait shared between continental populations. We estimated the between-population correlation of genetic effects at all SNPs ($$r_{g}$$ r g ) or genome-wide significant SNPs ($$r_{{g\left( {GWS} \right)}}$$ r g GWS ) for height and body mass index (BMI) in samples of European (EUR; $$n = 49,839$$ n = 49 , 839 ) and African (AFR; $$n = 17,426$$ n = 17 , 426 ) ancestry. The $$\hat{r}_{g}$$ r ^ g between EUR and AFR was 0.75 ($${\text{s}}.{\text{e}}. = 0.035$$ s . e . = 0.035 ) for height and 0.68 ($${\text{s}}.{\text{e}}. = 0.062$$ s . e . = 0.062 ) for BMI, and the corresponding $$\hat{r}_{{g\left( {GWS} \right)}}$$ r ^ g GWS was 0.82 ($${\text{s}}.{\text{e}}. = 0.030$$ s . e . = 0.030 ) for height and 0.87 ($${\text{s}}.{\text{e}}. = 0.064$$ s . e . = 0.064 ) for BMI, suggesting that a large proportion of GWAS findings discovered in Europeans are likely applicable to non-Europeans for height and BMI. There was no evidence that $$\hat{r}_{g}$$ r ^ g differs in SNP groups with different levels of between-population difference in allele frequency or linkage disequilibrium, which, however, can be due to the lack of power.

scholarly journals Epigenome-wide association study of serum urate reveals insights into urate co-regulation and the SLC2A9 locus

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Adrienne Tin ◽  
Pascal Schlosser ◽  
Pamela R. Matias-Garcia ◽  
Chris H. L. Thio ◽  
Roby Joehanes ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Complex Traits ◽  
Cardiometabolic Risk ◽  
Association Studies ◽  
Meta Analysis ◽  
Elevated Serum ◽  
Complex Trait ◽  
Serum Urate ◽  
Genome Wide Association Studies ◽  
Genome Wide

AbstractElevated serum urate levels, a complex trait and major risk factor for incident gout, are correlated with cardiometabolic traits via incompletely understood mechanisms. DNA methylation in whole blood captures genetic and environmental influences and is assessed in transethnic meta-analysis of epigenome-wide association studies (EWAS) of serum urate (discovery, n = 12,474, replication, n = 5522). The 100 replicated, epigenome-wide significant (p < 1.1E–7) CpGs explain 11.6% of the serum urate variance. At SLC2A9, the serum urate locus with the largest effect in genome-wide association studies (GWAS), five CpGs are associated with SLC2A9 gene expression. Four CpGs at SLC2A9 have significant causal effects on serum urate levels and/or gout, and two of these partly mediate the effects of urate-associated GWAS variants. In other genes, including SLC7A11 and PHGDH, 17 urate-associated CpGs are associated with conditions defining metabolic syndrome, suggesting that these CpGs may represent a blood DNA methylation signature of cardiometabolic risk factors. This study demonstrates that EWAS can provide new insights into GWAS loci and the correlation of serum urate with other complex traits.

scholarly journals Linkage disequilibrium and haplotype block patterns in popcorn populations

2019 ◽  
Author(s):  
Andréa Carla Bastos Andrade ◽  
José Marcelo Soriano Viana ◽  
Helcio Duarte Pereira ◽  
Vitor Batista Pinto ◽  
Fabyano Fonseca e Silva
Keyword(s):  
Linkage Disequilibrium ◽  
Genomic Selection ◽  
Association Studies ◽  
Breeding Population ◽  
Human Populations ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Haplotype Blocks ◽  
Genome Wide ◽  
Evolutionary Aspects

AbstractLinkage disequilibrium (LD) analysis provides information on evolutionary aspects of the populations and allows selecting populations and single nucleotide polymorphisms (SNPs) for association studies. Recently, haplotype blocks have been used to increase the power of quantitative trait loci detection in genome-wide association studies and the prediction accuracy with genomic selection. The objectives of this study were to compare the degree of LD, the LD decay, the LD decay extent, and the number and length of haplotype blocks in the populations and to elaborate the first LD map for maize, for elucidating if the maize chromosomes also had a pattern of interspaced regions of high and low rates of recombination. We used a biparental temperate population, a tropical synthetic, and a tropical breeding population, genotyped for approximately 75,000 SNPs. The level of LD expressed by the r2 values is surprisingly low (0.02, 0.04, and 0.04), but comparable to some non-isolated human populations. The general evidence is that the synthetic is the population with higher LD. It is not expected a significant advantage of haplotype-based association study and along generations genomic selection due to the reduced number of SNPs in the haplotype blocks (2 to 3). The results concerning LD decay (rapid decay after 5-10 kb) and LD decay extent (along up to 300 kb) are in the range observed with maize inbred line panels. Our most important result is that maize chromosomes had a pattern of regions of extensive LD interspaced with regions of low LD. However, our simple simulated LD map provides evidence that this pattern can reflect regions with differences of allele frequencies and LD level (expressed by D’) and not regions with high and low rates of recombination.

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