Sara Knott

Publications (8)58.13 Total impact

• Source

  Available from: Andrew A. Hicks

  Article: Copy number variation across European populations.

  Wanting Chen, Caroline Hayward, Alan F Wright, Andrew A Hicks, Veronique Vitart, Sara Knott, Sarah H Wild, Peter P Pramstaller, James F Wilson, Igor Rudan, David J Porteous
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  ABSTRACT: Genome analysis provides a powerful approach to test for evidence of genetic variation within and between geographical regions and local populations. Copy number variants which comprise insertions, deletions and duplications of genomic sequence provide one such convenient and informative source. Here, we investigate copy number variants from genome wide scans of single nucleotide polymorphisms in three European population isolates, the island of Vis in Croatia, the islands of Orkney in Scotland and the South Tyrol in Italy. We show that whereas the overall copy number variant frequencies are similar between populations, their distribution is highly specific to the population of origin, a finding which is supported by evidence for increased kinship correlation for specific copy number variants within populations.
  PLoS ONE 01/2011; 6(8):e23087. · 4.09 Impact Factor
• Article: The TCF7L2 diabetes risk variant is associated with HbA₁(C) levels: a genome-wide association meta-analysis.

  Christopher S Franklin, Yurii S Aulchenko, Jennifer E Huffman, Veronique Vitart, Caroline Hayward, Ozren Polašek, Sara Knott, Lina Zgaga, Tatijana Zemunik, Igor Rudan, Harry Campbell, Alan F Wright, Sarah H Wild, James F Wilson
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  ABSTRACT: Genome-wide association (GWA) studies have identified around 20 common genetic variants influencing the risk of type 2 diabetes (T2D). Likewise, a number of variants have been associated with diabetes-related quantitative glycaemic traits, but to date the overlap between these genes and variants has been low. The majority of genetic studies have focused on fasting plasma glucose levels; however, this measure is highly variable. We have conducted a GWA meta-analysis of glycated haemoglobin (HbA₁(C) ) levels within three healthy nondiabetic populations. This phenotype provides an estimate of mean glucose levels over 2-3 months and is a more stable predictor of future diabetes risk. Participants were from three isolated populations: the Orkney Isles in the north of Scotland, the Dalmatian islands of Vis, and Korčula in Croatia (total of 1782 nondiabetic subjects). Association was tested in each population and results combined by meta-analysis. The strongest association was with the TCF7L2 gene (rs7903146, P= 1.48 × 10⁻⁷). This is also the strongest common genetic risk factor for T2D but it has not been identified in previous genome-wide studies of glycated haemoglobin.
  Annals of Human Genetics 11/2010; 74(6):471-8. · 2.57 Impact Factor
• Article: Linkage and genome-wide association analysis of obesity-related phenotypes: association of weight with the MGAT1 gene.

  Asa Johansson, Fabio Marroni, Caroline Hayward, Christopher S Franklin, Anatoly V Kirichenko, Inger Jonasson, Andrew A Hicks, Veronique Vitart, Aaron Isaacs, Tatiana Axenovich, [......], James F Wilson, Igor Rudan, Harry Campbell, Cristian Pattaro, Peter Pramstaller, Ben A Oostra, Alan F Wright, Cornelia M van Duijn, Yurii S Aulchenko, Ulf Gyllensten
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  ABSTRACT: As major risk-factors for diabetes and cardiovascular diseases, the genetic contribution to obesity-related traits has been of interest for decades. Recently, a limited number of common genetic variants, which have replicated in different populations, have been identified. One approach to increase the statistical power in genetic mapping studies is to focus on populations with increased levels of linkage disequilibrium (LD) and reduced genetic diversity. We have performed joint linkage and genome-wide association analyses for weight and BMI in 3,448 (linkage) and 3,925 (association) partly overlapping healthy individuals from five European populations. A total of four chromosomal regions (two for weight and two for BMI) showed suggestive linkage (lod >2.69) either in one of the populations or in the joint data. At the genome-wide level (nominal P < 1.6 x 10(-7), Bonferroni-adjusted P < 0.05) one single-nucleotide polymorphism (SNP) (rs12517906) (nominal P = 7.3 x 10(-8)) was associated with weight, whereas none with BMI. The SNP associated with weight is located close to MGAT1. The monoacylglycerol acyltransferase (MGAT) enzyme family is known to be involved in dietary fat absorption. There was no overlap between the linkage regions and the associated SNPs. Our results show that genetic effects influencing weight and BMI are shared across diverse European populations, even though some of these populations have experienced recent population bottlenecks and/or been affected by genetic drift. The analysis enabled us to identify a new candidate gene, MGAT1, associated with weight in women.
  Obesity 10/2009; 18(4):803-8. · 4.28 Impact Factor
• Article: A web application to perform linkage disequilibrium and linkage analyses on a computational grid.

  Jules Hernández-Sánchez, Jean-Alain Grunchec, Sara Knott
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  ABSTRACT: Unravelling the genetic architecture of complex traits requires large amounts of data, sophisticated models and large computational resources. The lack of user-friendly software incorporating all these requisites is delaying progress in the analysis of complex traits. Linkage disequilibrium and linkage analysis (LDLA) is a high-resolution gene mapping approach based on sophisticated mixed linear models, applicable to any population structure. LDLA can use population history information in addition to pedigree and molecular markers to decompose traits into genetic components. Analyses are distributed in parallel over a large public grid of computers in the UK. We have proven the performance of LDLA with analyses of simulated data. There are real gains in statistical power to detect quantitative trait loci when using historical information compared with traditional linkage analysis. Moreover, the use of a grid of computers significantly increases computational speed, hence allowing analyses that would have been prohibitive on a single computer. The authors have implemented LDLA within the freely available GridQTL software (www.gridqtl.org.uk).
  Bioinformatics 04/2009; 25(11):1377-83. · 5.47 Impact Factor
• Source

  Available from: PubMed Central

  Article: Haplotyping via minimum recombinant paradigm.

  Jules Hernández-Sánchez, Sara Knott
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  ABSTRACT: Haplotypes can increase the power of gene detection over genotypes and are essential to estimate linkage disequilibrium. Haplotyping was based on the minimum recombinant paradigm, whereby a phase is obtained only if it uniquely minimises the number of recombinants within a full sib family. Performance of this method was tested across three different data sets, consisting of genotypes and pedigree. The percentage of phased alleles ranged from ~80% to ~95%, and the percentage of correct phases reached ~99% in all cases. A measure of uncertainty was obtained via simulations. A partial haplotyping algorithm consisting of four deterministic rules was almost as effective as a full one consisting of six deterministic rules, and took up to 5 times less time to compute. Haplotyping via the minimum recombinant paradigm is consistently reliable and computationally efficient. A single simulation is enough to produce a population-wide uncertainty estimate associated with a set of all reconstructed haplotypes.
  BMC proceedings 02/2009; 3 Suppl 1:S7.
• Article: Common variants in the JAZF1 gene associated with height identified by linkage and genome-wide association analysis.

  Asa Johansson, Fabio Marroni, Caroline Hayward, Christopher S Franklin, Anatoly V Kirichenko, Inger Jonasson, Andrew A Hicks, Veronique Vitart, Aaron Isaacs, Tatiana Axenovich, [......], James F Wilson, Igor Rudan, Harry Campbell, Cristian Pattaro, Peter Pramstaller, Ben A Oostra, Alan F Wright, Cornelia M van Duijn, Yurii S Aulchenko, Ulf Gyllensten
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  ABSTRACT: Genes for height have gained interest for decades, but only recently have candidate genes started to be identified. We have performed linkage analysis and genome-wide association for height in approximately 4000 individuals from five European populations. A total of five chromosomal regions showed suggestive linkage and in one of these regions, two SNPs (rs849140 and rs1635852) were associated with height (nominal P = 7.0 x 10(-8) and P = 9.6 x 10(-7), respectively). In total, five SNPs across the genome showed an association with height that reached the threshold of genome-wide significance (nominal P < 1.6 x 10(-7)). The association with height was replicated for two SNPs (rs1635852 and rs849140) using three independent studies (n = 31 077, n=1268 and n = 5746) with overall meta P-values of 9.4 x 10(-10) and 5.3 x 10(-8). These SNPs are located in the JAZF1 gene, which has recently been associated with type II diabetes, prostate and endometrial cancer. JAZF1 is a transcriptional repressor of NR2C2, which results in low IGF1 serum concentrations, perinatal and early postnatal hypoglycemia and growth retardation when knocked out in mice. Both the linkage and association analyses independently identified the JAZF1 region affecting human height. We have demonstrated, through replication in additional independent populations, the consistency of the effect of the JAZF1 SNPs on height. Since this gene also has a key function in the metabolism of growth, JAZF1 represents one of the strongest candidates influencing human height identified so far.
  Human Molecular Genetics 10/2008; 18(2):373-80. · 7.64 Impact Factor
• Article: Genetic control of lipids in the mouse cross DU6i x DBA/2.

  Gudrun A Brockmann, Ersin Karatayli, Christina Neuschl, Ioannis M Stylianou, Soner Aksu, Antje Ludwig, Ulla Renne, Chris S Haley, Sara Knott
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  ABSTRACT: An F(2) pedigree based on the mouse lines DU6i and DBA/2 with extremely different growth and obesity characteristics was generated to search for QTLs affecting serum concentrations of triglycerides (TG), total cholesterol (CHOL), HDL cholesterol (HDL-C), and LDL cholesterol (LDL-C). Compared with many other studies, we searched for spontaneous genetic variants contributing to high lipid levels under a standard breeding diet. Significant QTLs for CHOL were identified on chromosomes 4 and 6, and a female-specific locus on chromosome 3. QTLs for HDL-C were detected on chromosome 11 for both sexes, and on chromosome 1 for females. These QTLs are located in syntenic human regions that have QTLs that have not been previously confirmed in animal studies. LDL-C QTLs have been mapped for both sexes to chromosome 8 and in males on chromosome 13. Epistatic interactions that significantly accounted for the phenotypic variance of HDL-C, CHOL, and LDL-C serum concentrations were also detected with one interaction between chromosomes 8 and 15, accounting for 22% of the observed variance in LDL-C levels. The identified loci coincide in part with regions controlling growth and obesity. Thus, multiple genes or pleiotropic effects may be assumed. The identified QTLs for cholesterol and its transport proteins as subcomponents of risk for coronary heart disease will further improve our understanding of the genetic net controlling plasma lipid concentrations.
  Mammalian Genome 12/2007; 18(11):757-66. · 2.89 Impact Factor
• Source

  Available from: Douglas H R Blackwood

  Article: Is schizophrenia linked to chromosome 1q?

  Stuart Macgregor, Peter M Visscher, Sara Knott, David Porteous, Walter Muir, Kirsty Millar, Douglas Blackwood
  Science 01/2003; 298(5602):2277; author reply 2277. · 31.20 Impact Factor