The genetic basis of gout

2016 ◽  
Author(s):  
Tony R. Merriman
Keyword(s):  
Uric Acid ◽  
Genetic Variants ◽  
Genetic Basis ◽  
Histone Deacetylase Inhibitors ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Toll Like Receptor 4 ◽  
Genome Wide ◽  
Uric Acid Transporters ◽  
Genetically Determined

An individual’s risk of gout is determined by a complex relationship between inherited genetic variants and environmental exposures. Genetic variants that control hyperuricaemia and subsequent progression to clinical gout specify pathogenic pathways that could be therapeutically targeted. Genome-wide association studies (GWAS) have provided novel insights into the pathways leading to hyperuricaemia. GWAS have identified the renal uric acid transporter SLC2A9/GLUT9 and the gut excretory molecule ABCG2, which each have very strong genetic effects in the control of urate levels and risk of gout. Histone deacetylase inhibitors are able to correct the genetically-determined ABCG2 dysfunction. Other renal uric acid transporters, such as SLC22A11/OAT4 and SLC22A12/URAT1 have been confirmed to be genetically associated with urate and the risk of gout. Genes that generate urate during glycolysis (e.g. GCKR) are also implicated. In contrast very little is known about genetic variants that control the progression from hyperuricaemia to gout with the toll-like receptor 4 gene being the only gene with replicated evidence of association.

Clinical features of gout

2016 ◽  
Author(s):  
Nicola Dalbeth
Keyword(s):  
Uric Acid ◽  
Genetic Factors ◽  
Association Studies ◽  
Serum Urate ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Sweetened Beverages ◽  
Genome Wide ◽  
Uric Acid Transporters ◽  
Urate Crystals

About 60% of the variance in serum urate levels can be explained by inherited genetic factors, but the extent of the contribution of genetic factors to gout in the presence of hyperuricaemia is not known. Genome-wide association studies in Europeans have identified 28 loci controlling serum urate levels, although the molecular basis of the majority of these genetic associations is currently unknown. The SLC2A9 and ABCG2 renal and gut uric acid transporters have very strong effects on urate levels and the risk of gout. Other uric acid transporters (e.g. SLC22A11/OAT478, SLC22A12/URAT1) and a glycolysis gene (GCKR) are associated with urate levels. Environmental exposures such as sugar-sweetened beverages and alcohol interact with urate-associated genetic variants in an unpredictable fashion. Very little is known about the genetic control of gout in the presence of hyperuricaemia, formation of monosodium urate crystals, and the immune response.

Migraine: Genetic Variants and Clinical Phenotypes

2019 ◽  
Vol 26 (34) ◽  
pp. 6207-6221 ◽  
Author(s):  
Innocenzo Rainero ◽  
Alessandro Vacca ◽  
Flora Govone ◽  
Annalisa Gai ◽  
Lorenzo Pinessi ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Association Studies ◽  
Mthfr Gene ◽  
Genome Wide Association Studies ◽  
Clinical Phenotypes ◽  
Network Analyses ◽  
Genome Wide ◽  
Genomic Studies ◽  
The Common ◽  
The Relationship

Migraine is a common, chronic neurovascular disorder caused by a complex interaction between genetic and environmental risk factors. In the last two decades, molecular genetics of migraine have been intensively investigated. In a few cases, migraine is transmitted as a monogenic disorder, and the disease phenotype cosegregates with mutations in different genes like CACNA1A, ATP1A2, SCN1A, KCNK18, and NOTCH3. In the common forms of migraine, candidate genes as well as genome-wide association studies have shown that a large number of genetic variants may increase the risk of developing migraine. At present, few studies investigated the genotype-phenotype correlation in patients with migraine. The purpose of this review was to discuss recent studies investigating the relationship between different genetic variants and the clinical characteristics of migraine. Analysis of genotype-phenotype correlations in migraineurs is complicated by several confounding factors and, to date, only polymorphisms of the MTHFR gene have been shown to have an effect on migraine phenotype. Additional genomic studies and network analyses are needed to clarify the complex pathways underlying migraine and its clinical phenotypes.

scholarly journals Editing GWAS: experimental approaches to dissect and exploit disease-associated genetic variation

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Shuquan Rao ◽  
Yao Yao ◽  
Daniel E. Bauer
Keyword(s):  
Genome Editing ◽  
Genetic Variants ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Functional Studies ◽  
Functional Genetics ◽  
Genome Wide ◽  
Causal Variants ◽  
Experimental Approaches

AbstractGenome-wide association studies (GWAS) have uncovered thousands of genetic variants that influence risk for human diseases and traits. Yet understanding the mechanisms by which these genetic variants, mainly noncoding, have an impact on associated diseases and traits remains a significant hurdle. In this review, we discuss emerging experimental approaches that are being applied for functional studies of causal variants and translational advances from GWAS findings to disease prevention and treatment. We highlight the use of genome editing technologies in GWAS functional studies to modify genomic sequences, with proof-of-principle examples. We discuss the challenges in interrogating causal variants, points for consideration in experimental design and interpretation of GWAS locus mechanisms, and the potential for novel therapeutic opportunities. With the accumulation of knowledge of functional genetics, therapeutic genome editing based on GWAS discoveries will become increasingly feasible.

scholarly journals The Genetic Basis of Hypertriglyceridemia

2021 ◽  
Vol 23 (8) ◽  
Author(s):  
Germán D. Carrasquilla ◽  
Malene Revsbech Christiansen ◽  
Tuomas O. Kilpeläinen
Keyword(s):  
Genetic Basis ◽  
Association Studies ◽  
Cumulative Effect ◽  
Genome Wide Association Studies ◽  
Genetic Loci ◽  
Risk Variants ◽  
Genome Wide ◽  
Severe Hypertriglyceridemia ◽  
Increased Risk ◽  
Polygenic Scores

Abstract Purpose of Review Hypertriglyceridemia is a common dyslipidemia associated with an increased risk of cardiovascular disease and pancreatitis. Severe hypertriglyceridemia may sometimes be a monogenic condition. However, in the vast majority of patients, hypertriglyceridemia is due to the cumulative effect of multiple genetic risk variants along with lifestyle factors, medications, and disease conditions that elevate triglyceride levels. In this review, we will summarize recent progress in the understanding of the genetic basis of hypertriglyceridemia. Recent Findings More than 300 genetic loci have been identified for association with triglyceride levels in large genome-wide association studies. Studies combining the loci into polygenic scores have demonstrated that some hypertriglyceridemia phenotypes previously attributed to monogenic inheritance have a polygenic basis. The new genetic discoveries have opened avenues for the development of more effective triglyceride-lowering treatments and raised interest towards genetic screening and tailored treatments against hypertriglyceridemia. Summary The discovery of multiple genetic loci associated with elevated triglyceride levels has led to improved understanding of the genetic basis of hypertriglyceridemia and opened new translational opportunities.

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 GWAS of three molecular traits highlights core genes and pathways alongside a highly polygenic background

2020 ◽  
Author(s):  
Nasa Sinnott-Armstrong ◽  
Sahin Naqvi ◽  
Manuel Rivas ◽  
Jonathan K Pritchard
Keyword(s):  
Complex Traits ◽  
Genetic Basis ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Biological Processes ◽  
Uk Biobank ◽  
The Core ◽  
Genome Wide ◽  
Core Genes

SummaryGenome-wide association studies (GWAS) have been used to study the genetic basis of a wide variety of complex diseases and other traits. However, for most traits it remains difficult to interpret what genes and biological processes are impacted by the top hits. Here, as a contrast, we describe UK Biobank GWAS results for three molecular traits—urate, IGF-1, and testosterone—that are biologically simpler than most diseases, and for which we know a great deal in advance about the core genes and pathways. Unlike most GWAS of complex traits, for all three traits we find that most top hits are readily interpretable. We observe huge enrichment of significant signals near genes involved in the relevant biosynthesis, transport, or signaling pathways. We show how GWAS data illuminate the biology of variation in each trait, including insights into differences in testosterone regulation between females and males. Meanwhile, in other respects the results are reminiscent of GWAS for more-complex traits. In particular, even these molecular traits are highly polygenic, with most of the variance coming not from core genes, but from thousands to tens of thousands of variants spread across most of the genome. Given that diseases are often impacted by many distinct biological processes, including these three, our results help to illustrate why so many variants can affect risk for any given disease.

scholarly journals A deletion in GDF7 is associated with a heritable forebrain commissural malformation concurrent with ventriculomegaly and interhemispheric cysts in cats

2020 ◽  
Author(s):  
Yoshihiko Yu ◽  
Erica K. Creighton ◽  
Reuben M. Buckley ◽  
Leslie A. Lyons ◽  
Keyword(s):  
Genetic Basis ◽  
Association Studies ◽  
Homozygosity Mapping ◽  
Mammalian Brain ◽  
Genome Wide Association Studies ◽  
Commissural Axons ◽  
Genome Wide ◽  
Mixed Breed ◽  
Roof Plate ◽  
Control Association

AbstractAn inherited neurologic syndrome in a family of mixed-breed Oriental cats has been characterized as forebrain commissural malformation concurrent with ventriculomegaly and interhemispheric cysts. However, the genetic basis for this autosomal recessive syndrome in cats is unknown. Forty-three cats were genotyped on the Illumina Infinium Feline 63K iSelect DNA Array and used for analyses. Genome-wide association studies, including a sib-transmission disequilibrium test, a case-control association analysis, and homozygosity mapping, identified a critical region on cat chromosome A3. Short-read whole genome sequencing was completed for a cat trio segregating with the syndrome. A homozygous 7 bp deletion in growth differentiation factor 7 (GDF7) (c.221_227delGCCGCGC [p.Arg74Profs]) was identified in affected cats by comparison to the 99 Lives Cat variant dataset, validated using Sanger sequencing, and genotyped by fragment analyses. This variant was not identified in 192 unaffected cats in the 99 Lives dataset. The variant segregated concordantly in an extended pedigree. Obligate carrier cats were heterozygous. In mice, GDF7 mRNA is expressed within the roof plate when commissural axons initiate ventrally-directed growth. This finding emphasizes the importance of GDF7 in the neurodevelopmental process in the mammalian brain. A genetic test can be developed for use by cat breeders to eradicate this variant.

scholarly journals A transcriptome-wide Mendelian randomization study to uncover tissue-dependent regulatory mechanisms across the human phenome

2019 ◽  
Author(s):  
Tom G Richardson ◽  
Gibran Hemani ◽  
Tom R Gaunt ◽  
Caroline L Relton ◽  
George Davey Smith
Keyword(s):  
Gene Expression ◽  
Genetic Variants ◽  
Complex Traits ◽  
Mendelian Randomization ◽  
Drug Repositioning ◽  
Association Studies ◽  
Thyroid Tissue ◽  
Genome Wide Association Studies ◽  
Tissue Specific ◽  
Genome Wide

AbstractBackgroundDeveloping insight into tissue-specific transcriptional mechanisms can help improve our understanding of how genetic variants exert their effects on complex traits and disease. By applying the principles of Mendelian randomization, we have undertaken a systematic analysis to evaluate transcriptome-wide associations between gene expression across 48 different tissue types and 395 complex traits.ResultsOverall, we identified 100,025 gene-trait associations based on conventional genome-wide corrections (P < 5 × 10−08) that also provided evidence of genetic colocalization. These results indicated that genetic variants which influence gene expression levels in multiple tissues are more likely to influence multiple complex traits. We identified many examples of tissue-specific effects, such as genetically-predicted TPO, NR3C2 and SPATA13 expression only associating with thyroid disease in thyroid tissue. Additionally, FBN2 expression was associated with both cardiovascular and lung function traits, but only when analysed in heart and lung tissue respectively.We also demonstrate that conducting phenome-wide evaluations of our results can help flag adverse on-target side effects for therapeutic intervention, as well as propose drug repositioning opportunities. Moreover, we find that exploring the tissue-dependency of associations identified by genome-wide association studies (GWAS) can help elucidate the causal genes and tissues responsible for effects, as well as uncover putative novel associations.ConclusionsThe atlas of tissue-dependent associations we have constructed should prove extremely valuable to future studies investigating the genetic determinants of complex disease. The follow-up analyses we have performed in this study are merely a guide for future research. Conducting similar evaluations can be undertaken systematically at http://mrcieu.mrsoftware.org/Tissue_MR_atlas/.

scholarly journals GWASdb: a database for human genetic variants identified by genome-wide association studies

2011 ◽  
Vol 40 (D1) ◽  
pp. D1047-D1054 ◽  
Author(s):  
Mulin Jun Li ◽  
Panwen Wang ◽  
Xiaorong Liu ◽  
Ee Lyn Lim ◽  
Zhangyong Wang ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide

Statistical Genetics

2018 ◽  
pp. 57-69 ◽  
Author(s):  
Till F. M. Andlauer ◽  
Bertram Müller-Myhsok ◽  
Stephan Ripke
Keyword(s):  
Genetic Variants ◽  
Association Studies ◽  
Meta Analysis ◽  
Power Calculation ◽  
Genome Wide Association Studies ◽  
Psychiatric Genetics ◽  
Factors Influencing ◽  
Genome Wide ◽  
Basic Concepts ◽  
Study Designs

Over more than the last decade, hypothesis-free genome-wide association studies (GWAS) have been widely used to detect genetic factors influencing phenotypes of interest. The basic principle of GWAS has been unchanged since the beginning: a series of univariate tests is conducted on all genetic variants available across the genome. We present study designs and commonly used methods for genome-wide studies, with a focus on the analysis of common variants. The basic concepts required for an application of GWAS in psychiatric genetics are introduced, from power calculation to meta-analysis. This chapter will help the reader in gaining the knowledge required for participation in and realization of GWAS of both qualitative and quantitative traits.

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