European Human Genetics Conference (abstract database)
PPARG and PPARGC1A gene variants are associated with height in athletes
I. A. Mozhayskaya, I. I. Ahmetov, V. A. Rogozkin;
St Petersburg Research Institute of Physical Culture, St Petersburg, Russian Federation.
Presentation Number: P06.238
PPARgamma nuclear receptor positively promotes adipogenesis and negatively regulates osteoblast differentiation, indicating that PPARgamma is a negative regulator of bone mass. The Ala12 variant of PPARG gene Pro12Ala polymorphism is associated with lower transcriptional activity, increased body mass index and height in humans. PPARGC1A has been identified as a transcriptional coactivator of PPARgamma. Carriers of the Ser482 allele have been reported to have lower levels of PPARGC1A by comparison with Gly482 allele homozygotes. Therefore, one could expect that the Gly482Ser polymorphism might affect height too. The aim of the study was to investigate an association of PPARG Pro12Ala and PPARG1CA Gly482Ser polymorphisms with height in Russian male rowers and speed skaters. The study involved 99 rowers (height - 191.1 (5.4) cm, weight - 86 (9.7) kg; aged 20-27) and 64 speed skaters (height - 179.6 (6) cm, weight - 74.9 (8.8) kg; aged 20-25). Rowers were divided into three groups: the highest group (195-204 cm), the middle group (189-194 cm) and the lowest group (182-188 cm). Gene polymorphisms were determined by PCR-RLFP. We found that the presence of the PPARG 12Ala allele was significantly associated with higher body height (Ala/Ala+Pro/Ala- 182.7 (4.9) cm vs. Pro/Pro - 178.7 (6.1) cm; P=0.023) in speed skaters. The frequency of the PPARG1CA 482Ser allele was significantly higher in the highest group of rowers (33.3%), than in the middle (22.5%) and the lowest (18.8%) groups (P=0.032). In conclusion, functional polymorphisms in PPARG and PPARG1CA genes may influence the growth of the skeleton in male athletes.
Genome-wide association analysis identifies multiple loci associated with normal variation in height
M. N. Weedon1, H. Lango1, G. Lettre2, .. The GIANT Consortium1,2;
1Peninsula Medical School, Exeter, United Kingdom, 2Broad Institute, Boston, MA, United States.
Presentation Number: P07.060
There are many single gene disorders that affect stature, but little is known about the genetic variants that explain normal variation of adult height. The availability of genome-wide association data offers new opportunities to identify the genes involved in normal growth.
Recent meta-analyses of genome-wide association studies (GWAS), using up to 16,000 individuals, have identified 22 independent loci associated with height (p<5x10-8). The GIANT consortium has now extended these analyses, using imputation methods, to combine association results from 13 GWAS, with a total sample size of >32,000 individuals.
Initial meta-analysis identified 111 independent loci with p<1x10-5 and 50 with p<5x10-7. Confirmed loci implicate a wide range of molecular processes involved in normal growth. These include Hedgehog signaling (PTCH1, HHIP, IHH), chromatin remodeling (SCMH1, HMGA2), and basic cell cycling (CDK6, ANAPC13). Some of the variants and genes have been connected to other diseases, including cancer, suggesting that variants associated with height may also influence disease susceptibility. Many of the associated loci include genes known to be involved in growth based on monogenic human studies. Other loci implicate genes previously unsuspected to have a role in growth, and represent excellent candidate genes for, as yet unexplained, growth-related single gene disorders.
Combining data from many genome-wide association studies is likely to result in the identification of hundreds of loci that influence adult height. These data should result in an unprecedented increase in our knowledge of the genetics of growth and development.
A genome-wide scan of adult human stature and skeletal size
Presentation Time: Tuesday, 10:45 a.m. - 11:00 a.m.
N. Soranzo1, F. Rivadeneira2, U. Chinappen3, M. Inouye1, B. J. Richards3, S. Potter1, R. Gwilliam1, K. Papadakis4, E. Wheeler1, I. Barroso1, D. Hart5, G. Livshits6, R. J. F. Loos7, D. Strachan4, N. J. Wareham7, T. D. Spector3, A. Uitterlinden2, P. Deloukas1;
1The Wellcome Trust Sanger Institute, Hinxton, United Kingdom, 2Erasmus MC, Rotterdam, The Netherlands, 3School of Medicine, King’s College London, London, United Kingdom, 4St George's, University of London, London, United Kingdom, 5St. Thomas' Hospital, London, United Kingdom, 6Tel Aviv University, Tel Aviv, Israel, 7Institute of Metabolic Science, Cambridge, United Kingdom.
Presentation Number: C13.1
Human adult stature is a classical quantitative trait and a paradigm for genetic association studies of quantitative trait variation. We have carried out a meta-analysis of four genome-wide association scans of stature produced using the Illumina HumanHap300 SNP panel in 10,050 adults from four population-based cohorts (TwinsUK, EPIC Norfolk and 1958 Birth Cohort from the UK and the Rotterdam Study from the Netherlands). We have identified eighteen loci showing association with height with P-values of less than 10-5, which we have brought forward for replication in an independent sample of 9,000 individuals.
The signals identified provide strong evidence for replication in genomic regions previously implicated in height, including HMGA2 (rs8756, P-value = 5x10-13) and GDF5-UQCC (rs4911494, P-value = 1.5x10-10). In addition, we have identified novel candidate genetic loci for human height, some of which are in or near genes implicated in cellular growth and development (HHIP, ADAMTSL3 and DLEU7). In an attempt to dissect the mechanisms underlying human growth, we have tested the association of these novel candidate height loci with different measurements of skeletal growth. Our results provide both novel and confirmatory evidence for the implication of genes and pathways in human growth, thus contributing to the understanding of the biological processes underlying many common and severe human diseases.
Genome wide association analysis in human height of European-originated monozygotic female twins
J. A. Kettunen1,2, I. Lindqvist2, S. Ripatti2,3, T. D. Spector4, N. G. Martin5, L. Peltonen1,2, M. Perola2;
1Wellcome Trust Sanger Institute, Cambridge, United Kingdom, 2National Public Health Institute, Helsinki, Finland, 3Karolinska Institutet, Stockholm, Sweden, 4Twin Research and Genetic Epidemiology Unit, King's College, London, United Kingdom, 5Genetic Epidemiology Laboratory, Queensland Institute of Medical Research, Brisbane, Austria.
Presentation Number: P06.126
Stature (i.e. adult height) is a quantitative trait with high heritability. Various interesting regions in the human genome have been linked to adult stature but only few have been confirmed by later studies. Two genome wide association (GWA) studies have been published recently and they identified two loci (HMGA2 and GDF5-UQCC) to be strongly associated to stature after extensive replication studies. In this study we report a genome wide association analysis performed on 1631 European monozygotic female twin pairs from the GenomEUtwin consortium. One of each pair was genotyped with the Illumina HumanHap300-duo chip. Whole genome association analysis was performed with the PLINK-program. Area of residence and age were used as covariates in all of the analyses. Our study had two goals: We wanted to reduce the environmental variance by using the mean of each pair as a phenotype. We observed an association (p = 3.14*10-6) on 8q24 locus underlying the linkage peak identified previously in our linkage scan on European dizygotic twins (LOD 3.28). The replication study is underway for the most significant findings in this GWA scan. Second, we analyzed whether we could pinpoint any regions in genome which would be associated to the difference within each pair. This approach was aiming to find genes responsible for increasing variance in human height, thus potentially indicating for example GxE interaction or imprinting/gene silencing. The most significant finding for variance in stature (p = 1.22 * 10-5) was identified on 6q14 region.
Genetic analysis of adult stature in Dutch isolated population
I. V. Zorkoltseva1, T. I. Axenovich1, C. M. van Duijn2;
1Institute of Cytology and Genetics, Novosibirsk, Russian Federation, 2Department of Epidemiology & Biostatistics, Erasmus MC, Rotterdam, Netherlands.
Presentation Number: P06.008
We analysed a large complex pedigree from a Dutch genetically isolated population. About 2600 of 19700 pedigree members were phenotyped and genotyped for autosomal 5208 SNPs (Illumina 6K linkage panel). Complex segregation analysis of adult height was performed under mixed model including effects of biallelic major gene, polygene, age and sex. We used likelihood approximation based on breaking pedigree loops. The results confirmed large contribution of genes in the trait variance (h2 = 0.85 ) and significance of major gene effect in accordance with Elston-Stewart test. Three genotypic means were estimated as 183.5, 178.3 and 174.6 cm in males at 40 years with average difference of male and female genotypic means about 13 cm. The putative major gene explained 18% of trait variance.
A genome-wide scan was performed by variance-components method using Merlin program. Prior to analysis, the pedigree was split into smaller non-overlapping fragments, with maximum bit-size of 18. No loci demonstrated significant linkage, however for 6 loci linkage was suggestive:
SNP Chr Position(cM) LodScore
rs1993104 19 56.9 2.71
rs1873191 18 44.7 2.60
rs1019845 2 195.8 2.27
rs958883 5 123.3 2.15
rs936347 16 17.2 2.11
rs216223 17 2.1 2.11
Of these six loci, five were identified in previous linkage analyses, while locus at chromosome 16 (rs936347) was new.