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38,233 result(s) for "Genome-Wide Association Study"
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Genetic studies of body mass index yield new insights for obesity biology
Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci ( P  < 5 × 10 −8 ), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis. A genome-wide association study and Metabochip meta-analysis of body mass index (BMI) detects 97 BMI-associated loci, of which 56 were novel, and many loci have effects on other metabolic phenotypes; pathway analyses implicate the central nervous system in obesity susceptibility and new pathways such as those related to synaptic function, energy metabolism, lipid biology and adipogenesis. Genetic correlates of obesity In the second of two Articles in this issue from the GIANT Consortium, Elizabeth Speliotes and collegues conducted a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), commonly used to define obesity and assess adiposity, to find 97 BMI-associated loci, of which 56 were novel. Many of these loci have significant effects on other metabolic phenotypes. The 97 loci account for about 2.7% of BMI variation, and genome-wide estimates suggest common variation accounts for more than 20% of BMI variation. Pathway analyses implicate the central nervous system in obesity susceptibility including synaptic function, glutamate signaling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.
The power of genetic diversity in genome-wide association studies of lipids
Increased blood lipid levels are heritable risk factors of cardiovascular disease with varied prevalence worldwide owing to different dietary patterns and medication use 1 . Despite advances in prevention and treatment, in particular through reducing low-density lipoprotein cholesterol levels 2 , heart disease remains the leading cause of death worldwide 3 . Genome-wideassociation studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease. However, most previous GWAS 4 – 23 have been conducted in European ancestry populations and may have missed genetic variants that contribute to lipid-level variation in other ancestry groups. These include differences in allele frequencies, effect sizes and linkage-disequilibrium patterns 24 . Here we conduct a multi-ancestry, genome-wide genetic discovery meta-analysis of lipid levels in approximately 1.65 million individuals, including 350,000 of non-European ancestries. We quantify the gain in studying non-European ancestries and provide evidence to support the expansion of recruitment of additional ancestries, even with relatively small sample sizes. We find that increasing diversity rather than studying additional individuals of European ancestry results in substantial improvements in fine-mapping functional variants and portability of polygenic prediction (evaluated in approximately 295,000 individuals from 7 ancestry groupings). Modest gains in the number of discovered loci and ancestry-specific variants were also achieved. As GWAS expand emphasis beyond the identification of genes and fundamental biology towards the use of genetic variants for preventive and precision medicine 25 , we anticipate that increased diversity of participants will lead to more accurate and equitable 26 application of polygenic scores in clinical practice. A genome-wide association meta-analysis study of blood lipid levels in roughly 1.6 million individuals demonstrates the gain of power attained when diverse ancestries are included to improve fine-mapping and polygenic score generation, with gains in locus discovery related to sample size.
Multi-ethnic genome-wide association study for atrial fibrillation
Atrial fibrillation (AF) affects more than 33 million individuals worldwide 1 and has a complex heritability 2 . We conducted the largest meta-analysis of genome-wide association studies (GWAS) for AF to date, consisting of more than half a million individuals, including 65,446 with AF. In total, we identified 97 loci significantly associated with AF, including 67 that were novel in a combined-ancestry analysis, and 3 that were novel in a European-specific analysis. We sought to identify AF-associated genes at the GWAS loci by performing RNA-sequencing and expression quantitative trait locus analyses in 101 left atrial samples, the most relevant tissue for AF. We also performed transcriptome-wide analyses that identified 57 AF-associated genes, 42 of which overlap with GWAS loci. The identified loci implicate genes enriched within cardiac developmental, electrophysiological, contractile and structural pathways. These results extend our understanding of the biological pathways underlying AF and may facilitate the development of therapeutics for AF. This large, multi-ethnic genome-wide association study identifies 97 loci significantly associated with atrial fibrillation. These loci are enriched for genes involved in cardiac development, electrophysiology, structure and contractile function.
A genome-wide association study of anorexia nervosa
Anorexia nervosa (AN) is a complex and heritable eating disorder characterized by dangerously low body weight. Neither candidate gene studies nor an initial genome-wide association study (GWAS) have yielded significant and replicated results. We performed a GWAS in 2907 cases with AN from 14 countries (15 sites) and 14 860 ancestrally matched controls as part of the Genetic Consortium for AN (GCAN) and the Wellcome Trust Case Control Consortium 3 (WTCCC3). Individual association analyses were conducted in each stratum and meta-analyzed across all 15 discovery data sets. Seventy-six (72 independent) single nucleotide polymorphisms were taken forward for in silico (two data sets) or de novo (13 data sets) replication genotyping in 2677 independent AN cases and 8629 European ancestry controls along with 458 AN cases and 421 controls from Japan. The final global meta-analysis across discovery and replication data sets comprised 5551 AN cases and 21 080 controls. AN subtype analyses (1606 AN restricting; 1445 AN binge–purge) were performed. No findings reached genome-wide significance. Two intronic variants were suggestively associated: rs9839776 ( P =3.01 × 10 −7 ) in SOX2OT and rs17030795 ( P =5.84 × 10 −6 ) in PPP3CA . Two additional signals were specific to Europeans: rs1523921 ( P =5.76 × 10 − 6 ) between CUL3 and FAM124B and rs1886797 ( P =8.05 × 10 − 6 ) near SPATA13 . Comparing discovery with replication results, 76% of the effects were in the same direction, an observation highly unlikely to be due to chance ( P =4 × 10 −6 ), strongly suggesting that true findings exist but our sample, the largest yet reported, was underpowered for their detection. The accrual of large genotyped AN case-control samples should be an immediate priority for the field.
Genetic identification of cell types underlying brain complex traits yields insights into the etiology of Parkinson’s disease
Genome-wide association studies have discovered hundreds of loci associated with complex brain disorders, but it remains unclear in which cell types these loci are active. Here we integrate genome-wide association study results with single-cell transcriptomic data from the entire mouse nervous system to systematically identify cell types underlying brain complex traits. We show that psychiatric disorders are predominantly associated with projecting excitatory and inhibitory neurons. Neurological diseases were associated with different cell types, which is consistent with other lines of evidence. Notably, Parkinson’s disease was genetically associated not only with cholinergic and monoaminergic neurons (which include dopaminergic neurons) but also with enteric neurons and oligodendrocytes. Using post-mortem brain transcriptomic data, we confirmed alterations in these cells, even at the earliest stages of disease progression. Our study provides an important framework for understanding the cellular basis of complex brain maladies, and reveals an unexpected role of oligodendrocytes in Parkinson’s disease. Integration of GWAS and single-cell transcriptomic data from the entire nervous system systematically identifies cell types underlying brain complex traits and provides insights into the etiology of Parkinson’s disease.
Metabolite‐based genome‐wide association study enables dissection of the flavonoid decoration pathway of wheat kernels
Summary The marriage of metabolomic approaches with genetic design has proven a powerful tool in dissecting diversity in the metabolome and has additionally enhanced our understanding of complex traits. That said, such studies have rarely been carried out in wheat. In this study, we detected 805 metabolites from wheat kernels and profiled their relative contents among 182 wheat accessions, conducting a metabolite‐based genome‐wide association study (mGWAS) utilizing 14 646 previously described polymorphic SNP markers. A total of 1098 mGWAS associations were detected with large effects, within which 26 candidate genes were tentatively designated for 42 loci. Enzymatic assay of two candidates indicated they could catalyse glucosylation and subsequent malonylation of various flavonoids and thereby the major flavonoid decoration pathway of wheat kernel was dissected. Moreover, numerous high‐confidence genes associated with metabolite contents have been provided, as well as more subdivided metabolite networks which are yet to be explored within our data. These combined efforts presented the first step towards realizing metabolomics‐associated breeding of wheat.
Genetic diversity fuels gene discovery for tobacco and alcohol use
Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury 1 – 4 . These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries 5 . Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction. A multi-ancestry meta-regression study analyses diverse genome-wide association studies and genome loci associated with tobacco and alcohol use.
Multi-omics approaches to disease
High-throughput technologies have revolutionized medical research. The advent of genotyping arrays enabled large-scale genome-wide association studies and methods for examining global transcript levels, which gave rise to the field of “integrative genetics”. Other omics technologies, such as proteomics and metabolomics, are now often incorporated into the everyday methodology of biological researchers. In this review, we provide an overview of such omics technologies and focus on methods for their integration across multiple omics layers. As compared to studies of a single omics type, multi-omics offers the opportunity to understand the flow of information that underlies disease.
A natural promoter variation of SlBBX31 confers enhanced cold tolerance during tomato domestication
Summary Cold stress affects crop growth and productivity worldwide. Understanding the genetic basis of cold tolerance in germplasms is critical for crop improvement. Plants can coordinate environmental stimuli of light and temperature to regulate cold tolerance. However, it remains unknown which gene in germplasms could have such function. Here, we utilized genome‐wide association study (GWAS) to investigate the cold tolerance of wild and cultivated tomato accessions and discovered that increased cold tolerance is accompanied with tomato domestication. We further identified a 27‐bp InDel in the promoter of the CONSTANS‐like transcription factor (TF) SlBBX31 is significantly linked with cold tolerance. Coincidentally, a key regulator of light signalling, SlHY5, can directly bind to the SlBBX31 promoter to activate SlBBX31 transcription while the 27‐bp InDel can prevent S1HY5 from transactivating SlBBX31. Parallel to these findings, we observed that the loss of function of SlBBX31 results in impaired tomato cold tolerance. SlBBX31 can also modulate the cold‐induced expression of several ERF TFs including CBF2 and DREBs. Therefore, our study has uncovered that SlBBX31 is possibly selected during tomato domestication for cold tolerance regulation, providing valuable insights for the development of hardy tomato varieties.
A small secreted protein in Zymoseptoria tritici is responsible for avirulence on wheat cultivars carrying the Stb6 resistance gene
Zymoseptoria tritici is the causal agent of Septoria tritici blotch, a major pathogen of wheat globally and the most damaging pathogen of wheat in Europe. A gene-for-gene (GFG) interaction between Z. tritici and wheat cultivars carrying the Stb6 resistance gene has been postulated for many years, but the genes have not been identified. We identified AvrStb6 by combining quantitative trait locus mapping in a cross between two Swiss strains with a genome-wide association study using a natural population of c. 100 strains from France. We functionally validated AvrStb6 using ectopic transformations. AvrStb6 encodes a small, cysteine-rich, secreted protein that produces an avirulence phenotype on wheat cultivars carrying the Stb6 resistance gene. We found 16 nonsynonymous single nucleotide polymorphisms among the tested strains, indicating that AvrStb6 is evolving very rapidly. AvrStb6 is located in a highly polymorphic subtelomeric region and is surrounded by transposable elements, which may facilitate its rapid evolution to overcome Stb6 resistance. AvrStb6 is the first avirulence gene to be functionally validated in Z. tritici, contributing to our understanding of avirulence in apoplastic pathogens and the mechanisms underlying GFG interactions between Z. tritici and wheat.