Publications by authors named "Laura J Corbin"

17 Publications

  • Page 1 of 1

Effects of adiposity on the human plasma proteome: observational and Mendelian randomisation estimates.

Int J Obes (Lond) 2021 Jul 5. Epub 2021 Jul 5.

Medical Research Council (MRC) Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.

Background: Variation in adiposity is associated with cardiometabolic disease outcomes, but mechanisms leading from this exposure to disease are unclear. This study aimed to estimate effects of body mass index (BMI) on an extensive set of circulating proteins.

Methods: We used SomaLogic proteomic data from up to 2737 healthy participants from the INTERVAL study. Associations between self-reported BMI and 3622 unique plasma proteins were explored using linear regression. These were complemented by Mendelian randomisation (MR) analyses using a genetic risk score (GRS) comprised of 654 BMI-associated polymorphisms from a recent genome-wide association study (GWAS) of adult BMI. A disease enrichment analysis was performed using DAVID Bioinformatics 6.8 for proteins which were altered by BMI.

Results: Observationally, BMI was associated with 1576 proteins (P < 1.4 × 10), with particularly strong evidence for a positive association with leptin and fatty acid-binding protein-4 (FABP4), and a negative association with sex hormone-binding globulin (SHBG). Observational estimates were likely confounded, but the GRS for BMI did not associate with measured confounders. MR analyses provided evidence for a causal relationship between BMI and eight proteins including leptin (0.63 standard deviation (SD) per SD BMI, 95% CI 0.48-0.79, P = 1.6 × 10), FABP4 (0.64 SD per SD BMI, 95% CI 0.46-0.83, P = 6.7 × 10) and SHBG (-0.45 SD per SD BMI, 95% CI -0.65 to -0.25, P = 1.4 × 10). There was agreement in the magnitude of observational and MR estimates (R = 0.33) and evidence that proteins most strongly altered by BMI were enriched for genes involved in cardiovascular disease.

Conclusions: This study provides evidence for a broad impact of adiposity on the human proteome. Proteins strongly altered by BMI include those involved in regulating appetite, sex hormones and inflammation; such proteins are also enriched for cardiovascular disease-related genes. Altogether, results help focus attention onto new proteomic signatures of obesity-related disease.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41366-021-00896-1DOI Listing
July 2021

The trans-ancestral genomic architecture of glycemic traits.

Nat Genet 2021 06 31;53(6):840-860. Epub 2021 May 31.

Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41588-021-00852-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7610958PMC
June 2021

Loss-of-function mutations in the melanocortin 4 receptor in a UK birth cohort.

Nat Med 2021 Jun 27;27(6):1088-1096. Epub 2021 May 27.

Wellcome Trust-MRC Institute of Metabolic Science and NIHR Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, UK.

Mutations in the melanocortin 4 receptor gene (MC4R) are associated with obesity but little is known about the prevalence and impact of such mutations throughout human growth and development. We examined the MC4R coding sequence in 5,724 participants from the Avon Longitudinal Study of Parents and Children, functionally characterized all nonsynonymous MC4R variants and examined their association with anthropometric phenotypes from childhood to early adulthood. The frequency of heterozygous loss-of-function (LoF) mutations in MC4R was ~1 in 337 (0.30%), considerably higher than previous estimates. At age 18 years, mean differences in body weight, body mass index and fat mass between carriers and noncarriers of LoF mutations were 17.76 kg (95% CI 9.41, 26.10), 4.84 kg m (95% CI 2.19, 7.49) and 14.78 kg (95% CI 8.56, 20.99), respectively. MC4R LoF mutations may be more common than previously reported and carriers of such variants may enter adult life with a substantial burden of excess adiposity.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41591-021-01349-yDOI Listing
June 2021

The Role of Inflammatory Cytokines as Intermediates in the Pathway from Increased Adiposity to Disease.

Obesity (Silver Spring) 2021 02;29(2):428-437

MRC Integrative Epidemiology Unit at University of Bristol, Bristol, UK.

Objective: This study aimed to investigate the role of cytokines as intermediates in the pathway from increased adiposity to disease.

Methods: BMI and circulating levels of up to 41 cytokines were measured in individuals from three Finnish cohort studies (n = 8,293). Mendelian randomization (MR) was used to assess the impact of BMI on circulating cytokines and the impact of BMI-driven cytokines on risk of obesity-related diseases.

Results: Observationally, BMI was associated with 19 cytokines. For every SD increase in BMI, causal effect estimates were strongest for hepatocyte growth factor, monocyte chemotactic protein-1 (MCP-1), and tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) and were as ratios of geometric means 1.13 (95% CI: 1.08-1.19), 1.08 (95% CI: 1.04-1.14), and 1.13 (95% CI: 1.04-1.21), respectively. TRAIL was associated with a small increase in the odds of coronary artery disease (odds ratio: 1.03; 95% CI: 1.00-1.06). There was inconsistent evidence for a protective role of MCP-1 against inflammatory bowel diseases.

Conclusions: Observational and MR estimates of the effect of BMI on cytokine levels were generally concordant. There was little evidence for an effect of raised levels of BMI-driven cytokines on disease. These findings illustrate the challenges of MR when applied in the context of molecular mediation.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1002/oby.23060DOI Listing
February 2021

Metabolic characterisation of disturbances in the APOC3/triglyceride-rich lipoprotein pathway through sample-based recall by genotype.

Metabolomics 2020 06 3;16(6):69. Epub 2020 Jun 3.

MRC Integrative Epidemiology Unit at University of Bristol, Bristol, BS8 2BN, UK.

Introduction: High plasma triacylglyceride levels are known to be associated with increased risk of atherosclerotic cardiovascular disease. Apolipoprotein C-III (apoC-III) is a key regulator of plasma triacylglyceride levels and is associated with hypertriglyceridemia via a number of pathways. There is consistent evidence for an association of cardiovascular events with blood apoC-III level, with support from human genetic studies of APOC3 variants. As such, apoC-III has been recognised as a potential therapeutic target for patients with severe hypertriglyceridaemia with one of the most promising apoC-III-targeting drugs, volanesorsen, having recently progressed through Phase III trials.

Objectives: To exploit a rare loss of function variant in APOC3 (rs138326449) to characterise the potential long-term treatment effects of apoC-III targeting interventions on the metabolome.

Methods: In a recall-by-genotype study, 115 plasma samples were analysed by UHPLC-MS to acquire non-targeted metabolomics data. The study included samples from 57 adolescents and 33 adults. Overall, 12 985 metabolic features were tested for an association with APOC3 genotype.

Results: 161 uniquely annotated metabolites were found to be associated with rs138326449(APOC3). The highest proportion of associated metabolites belonged to the acyl-acyl glycerophospholipid and triacylglyceride metabolite classes. In addition to the anticipated (on-target) reduction of metabolites in the triacylglyceride and related classes, carriers of the rare variant exhibited previously unreported increases in levels of a number of metabolites from the acyl-alkyl glycerophospholipid class.

Conclusion: Overall, our results suggest that therapies targeting apoC-III may potentially achieve a broad shift in lipid profile that favours better metabolic health.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1007/s11306-020-01689-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7270992PMC
June 2020

An Independent Locus Upstream of Controls Variation in the Shade of the Bay Coat Colour in Horses.

Genes (Basel) 2020 05 30;11(6). Epub 2020 May 30.

Department of Animal Sciences, University of Florida, Gainesville, FL 32610, USA.

Novel coat colour phenotypes often emerge during domestication, and there is strong evidence of genetic selection for the two main genes that control base coat colour in horses- and . These genes direct the type of pigment produced, red pheomelanin () or black eumelanin (), as well as the relative concentration and the temporal-spatial distribution of melanin pigment deposits in the skin and hair coat. Here, we describe a genome-wide association study (GWAS) to identify novel genic regions involved in the determination of the shade of bay. In total, 126 horses from five different breeds were ranked according to the extent of the distribution of eumelanin: spanning variation in phenotype from black colour restricted only to the extremities to the presence of some black pigment across nearly all the body surface. We identified a single region associated with the shade of bay ranking spanning approximately 0.5 MB on ECA22, just upstream of the gene ( 9.76 × 10). This candidate region encompasses the distal 5' end of the transcript (as predicted from other species) as well as the gene. Both loci are viable candidates based on the presence of similar alleles in other species. These results contribute to the growing understanding of coat colour genetics in the horse and to the mapping of genetic determinants of pigmentation on a molecular level. Given pleiotropic phenotypes in behaviour and obesity for alleles, especially those in the 5' regulatory region, improved understanding of this new allele may have implications for health management in the horse.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3390/genes11060606DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7349280PMC
May 2020

Common variation at 16p11.2 is associated with glycosuria in pregnancy: findings from a genome-wide association study in European women.

Hum Mol Genet 2020 07;29(12):2098-2106

Medical Research Council Integrative Epidemiology Unit, Avon Longitudinal Study of Parents and Children, Population Health Science, Bristol Medical School, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK.

Glycosuria is a condition where glucose is detected in urine at higher concentrations than normal (i.e. not detectable). Glycosuria at some point during pregnancy has an estimated prevalence of 50% and is associated with adverse outcomes in both mothers and offspring. Little is currently known about the genetic contribution to this trait or the extent to which it overlaps with other seemingly related traits, e.g. diabetes. We performed a genome-wide association study (GWAS) for self-reported glycosuria in pregnant mothers from the Avon Longitudinal Study of Parents and Children (cases/controls = 1249/5140). We identified two loci, one of which (lead SNP = rs13337037; chromosome 16; odds ratio of glycosuria per effect allele: 1.42; 95% CI: 1.30, 1.56; P = 1.97 × 10-13) was then validated using an obstetric measure of glycosuria measured in the same cohort (227/6639). We performed a secondary GWAS in the 1986 Northern Finland Birth Cohort (NFBC1986; 747/2991) using midwife-reported glycosuria and offspring genotype as a proxy for maternal genotype. The combined results revealed evidence for a consistent effect on glycosuria at the chromosome 16 locus. In follow-up analyses, we saw little evidence of shared genetic underpinnings with the exception of urinary albumin-to-creatinine ratio (Rg = 0.64; SE = 0.22; P = 0.0042), a biomarker of kidney disease. In conclusion, we identified a genetic association with self-reported glycosuria during pregnancy, with the lead SNP located 15kB upstream of SLC5A2, a target of antidiabetic drugs. The lack of strong genetic correlation with seemingly related traits such as type 2 diabetes suggests different genetic risk factors exist for glycosuria during pregnancy.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/hmg/ddaa054DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7390941PMC
July 2020

Genetic architecture of human thinness compared to severe obesity.

PLoS Genet 2019 01 24;15(1):e1007603. Epub 2019 Jan 24.

University of Cambridge Metabolic Research Laboratories and NIHR Cambridge Biomedical Research Centre, Wellcome Trust-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, United Kingdom.

The variation in weight within a shared environment is largely attributable to genetic factors. Whilst many genes/loci confer susceptibility to obesity, little is known about the genetic architecture of healthy thinness. Here, we characterise the heritability of thinness which we found was comparable to that of severe obesity (h2 = 28.07 vs 32.33% respectively), although with incomplete genetic overlap (r = -0.49, 95% CI [-0.17, -0.82], p = 0.003). In a genome-wide association analysis of thinness (n = 1,471) vs severe obesity (n = 1,456), we identified 10 loci previously associated with obesity, and demonstrate enrichment for established BMI-associated loci (pbinomial = 3.05x10-5). Simulation analyses showed that different association results between the extremes were likely in agreement with additive effects across the BMI distribution, suggesting different effects on thinness and obesity could be due to their different degrees of extremeness. In further analyses, we detected a novel obesity and BMI-associated locus at PKHD1 (rs2784243, obese vs. thin p = 5.99x10-6, obese vs. controls p = 2.13x10-6 pBMI = 2.3x10-13), associations at loci recently discovered with much larger sample sizes (e.g. FAM150B and PRDM6-CEP120), and novel variants driving associations at previously established signals (e.g. rs205262 at the SNRPC/C6orf106 locus and rs112446794 at the PRDM6-CEP120 locus). Our ability to replicate loci found with much larger sample sizes demonstrates the value of clinical extremes and suggest that characterisation of the genetics of thinness may provide a more nuanced understanding of the genetic architecture of body weight regulation and may inform the identification of potential anti-obesity targets.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1371/journal.pgen.1007603DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6345421PMC
January 2019

Formalising recall by genotype as an efficient approach to detailed phenotyping and causal inference.

Nat Commun 2018 02 19;9(1):711. Epub 2018 Feb 19.

Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 7LE, UK.

Detailed phenotyping is required to deepen our understanding of the biological mechanisms behind genetic associations. In addition, the impact of potentially modifiable risk factors on disease requires analytical frameworks that allow causal inference. Here, we discuss the characteristics of Recall-by-Genotype (RbG) as a study design aimed at addressing both these needs. We describe two broad scenarios for the application of RbG: studies using single variants and those using multiple variants. We consider the efficacy and practicality of the RbG approach, provide a catalogue of UK-based resources for such studies and present an online RbG study planner.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41467-018-03109-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5818506PMC
February 2018

A reference panel of 64,976 haplotypes for genotype imputation.

Nat Genet 2016 10 22;48(10):1279-83. Epub 2016 Aug 22.

IRGB, CNR, Sardinia, Italy.

We describe a reference panel of 64,976 human haplotypes at 39,235,157 SNPs constructed using whole-genome sequence data from 20 studies of predominantly European ancestry. Using this resource leads to accurate genotype imputation at minor allele frequencies as low as 0.1% and a large increase in the number of SNPs tested in association studies, and it can help to discover and refine causal loci. We describe remote server resources that allow researchers to carry out imputation and phasing consistently and efficiently.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/ng.3643DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5388176PMC
October 2016

Body mass index: Has epidemiology started to break down causal contributions to health and disease?

Obesity (Silver Spring) 2016 08;24(8):1630-8

MRC Integrative Epidemiology Unit (IEU) at the University of Bristol, Bristol, UK.

Objectives: To review progress in understanding the methods and results concerning the causal contribution of body mass index (BMI) to health and disease.

Methods: In the context of conventional evidence focused on the relationship between BMI and health, this review considers current literature on the common, population-based, genetic contribution to BMI and how this has fed into the developing field of applied epidemiology.

Results: Technological and analytical developments have driven considerable success in identifying genetic variants relevant to BMI. This has enabled the implementation of Mendelian randomization to address questions of causality. The product of this work has been the implication of BMI as a causal agent in a host of health outcomes. Further breakdown of causal pathways by integration with other "omics" technologies promises to deliver additional benefit.

Conclusions: Gaps remain in our understanding of BMI as a risk factor for health and disease, and while promising, applied genetic epidemiology should be considered alongside alternative methods for assessing the impact of BMI on health. Potential limitations, relating to inappropriate or nonspecific measures of obesity and the improper use of genetic instruments, will need to be explored and incorporated into future research aiming to dissect BMI as a risk factor.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1002/oby.21554DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5972005PMC
August 2016

BMI as a Modifiable Risk Factor for Type 2 Diabetes: Refining and Understanding Causal Estimates Using Mendelian Randomization.

Diabetes 2016 10 8;65(10):3002-7. Epub 2016 Jul 8.

MRC Integrative Epidemiology Unit, University of Bristol, Bristol, U.K.

This study focused on resolving the relationship between BMI and type 2 diabetes. The availability of multiple variants associated with BMI offers a new chance to resolve the true causal effect of BMI on type 2 diabetes; however, the properties of these associations and their validity as genetic instruments need to be considered alongside established and new methods for undertaking Mendelian randomization (MR). We explore the potential for pleiotropic genetic variants to generate bias, revise existing estimates, and illustrate value in new analysis methods. A two-sample MR approach with 96 genetic variants was used with three different analysis methods, two of which (MR-Egger and the weighted median) have been developed specifically to address problems of invalid instrumental variables. We estimate an odds ratio for type 2 diabetes per unit increase in BMI (kg/m(2)) of between 1.19 and 1.38, with the most stable estimate using all instruments and a weighted median approach (1.26 [95% CI 1.17, 1.34]). TCF7L2(rs7903146) was identified as a complex effect or pleiotropic instrument, and removal of this variant resulted in convergence of causal effect estimates from different causal analysis methods. This indicated the potential for pleiotropy to affect estimates and differences in performance of alternative analytical methods. In a real type 2 diabetes-focused example, this study demonstrates the potential impact of invalid instruments on causal effect estimates and the potential for new approaches to mitigate the bias caused.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.2337/db16-0418DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5279886PMC
October 2016

Genetics, sleep and memory: a recall-by-genotype study of ZNF804A variants and sleep neurophysiology.

BMC Med Genet 2015 Oct 24;16:96. Epub 2015 Oct 24.

MRC Integrative Epidemiology Unit at University of Bristol, Bristol, UK.

Background: Schizophrenia is a complex, polygenic disorder for which over 100 genetic variants have been identified that correlate with diagnosis. However, the biological mechanisms underpinning the different symptom clusters remain undefined. The rs1344706 single nucleotide polymorphism within ZNF804A was among the first genetic variants found to be associated with schizophrenia. Previously, neuroimaging and cognitive studies have revealed several associations between rs1344706 and brain structure and function. The aim of this study is to use a recall-by-genotype (RBG) design to investigate the biological basis for the association of ZNF804A variants with schizophrenia. A RBG study, implemented in a population cohort, will be used to evaluate the impact of genetic variation at rs1344706 on sleep neurophysiology and procedural memory consolidation in healthy participants.

Methods/design: Participants will be recruited from the Avon Longitudinal Study of Parents and Children (ALSPAC) on the basis of genotype at rs1344706 (n = 24). Each participant will be asked to take part in two nights of in-depth sleep monitoring (polysomnography) allowing collection of neurophysiological sleep data in a manner not amenable to large-scale study. Sleep questionnaires will be used to assess general sleep quality and subjective sleep experience after each in-house recording. A motor sequencing task (MST) will be performed before and after the second night of polysomnography. In order to gather additional data about habitual sleep behaviour participants will be asked to wear a wrist worn activity monitor (actiwatch) and complete a sleep diary for two weeks.

Discussion: This study will explore the biological function of ZNF804A genotype (rs1344706) in healthy volunteers by examining detailed features of sleep architecture and physiology in relation to motor learning. Using a RBG approach will enable us to collect precise and detailed phenotypic data whilst achieving an informative biological gradient. It would not be feasible to collect such data in the large sample sizes that would be required under a random sampling scheme. By dissecting the role of individual variants associated with schizophrenia in this way, we can begin to unravel the complex genetic mechanisms of psychiatric disorders and pave the way for future development of novel therapeutic approaches.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s12881-015-0244-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4619339PMC
October 2015

Using inactivating mutations to provide insight into drug action.

Genome Med 2015 28;7(1). Epub 2015 Jan 28.

MRC Integrative Epidemiology Unit (IEU), University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN UK.

The role of ezetimibe in lowering plasma cholesterol has been established; however, controversy remains about its clinical benefit. A recent study utilizes naturally occurring genetic variation within the NPC1-like 1 gene (NPC1L1) to demonstrate the potential for pharmacologic inhibition of the protein to reduce the risk of coronary heart disease. This research demonstrates the application of the concept of genocopy to a population-based validation of NPC1L1 as a therapeutic target.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s13073-015-0130-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4307143PMC
January 2015

The utility of low-density genotyping for imputation in the Thoroughbred horse.

Genet Sel Evol 2014 Feb 4;46. Epub 2014 Feb 4.

Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian EH25 9RG, UK.

Background: Despite the dramatic reduction in the cost of high-density genotyping that has occurred over the last decade, it remains one of the limiting factors for obtaining the large datasets required for genomic studies of disease in the horse. In this study, we investigated the potential for low-density genotyping and subsequent imputation to address this problem.

Results: Using the haplotype phasing and imputation program, BEAGLE, it is possible to impute genotypes from low- to high-density (50K) in the Thoroughbred horse with reasonable to high accuracy. Analysis of the sources of variation in imputation accuracy revealed dependence both on the minor allele frequency of the single nucleotide polymorphisms (SNPs) being imputed and on the underlying linkage disequilibrium structure. Whereas equidistant spacing of the SNPs on the low-density panel worked well, optimising SNP selection to increase their minor allele frequency was advantageous, even when the panel was subsequently used in a population of different geographical origin. Replacing base pair position with linkage disequilibrium map distance reduced the variation in imputation accuracy across SNPs. Whereas a 1K SNP panel was generally sufficient to ensure that more than 80% of genotypes were correctly imputed, other studies suggest that a 2K to 3K panel is more efficient to minimize the subsequent loss of accuracy in genomic prediction analyses. The relationship between accuracy and genotyping costs for the different low-density panels, suggests that a 2K SNP panel would represent good value for money.

Conclusions: Low-density genotyping with a 2K SNP panel followed by imputation provides a compromise between cost and accuracy that could promote more widespread genotyping, and hence the use of genomic information in horses. In addition to offering a low cost alternative to high-density genotyping, imputation provides a means to combine datasets from different genotyping platforms, which is becoming necessary since researchers are starting to use the recently developed equine 70K SNP chip. However, more work is needed to evaluate the impact of between-breed differences on imputation accuracy.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/1297-9686-46-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3930001PMC
February 2014

A genome-wide association study of osteochondritis dissecans in the Thoroughbred.

Mamm Genome 2012 Apr 4;23(3-4):294-303. Epub 2011 Nov 4.

The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, Scotland, UK.

Osteochondrosis is a developmental orthopaedic disease that occurs in horses, other livestock species, companion animal species, and humans. The principal aim of this study was to identify quantitative trait loci (QTL) associated with osteochondritis dissecans (OCD) in the Thoroughbred using a genome-wide association study. A secondary objective was to test the effect of previously identified QTL in the current population. Over 300 horses, classified as cases or controls according to clinical findings, were genotyped for the Illumina Equine SNP50 BeadChip. An animal model was first implemented in order to adjust each horse's phenotypic status for average relatedness among horses and other potentially confounding factors which were present in the data. The genome-wide association test was then conducted on the residuals from the animal model. A single SNP on chromosome 3 was found to be associated with OCD at a genome-wide level of significance, as determined by permutation. According to the current sequence annotation, the SNP is located in an intergenic region of the genome. The effects of 24 SNPs, representing QTL previously identified in a sample of Hanoverian Warmblood horses, were tested directly in the animal model. When fitted alongside the significant SNP on ECA3, two of these SNPs were found to be associated with OCD. Confirmation of the putative QTL identified on ECA3 requires validation in an independent sample. The results of this study suggest that a significant challenge faced by equine researchers is the generation of sufficiently large data sets to effectively study complex diseases such as osteochondrosis.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1007/s00335-011-9363-1DOI Listing
April 2012