Article: Oculo-facio-cardio-dental syndrome in three succeeding generations: genotypic data and phenotypic features.Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologicas / Sociedade Brasileira de Biofisica ... [et al.] 09/2012; · 1.08 Impact Factor
R. McQuillan, N. Eklund, N. Pirastu, M. Kuningas, B. P. McEvoy, T. Esko, T. Corre, G. Davies, M. Kaakinen, L. P. Lyytikainen, [......], D. Toniolo, J. G. Eriksson, A. Jula, O. T. Raitakari, A. Metspalu, M. Perola, M. R. Jarvelin, A. Uitterlinden, P. M. Visscher, J. F. Wilson[show abstract] [hide abstract]
ABSTRACT: Stature is a classical and highly heritable complex trait, with 80%-90% of variation explained by genetic factors. In recent years, genome-wide association studies (GWAS) have successfully identified many common additive variants influencing human height; however, little attention has been given to the potential role of recessive genetic effects. Here, we investigated genome-wide recessive effects by an analysis of inbreeding depression on adult height in over 35,000 people from 21 different population samples. We found a highly significant inverse association between height and genome-wide homozygosity, equivalent to a height reduction of up to 3 cm in the offspring of first cousins compared with the offspring of unrelated individuals, an effect which remained after controlling for the effects of socio-economic status, an important confounder (chi(2) = 83.89, df = 1; p = 5.2x10(-20)). There was, however, a high degree of heterogeneity among populations: whereas the direction of the effect was consistent across most population samples, the effect size differed significantly among populations. It is likely that this reflects true biological heterogeneity: whether or not an effect can be observed will depend on both the variance in homozygosity in the population and the chance inheritance of individual recessive genotypes. These results predict that multiple, rare, recessive variants influence human height. Although this exploratory work focuses on height alone, the methodology developed is generally applicable to heritable quantitative traits (QT), paving the way for an investigation into inbreeding effects, and therefore genetic architecture, on a range of QT of biomedical importance.PLoS Genet. 01/2012; 8(7):e1002655.
Article: Genome-wide association analyses identify 18 new loci associated with serum urate concentrations.Anna Köttgen, Eva Albrecht, Alexander Teumer, Veronique Vitart, Jan Krumsiek, Claudia Hundertmark, Giorgio Pistis, Daniela Ruggiero, Conall M O'Seaghdha, Toomas Haller, [......], Nicole Soranzo, Daniela Toniolo, Daniel I Chasman, Olli Raitakari, W H Linda Kao, Marina Ciullo, Caroline S Fox, Mark Caulfield, Murielle Bochud, Christian Gieger[show abstract] [hide abstract]
ABSTRACT: Elevated serum urate concentrations can cause gout, a prevalent and painful inflammatory arthritis. By combining data from >140,000 individuals of European ancestry within the Global Urate Genetics Consortium (GUGC), we identified and replicated 28 genome-wide significant loci in association with serum urate concentrations (18 new regions in or near TRIM46, INHBB, SFMBT1, TMEM171, VEGFA, BAZ1B, PRKAG2, STC1, HNF4G, A1CF, ATXN2, UBE2Q2, IGF1R, NFAT5, MAF, HLF, ACVR1B-ACVRL1 and B3GNT4). Associations for many of the loci were of similar magnitude in individuals of non-European ancestry. We further characterized these loci for associations with gout, transcript expression and the fractional excretion of urate. Network analyses implicate the inhibins-activins signaling pathways and glucose metabolism in systemic urate control. New candidate genes for serum urate concentration highlight the importance of metabolic control of urate production and excretion, which may have implications for the treatment and prevention of gout.Nature genetics. 01/2013; 45(2):145-54.
Nora Franceschini, Frank J A van Rooij, Bram P Prins, Mary F Feitosa, Mahir Karakas, John H Eckfeldt, Aaron R Folsom, Jeffrey Kopp, Ahmad Vaez, Jeanette S Andrews, [......], Alan F Wright, Qingyu Wu, Yongmei Liu, Nancy S Jenny, Kari E North, Janine F Felix, Behrooz Z Alizadeh, L Adrienne Cupples, John R B Perry, Andrew P Morris[show abstract] [hide abstract]
ABSTRACT: Many disorders are associated with altered serum protein concentrations, including malnutrition, cancer, and cardiovascular, kidney, and inflammatory diseases. Although these protein concentrations are highly heritable, relatively little is known about their underlying genetic determinants. Through transethnic meta-analysis of European-ancestry and Japanese genome-wide association studies, we identified six loci at genome-wide significance (p < 5 × 10(-8)) for serum albumin (HPN-SCN1B, GCKR-FNDC4, SERPINF2-WDR81, TNFRSF11A-ZCCHC2, FRMD5-WDR76, and RPS11-FCGRT, in up to 53,190 European-ancestry and 9,380 Japanese individuals) and three loci for total protein (TNFRS13B, 6q21.3, and ELL2, in up to 25,539 European-ancestry and 10,168 Japanese individuals). We observed little evidence of heterogeneity in allelic effects at these loci between groups of European and Japanese ancestry but obtained substantial improvements in the resolution of fine mapping of potential causal variants by leveraging transethnic differences in the distribution of linkage disequilibrium. We demonstrated a functional role for the most strongly associated serum albumin locus, HPN, for which Hpn knockout mice manifest low plasma albumin concentrations. Other loci associated with serum albumin harbor genes related to ribosome function, protein translation, and proteasomal degradation, whereas those associated with serum total protein include genes related to immune function. Our results highlight the advantages of transethnic meta-analysis for the discovery and fine mapping of complex trait loci and have provided initial insights into the underlying genetic architecture of serum protein concentrations and their association with human disease.The American Journal of Human Genetics 09/2012; 91(4):744-753. · 10.60 Impact Factor
Jian Yang, Ruth J F Loos, Joseph E Powell, Sarah E Medland, Elizabeth K Speliotes, Daniel I Chasman, Lynda M Rose, Gudmar Thorleifsson, Valgerdur Steinthorsdottir, Reedik Mägi, [......], David P Strachan, William G Hill, Harold Snieder, Paul M Ridker, Unnur Thorsteinsdottir, Kari Stefansson, Timothy M Frayling, Joel N Hirschhorn, Michael E Goddard, Peter M Visscher[show abstract] [hide abstract]
ABSTRACT: There is evidence across several species for genetic control of phenotypic variation of complex traits, such that the variance among phenotypes is genotype dependent. Understanding genetic control of variability is important in evolutionary biology, agricultural selection programmes and human medicine, yet for complex traits, no individual genetic variants associated with variance, as opposed to the mean, have been identified. Here we perform a meta-analysis of genome-wide association studies of phenotypic variation using ∼170,000 samples on height and body mass index (BMI) in human populations. We report evidence that the single nucleotide polymorphism (SNP) rs7202116 at the FTO gene locus, which is known to be associated with obesity (as measured by mean BMI for each rs7202116 genotype), is also associated with phenotypic variability. We show that the results are not due to scale effects or other artefacts, and find no other experiment-wise significant evidence for effects on variability, either at loci other than FTO for BMI or at any locus for height. The difference in variance for BMI among individuals with opposite homozygous genotypes at the FTO locus is approximately 7%, corresponding to a difference of ∼0.5 kilograms in the standard deviation of weight. Our results indicate that genetic variants can be discovered that are associated with variability, and that between-person variability in obesity can partly be explained by the genotype at the FTO locus. The results are consistent with reported FTO by environment interactions for BMI, possibly mediated by DNA methylation. Our BMI results for other SNPs and our height results for all SNPs suggest that most genetic variants, including those that influence mean height or mean BMI, are not associated with phenotypic variance, or that their effects on variability are too small to detect even with samples sizes greater than 100,000.Nature 09/2012; 490(7419):267-72. · 36.28 Impact Factor