Evolutionary explanations regarding the differential preference for particular traits hold that preferences arose due to traits’ association with increased potential for reproductive fitness. Assessments of physical attractiveness have been shown to be related to perceived and measured levels of health, an important fitness-related trait. Despite the robust association between physical attractiveness and health observed in the extant literature, a number of theoretical and methodological concerns remain. Specifically, the research in this area possesses a lack of specificity in terms of measures of health, a reliance on artificial social interactions in assessing physical attractiveness, a relatively infrequent use of non-student samples, and has left unaddressed the confounding effects of raters of attractiveness. Using these concerns as a springboard, the current study employed data from the National Longitudinal Study for Adolescent Health (N ≈ 15,000; aged 25 to 34 years) to assess the relationship between physical attractiveness and various specific and overall measures of health. Logistic and OLS regression models illustrated a robust association between physical attractiveness and various measures of health, controlling for a variety of confounding factors. In sum, the more attractive a respondent was rated, the less likely he or she was to report being diagnosed with a wide range of chronic diseases and neuropsychological disorders. Importantly, this finding was observed for both sexes. These analyses provide further support for physical attractiveness as a phenotypic marker of health. The findings are discussed in reference to evolutionary theory and the limitations of the study and future research suggestions are also addressed.
Dr James Higham, senior author, said: "Evolution produces adaptations that help animals thrive in a particular environment, and over time these adaptations lead to the evolution of new species.
"A key question is what mechanisms keep closely related species that overlap geographically from interbreeding, so that they are maintained as separate species.
"Our findings offer evidence for the use of visual signals to help ensure species recognition: species may evolve to look distinct specifically from the other species they are at risk of interbreeding with," Dr Higham said.
"In other words, how you end up looking is a function of how those around you look. With the primates we studied, this has a purpose: to strengthen reproductive isolation between populations."
1Stony Brook University, Stony Brook, New York, USA, 2University of Michigan, Ann Arbor, Michigan, USA
1Harvard Medical School, Boston, USA, 2Broad Institute, Cambridge, USA, 3Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
As a first step, we have developed a statistical method for inferring segments of Neandertal local ancestry in modern humans and applied this method to construct a map of Neandertal ancestry in modern non-Africans, using data from Phase 1 of the 1000 genomes project combined with a high coverage (50×) Neandertal genome. This map reveals the adaptive impact of Neandertal gene flow as we find enhanced Neandertal ancestry in genes involved in keratin filament formation as well as other biological pathways. We also observe large regions with reduced Neandertal ancestry consistent with purifying selection against introgressing Neandertal alleles in part due to these alleles contributing to hybrid male sterility.
To extend this approach to other archaic-modern human introgression events, we generated deep genome sequences of 21 people from populations with substantial Denisovan ancestry: 16 Papua New Guineans, 2 Bougainville Islanders, and 3 aboriginal individuals from Australia. We also extend our method to infer Neandertal and Denisovan local ancestry in these populations. We test whether the same evidence for hybrid male sterility is observed in this introgression event as is observed between Neandertals and modern humans.
1Eco-anthropologie et Ethnobiologie, UMR 7206 CNRS, MNHN, Univ Paris Diderot, Sorbonne Paris Cité, F-75005, Paris, France, 2Max Planck Institute for Evolutionary Anthropology, Department of Evolutionary Genetics, Leipzig, Germany
SMBE 2014: Genome-wide ancestry patterns in Easter Islanders suggest a pre-European admixture event with Native Americans
1Centre for GeoGenetics. University of Copenhagen, Copenhagen, Denmark, 2Institute of Immunology. Oslo University Hospital. University of Oslo, Oslo, Norway, 3Center for Biological Sequence Analysis. Technical University of Denmark, Kongens Lyngby, Denmark
We have generated genome-wide data for 10 unrelated reputedly non-admixed Easter Islanders. By using non-parametric multidimensional statistics and clustering methods, we show genome-wide patterns consistent with both Native American and European admixture. We infer local Polynesian, Native American and European ancestry tracts and compare their length distributions to those expected under different demographic history models. We find more support for a model with Native American admixture event that predates a European admixture event. By masking the European and Native American ancestry tracts, we reconstruct the recent history of the Easter Island population compared to other existing genotyped Oceanic populations. These results provide additional detailed insight into the demographic history of Polynesian islanders revealing an outstanding event in recent human history.
SMBE 2014: Whole genome sequencing of an Ashkenazi Jewish reference panel supports population-targeted personal genomics and illuminates Jewish and European origins
1Columbia University, New York, NY, USA, 2Yale University, New Haven, CT, USA, 3The Feinstein Institute, Manhasset, NY, USA, 4The Zucker Hillside Hospital, Glen Oaks, NY, USA, 5Icahn School of Medicine at Mount Sinai, New York, NY, USA, 6Albert Einstein College of Medicine, New York, NY, USA, 7Memorial Sloan Kettering Cancer Center, New York, NY, USA, 8The Hebrew University of Jerusalem, Jerusalem, Israel, 9Beth Israel Medical Center, New York, NY, USA
Department of Genetics, Harvard Medical School, Boston, USA
National University of Ireland Galway, Galway, Connaught, Ireland
SMBE 2014: Genotyping of 390,000 SNPs in more than forty 3,000-9,000 year old humans from the ancient Russian steppe
1Harvard Medical School, Boston, MA, USA, 2Broad Institute of Harvard and MIT, Cambridge, MA, USA, 3Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany, 4Hartwick College, Oneonta, NY, USA
We applied the SNP capture as well as mitochondrial genome enrichment to a series of 65 bones dating to between 3,000-9,000 years ago from the Samara district of Russia in the far east of Europe, a region that has been suggested to be part of the Proto-Indo-European homeland. We successfully extracted nuclear data from 10-90% of targeted SNPs for more than 40 of the samples, and for all of these samples also obtained complete mitochondrial genomes. We report three key findings:
- Samples from the Samara region possess Ancient North Eurasian (ANE) admixture related to a recently published 24,000 year old Upper Paleolithic Siberian genome. This contrasts with both European agriculturalists and with European hunter-gatherers from Luxembourg and Iberia who had little such ancestry (Lazaridis et al. arXiv.org 2013). This suggests that European steppe groups may have been be implicated in the dispersal of ANE ancestry across Europe where it is currently pervasive.
- The mtDNA composition of the steppe population is primarily West Eurasian, in contrast with northwest Russian samples of this period (Der Sarkissian et al. PLoS Genetics 2013) where an East Eurasian presence is evident.
- Samara experienced major population turnovers over time: early samples (>6000 years) belong primarily to mtDNA haplogroups U4 and U5, typical of European hunter-gatherers but later ones include haplogroups W, H, T, I, K, J.
[Via Greg Cochran.]
ESHG 2014: Causal relationship of body mass index with cardiometabolic traits and events: a Mendelian randomization analysis
Keywords: body mass index; Mendelian randomization; Cardiometabolic
Authors: M. V. Holmes1,2, L. A. Lange3, T. Palmer4, M. B. Lanktree5, IBC BMI Mendelian Randomization Group, E. E. Schadt6, F. W. Asselbergs7,8,2, A. P. Reiner9,10, B. J. Keating1; 1University of Pennsylvania, Philadelphia, PA, United States, 2University College London, London, United Kingdom, 3University of North Carolina School of Medicine at Chapel Hill, Chapel Hill, NC, United States, 4University of Warwick, Warwick, United Kingdom, 5McMaster University, Hamilton, ON, Canada, 6Mount Sinai School of Medicine, New York, NY, United States, 7University Medical Center Utrecht, Utrecht, Netherlands, 8Durrer Center for Cardiogenetic Research, Utrecht, Netherlands, 9University of Virginia, Charlottesville, VA, United States, 10Fred Hutchinson Cancer Research Center, Seattle, WA, United States.
Abstract: Elevated body mass index (BMI) associates with cardiometabolic traits on observational analysis, yet the underlying causal relationships remain unclear. We conducted Mendelian randomization analyses using 14 SNPs associated with BMI from a recent discovery analysis to investigate the causal role of BMI with cardiometabolic traits. We used eight population-based cohorts, including 34,538 individuals of European ancestry with 4,407 type 2 diabetes (T2D), 6,073 coronary heart disease (CHD) and 3,813 stroke cases. A genetically-elevated one kg/m2 increase in BMI resulted in higher levels of fasting glucose, insulin, interleukin-6 and systolic blood pressure but reduced levels of HDL-C and LDL-C (values reported in Table). Apart from LDL-C, all causal estimates were directionally concordant to observational estimates. A genetically-elevated one kg/m2 increase in BMI increased odds of T2D but did not affect risk of CHD or stroke. A meta-analysis incorporating published studies with 27,465 CHD events in 219,423 individuals yielded a pooled odds ratio of 1.04 (95%CI: 0.97, 1.12) per 1 kg/m2 increase in BMI. In conclusion, we identified causal effects of BMI on several cardiometabolic traits, however whether BMI causally impacts on CHD risk requires further evidence.
ESHG 2014: Insights into the genetic architecture of anthropometric traits using whole genome sequence data
Keywords: body mass index; whole genome sequencing; association
Authors: E. Zeggini, UK10K consortium; Wellcome Trust Sanger Institute, Hinxton, United Kingdom.
Abstract: Body weight and fat distribution measures are associated with increased risk of cardiometabolic disease. As part of the UK10K study, we have investigated the genetic architecture of anthropometric traits in 3,538 individuals with 6.5x whole genome sequence (WGS) data from the ALSPAC and TwinsUK cohorts. Variants discovered through WGS, along with those from the 1000 Genomes Project (1KGP), were imputed into additional individuals from the ALSPAC and TwinsUK cohorts with GWAS data (total sample size 9,979). We investigated association between anthropometric traits and 8.6 million low frequency and common variants (MAF>0.01). We are in the process of obtaining in silico replication of prioritised signals. In interim replication analysis across ~15,000 samples, 43 out of 66 novel signals for BMI have the same direction of effect in the replication cohorts (p-value=0.0093). We examined the concordance of the direction of effect at established loci for each trait. Out of the 31 established independent loci for BMI that were present in our data, 28 have the same direction of effect (p-value=2.3e-06). For weight, 10 out of 11 known loci (p-value=0.006), and for height 151 out of 172 loci (p-value < 2.2e-16) have the same direction of effect, respectively. We estimated the improvement in genome-wide signal captured relative to those present in HapMap 2, HapMap 3 or 1KGP. We find no appreciable increase in variance explained as density increases, suggesting that the contribution of variants with MAF>0.01 are likely to be well-captured by existing GWAS implementation. Larger sample sizes will be required to refine these estimates.
ESHG 2014: The degree of Intellectual Disability is significantly associated with an excess of Runs of Homozygosity (ROH)
Keywords: Intellectual Disability; ROH
Authors: I. Gandin1,2, F. Faletra2, M. Carella3, V. Pecile2, G. Ferrero4, E. Belligni4, P. Palumbo3, O. Palumbo3, P. Bosco5, C. Romano5, C. Belcaro1, D. Vozzi2, A. P. d'Adamo1,2; 1University of Trieste, Trieste, Italy, 2IRCCS Burlo Garofolo, Trieste, Italy, 3IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo (FG), Italy, 4AO citta' della salute e della scienza, Torino, Italy, 5IRCCS Oasi Maria SS, Troina(EN), Italy.
Abstract: Several recent studies focused on the effect of extended homozygosity on highly complex and polygenic traits where recessive inheritance may play an important role. Since excess of homozygosity might increase the risk for disorders like schizophrenia, Alzheimer disease and autism, we have set out a study to investigate the effect of ROHs on the degree of Intellectual Disability (ID). About 370 unrelated individuals with ID were collected and classified into mild/moderate ID (MM-ID) for IQ ranging from 35-40 to 70-75 and severe/profound ID (SP-ID) for IQ below 35-40. High-density SNP array data were processed with the aim of detecting and analyze ROHs. Since different array platform were used, homozygosity and ROHs mean length were compared in MM-ID vs SP-ID separately in each dataset. Results were then combined for a meta-analysis. Our data revealed an association between the amount of homozygosity and the degree of ID, according to the recent findings on autism (Gamsiz et al., 2013). Accounting for principal components to control population stratification, we tested for ROHs mean length and detected significantly (p < 0.005) longer stretches in SP-ID compared to MM-ID. Weaker association was detected in burden ROH analysis, showing an increase of the percentage of genome covered by ROHs for SP-ID cases. Extent of ROHs seems to contribute to the pathogenesis of ID, suggesting that autosomal recessive variants have a crucial role on the modulation of the severity of ID that still need to be investigated.
ESHG 2014: Polygenic risk for ADHD is associated with impaired educational achievement and lower IQ in the general population
Keywords: ADHD; Polygenic scores; Educational attainment
Authors: E. Stergiakouli1, J. Martin2, M. L. Hamshere2, A. Thapar2, D. M. Evans1, N. J. Timpson1, G. Davey Smith1; 1MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom, 2MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University School of Medicine, Cardiff, United Kingdom.
High levels of ADHD symptoms during childhood carry risk of worse academic performance and can impact on employment and earnings in adulthood. Polygenic score analysis was used to show that common risk alleles for clinical ADHD contribute to the risk of having higher ADHD symptoms in the general population (Martin et al. in press). We have used polygenic score analysis to investigate the contribution of common risk variants for clinical ADHD on educational performance and IQ in the general population.
Academic performance was assessed using results from Key Stage 3 national tests and externally marked GCSE examinations in 6,385 children from the Avon Longitudinal Study of Parents and Children (ALSPAC). Polygenic risk scores were calculated for ALSPAC children and their mothers based on the results of an ADHD GWAS (Stergiakouli et al. 2012).
ADHD polygenic scores on the children were associated with worst educational outcomes as represented by both time points and also with lower IQ scores at age 15.5 (see Table). Moreover, ADHD polygenic scores on the mothers were associated with lower IQ in the mothers and worst educational outcomes in the children (see Table).
Our results suggest that the same genetic variants that are relevant for an ADHD diagnosis are also implicated in impaired academic performance in the general population and lower IQ score in both children and adults.
ESHG 2014: A mitogenomic phylogeny of haplogroups U2e and U3: revealing the phylogenetic signals for population expansions in the Slavs prehistory
Keywords: mitochondrial DNA; molecular phylogeography; molecular evolution
Authors: B. Malyarchuk1, M. Derenko1, T. Grzybowski2, M. Perkova1, G. Denisova1, A. Litvinov1, U. Rogalla2, K. Skonieczna2; 1Institute of Biological Problems of the North, Magadan, Russian Federation, 2Institute of Forensic Medicine, Nicolaus Copernicus University, Bydgoszcz, Poland.
Abstract: To resolve the phylogeny of some uncommon and poorly studied West Eurasian mitochondrial DNA (mtDNA) haplogroups, we sequenced 32 U2e and 19 U3 complete mitogenomes of Central and Eastern Europeans (Czechs, Slovaks, Poles, Russians, Ukrainians and Belarusians) and re-analysed the available at the present time data on 74 U2e and 80 U3 complete mtDNAs. Molecular dating suggests that the coalescence time estimates are ~21 and ~35 thousand years (ky) for haplogroups U2e and U3, respectively. Detailed analysis of about 500 Slavic complete mitogenomes belonging to different haplogroups allowed us to identify a number of lineages that seem specific for Central and Eastern Europe (U3b1b, U4a2a1, U5a2a1c, U2e1b1a, U2e1b1, U3a1a, H5a1f, U5a1a1a1, U5a1c1, U2e2a1a, U4a2a, H5a2, U2e2a1d and U5a1b1b). These subhaplogroups consist of similar haplotypes revealed in different ethnic groups of modern Slavs, thereby proving the existence of ethnolinguistic community of Slavs through DNA testing. Evolutionary age of Slavic-specific subhaplogroups is calculated to approximately 3.9 ky (from 2.3 to 5.9 ky, according to the mutation rate proposed by Soares et al. (2009) for the entire mtDNA molecule). This indicates that the ancestors of modern Slavs inhabited areas of Central and Eastern Europe from the times of Bronze and Iron Ages, i.e. earlier than it was estimated on the basis of archaeological, historical and linguistic data. This study was supported by Russian Foundation for Basic Research (grant 14-04-00131) and the Program of Presidium of Russian Academy of Sciences (grant 12-I-P30-12).
Keywords: olfactory receptor clusters; Silk Road; population structure
Authors: M. Mezzavilla1,2, S. Ulivi2, P. Gasparini1,2, V. Colonna3; 1University of Trieste, Trieste, Italy, 2Institute for Maternal and Child Health - IRCCS “Burlo Garofolo”, Trieste, Italy, 3Institute of Genetics and Biophysics "A. Buzzati-Traverso", National Research Council (CNR), Napoli, Italy.
Abstract: Smell is a versatile mechanism for recognizing different odours and is mediated by olfactory receptors. While collecting phenotypes related to smell in six countries along the Silk Road, we found an increased rate of failure to discriminate odorants in individuals from Tajikistan respect to the other countries. Using haplotype-based association we linked this to a 15 kb region within olfactory receptor gene cluster on chromosome 6 (p-value 3.86e-05). This region is embedded in the largest intron of OR5V1 and is downstream OR11A1 and upstream OR12D3. We also analysed genetic variability in 1,114 unrelated samples either from the Silk Road and ten other worldwide populations at over 300,000 polymorphic sites and characterized population genetic structure of the Silk Road within a worldwide context with a resolution never obtained before. We identified genetic components peculiar to Central Asia and observed that Tajikistan behaves as an outlier population. Indeed Tajiks share a consistent number of unusually large stretches of homozygosity and have the lowest effective population size (Ne) among the studied populations, most likely as the result of past isolation and/or consanguinity. Altogether these novel findings clarify the complex genetic patterns of the Silk Road populations and suggest that the smell misperception phenotype observed in Tajikistan might be the result of a combination of genetic drift and relaxed selection at the olfactory receptors genes.
ESHG 2014: estimation of pairwise genetic correlations between hundreds of quantitative traits from population samples of thousands of individuals
Keywords: linear mixed model; genetic correlation
Authors: M. Pirinen1, C. Benner1, T. Lehtimäki2, J. G. Eriksson3,4,5, O. T. Raitakari6,7, M. Järvelin8,9,10, V. Salomaa3, S. Ripatti1,11,12; 1Institute for Molecular Medicine Finland, Helsinki, Finland, 2Department of Clinical Chemistry, Fimlab Laboratories, University of Tampere School of Medicine, Tampere, Finland, 3Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland, 4Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland, 5Unit of General Practice, Helsinki University Central Hospital, Helsinki, Finland, 6Department of Clinical Physiology and Nuclear Medicine, University of Turku and Turku University Hospital, Turku, Finland, 7Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku and Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland, 8Department of Epidemiology and Biostatistics, MRC Health Protection Agency (HPA) Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom, 9Institute of Health Sciences, University of Oulu, Oulu, Finland, 10Biocenter Oulu, University of Oulu, Oulu, Finland, 11Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom, 12Hjelt Institute, University of Helsinki, Helsinki, Finland.
Abstract: Several modern technologies, such as nuclear magnetic resonance and mass spectrometry platforms in metabolomics, produce high-dimensional phenotype data on individuals. A first step towards utilising high-dimensional phenotypes in genetic studies is to understand how their genetic components are related.
Recent algorithmic advances in multivariate linear mixed models have enabled variance component estimation for pairs of traits using population samples of individuals and genome-wide panels of SNPs. However, current methods have not been tailored for situations where hundreds of traits are available on the same set of individuals. For such settings, we introduce an algorithm that efficiently decomposes pairwise phenotypic correlations into genetic and environmental components.
We illustrate our approach with an application to 105 pairs of metabolic and anthropometric traits measured on up to 14,000 Finnish individuals. For example, we estimate that the observed phenotypic correlation (-0.41) between triglyserides (TG) and HDL cholesterol decomposes into an additive genetic correlation (-0.59, s.e. 0.06) and an environmental correlation (-0.36 s.e. 0.02).
We discuss the interpretation of genetic correlations as correlations between locus-wise genetic effects and characterise settings where prior information about genetic correlation increases statistical power to identify pleiotropic loci, i.e. loci that contribute to multiple traits.
Keywords: SHBG; polymorphism; athletes
Authors: E. S. Egorova1, L. J. Mustafina2, I. I. Ahmetov2,1; 1Kazan State Medical University, Kazan, Russian Federation, 2Volga Region State Academy of Physical Culture, Sport and Tourism, Kazan, Russian Federation.
Abstract: Testosterone regulates muscle mass and strength, bone mass, fat distribution and the production of red blood cells. Sex hormone-binding globulin (SHBG) is the key protein responsible for binding and transporting of testosterone. SHBG regulates its bioavailability and therefore its effects in the body. Polymorphism at the SHBG gene locus (rs12150660 G/T) has been associated with testosterone concentrations. Since individuals with the TT genotype have higher serum testosterone concentrations in comparison with carriers of the G allele (data from GWAS), we hypothesized that the carriage of the T allele may give some advantage for strength and power performance. The aim of the study was to investigate the association between the SHBG G/T polymorphism, athlete status and muscle mass. A total of 363 Russian athletes and 130 controls were genotyped using RT-PCR. Muscle mass was measured by body composition analyzer Tanita MC-980. The frequencies of the T allele in power-oriented athletes (n=143, 20.3%; P=0.7462), endurance-oriented athletes (n=220, 15.0%; P=0.2054) and a whole cohort of athletes (17.1%; P=0.5078) were not significantly different from controls (18.8%). However, the frequency of the T allele in elite power-oriented athletes (n=65, 26.2 vs. 12%, P=0.0061) was significantly higher as compared with elite endurance-oriented athletes (n=58). Furthermore, correlation analysis showed positive association between the T allele and muscle mass among non-elite female athletes (n=8, P=0.0072, r= 0.8729). Although more evidence is needed, one might suggest that the SHBG gene G/T polymorphism is associated with power athlete status.
Title: J17.28 - Genome-wide association analysis identifies a locus on DMD (dystrophin) gene for power athlete status in Russians
Keywords: GWAS; athlete; DMD
Authors: V. A. Naumov1, I. I. Ahmetov2, A. K. Larin1, E. V. Generozov1, N. A. Kulemin1, E. A. Ospanova1, A. V. Pavlenko1, E. S. Kostryukova1, D. G. Alexeev1, V. M. Govorun1; 1Research Institute for Physical-Chemical Medicine, Moscow, Russian Federation, 2Volga Region State Academy of Physical Culture, Sport and Tourism, Kazan, Russian Federation.
Abstract: Power athlete status is a heritable trait: around two-thirds of the variance in this phenotype is explained by genetic factors. Since power and endurance are located at the opposite extremes of a muscle performance continuum, a genome-wide association study (GWAS) of elite Russian power-oriented athletes (sprinters and strength athletes) and endurance-oriented athletes as controls was performed to identify common genetic variants associated with elite power athlete status. 102 sprinters, 86 strength athletes and 178 endurance-oriented athletes were genotyped using the Illumina® HumanOmni1-Quad BeadChips. When comparing sprinters and endurance-oriented athletes, the most significant association (P=6.2[[unable to display character: ∗]]10-7) was shown for the rs939787 polymorphism. Interestingly, this association was replicated (P=2.9[[unable to display character: ∗]]10-6) by comparing strength athletes and endurance-oriented athletes (P=3[[unable to display character: ∗]]10-8 when sprinters and strength athletes were combined). The rs939787 is located in the DMD (dystrophin) gene which plays an important role in muscle contraction and strength, linking the intracellular cytoskeleton to the extracellular matrix. In conclusion, our data suggest that the DMD gene rs939787 polymorphism is associated with elite power athlete status in Russians.
Title: J17.58 - Variations in nuclear genes are associated with elite sport performance in the Polish population
Keywords: sport performance; ACE; ACTN3
Authors: B. J. Peplonska1, K. Safranow2, J. G. Adamczyk3, M. Siewierski3, H. Sozański3, A. K. Gajewski3, M. Berdynski1, A. Maruszak1, C. Zekanowski3; 1Mossakowski Medical Research Centre Polish Academy of Sciences, Warszawa, Poland, 2Department of Biochemistry and Medical Chemistry, Pomeranian Medical University, Szczecin, Poland, 3Department of Sport’s Theory, Institute of Sport, Jozef Pilsudski University oh Physical Education in Warsaw, Warszawa, Poland.
Abstract: Objectives: Single nucleotide polymorphisms are the most common type of human genetic variation. It is widely recognized that genetic factors located in mitochondrial and nuclear genomes influence sport performance. The aim of our study was to assess whether selected nuclear DNA variants are associated with athlete performance in the Polish population.
Methods: The study group comprised 413 unrelated elite athletes and the control group consisted of 451unrelated sedentary individuals. The athletes were stratified into two subgroups: the power athletes (n=188) and the endurance ones (n=225). The study group included 284 participants of Olympic and International Games and the remaining 129 athletes were national[[unable to display character: –]]level athletes. The DNA was isolated from peripheral blood lymphocytes using standard procedures. Genotyping of 10 nuclear DNA variants (ACE, rs4341; ACTN3, rs1815739; GABPB1, rs12594956; CHRNB3, rs4950; AGT, rs699; FAAH, rs324420; PPARG, rs1801282; TFAM, rs1937; TFAM, rs 2306604; PGC1α, rs 8192678) was conducted using TaqMan method. All statistical analyses were performed using Statistica ver. 10.
Results: We showed that six polymorphisms were associated with outstanding results in power (TFAM,rs 2306604, FAAH, ACE, ACTN3) or endurance sports (CHRNB3, GABP1). Gender and sport level of athletes were also significant
Conclusion: Our study indicates that in the Polish population genetic background could influence sport performance.
Title: J17.48 - The association of REN gene polymorphism with athlete status and muscle mass
Keywords: polymorphism; REN gene; skeletal muscle
Authors: L. J. Mustafina1,2, G. N. Khafizova1, R. R. Almetova1, R. R. Kasimova1, E. S. Egorova2, I. I. Ahmetov1,2; 1Volga Region State Academy of Physical Culture, Sport and Tourism, Kazan, Russian Federation, 2Kazan State Medical University, Kazan, Russian Federation.
Abstract: The renin-angiotensin system (RAS) is supposed to be one of the regulators of skeletal muscle growth and differentiation (Zhang et al. 2003; Johnston et al. 2011). Renin (encoded by REN gene), as a component of the RAS, activates the renin-angiotensin cascade by catalyzing the conversion of angiotensinogen to angiotensin I (Rupert, 2006). The aim of present study was to investigate the association between the intron 8 83A/G (rs2368564) polymorphism of the REN gene, athlete status and muscle mass in Russians. Two hundred and sixty eight Russian athletes (90 females and 178 males) from different sporting disciplines were involved in the study. REN genotype and allele frequencies were compared to 151 controls (74 females and 77 males). Genotyping for the REN polymorphism was performed by RT-PCR. Muscle mass parameters were assessed by bioelectrical impedance analyzer Tanita MC 980 (Japan) in 125 athletes (44 females and 81 males). We found that the frequency of the REN G allele was significantly higher in power-oriented athletes (78 vs 68%; P=0.021) compared to controls and this difference was even more pronounced in elite power-oriented athletes (89%; P=0.018). Furthermore, the REN G allele was positively correlated with fat-free mass, absolute muscle mass, muscle mass of trunk and left/right legs in elite athletes. In conclusion, we have shown that the 83A/G polymorphism of the REN gene is associated with power athlete status and skeletal muscle parameters in Russians.
Keywords: Genetic introgression; Principal Component Analysis; GS:SFHS
Authors: C. Amador1, J. Huffman1, H. Trochet1, A. Campbell1, D. Porteous1, G. Scotland1, N. Hastie1, V. Vitart1, C. Hayward1, P. Navarro1, C. S. Haley1,2; 1MRC IGMM, University of Edinburgh, Edinburgh, United Kingdom, 2Roslin Institute and Royal (Dick) School of Veterinary Studies, Edinburgh, United Kingdom.
Abstract: Generation Scotland’s Scottish Family Health Study (GS:SFHS) includes over 24,000 participants from across Scotland with records for health-related traits and environmental covariates, 10,000 genotyped for ~700K SNPs. The cohort represents an important resource for the study of complex traits and diseases. We have analysed the genomic structure of GS:SFHS as a preliminary step towards choosing appropriate subsets of individuals and statistical techniques for future studies. Initially we merged the GS:SFHS data with 1092 individuals of diverse ancestries from the 1000 Genomes project and estimated genomic relationships using the ~700K SNPs. A Principal Component Analysis on the resulting relationships facilitated identification of a group of 70 individuals of likely Italian ancestry and a number of individuals with African or Asian ancestry. We characterised the amount of genetic introgression and were able to differentiate between individuals with a few small exogenous regions in their genome, and those with long exogenous haplotypes covering a large part of the genome. We found that the pattern of homozygosity was very similar to that of other European populations and identified an individual carrying a chromosome 1 uniparental disomy. Overall, there is very limited evidence for geographic differentiation or stratification of the GS:SFHS sample within Scotland. These findings provide a genomic perspective on the history of the Scottish population, and have implications for further analyses, such as studying the contributions of common and rare variants to trait heritabilities and evaluation of genomic and phenotypic prediction of disease.
Title: P16.66-M - The influence of genetics on personality development
Keywords: Personality; NEO-FFI Authors: K. B. Wolffhechel1, H. Jarmer1, S. M. van den Berg2, M. H. M. de Moor3, D. I. Boomsma3; 1Center for Biological Sequence Analysis, Technical University of Denmark, Kongens Lyngby, Denmark, 2Department of Research Methodology, Measurement and Data Analysis, University of Twente, Enschede, Netherlands, 3Department of Biological Psychology, VU University Amsterdam, Amsterdam, Netherlands.
Abstract: Personality is known as hereditary to a certain extent. In this work we attempt to classify personality traits as binary traits based on genetic information only. For this we used the 60-item NEO-FFI and over 8 million SNPs from 6655 Dutch participants. For feature selection we performed a genome-wide association for each personality trait in a five-fold cross validation setup. All SNPs with a p-value < 0.01 were chosen as predictors for a given fold and a given personality trait, amounting to approximately 2,500 associated SNPs for each trait. An artificial neural network was trained with the SNPs as input and the personality scores as output. We found it possible to classify a person’s personality to the two sides of the scale significantly better than random. The results of this study prove in a novel way that genetics have an influence on personality. The next step is to identify, which genes these SNPs belong to, which hopefully will lead to a greater understanding of the processes involved in personality development and the onset of personality disorders.
ESHG 2014: Multiple genes of small effect and their interactions with environmental factors explain variation in personality traits
Abstract: Personality traits are thought to be endophenotypes (high Harm Avoidance (HA), low Self-directedness (SD)) for most psychiatric disorders and predictors of life outcomes. Genetic influences on personality traits are attributable to many genes of small effect and are modulated by environmental factors. We aimed to examine gene-environment (GxE) and gene-gene (GxG) interaction models based on neurotrophic factor (NGF, BDNF, NTRK2, NTRK3), serotoninergic (SLC6A4, TPH1) and dopaminergic system (DRD2, SLC6A3) gene polymorphisms contributing into personality traits variation in healthy individuals.
In total, 1018 healthy individuals (68% women) from Russia (mean age±SD: 19.81±2.65 years) without any history of psychopathologies were subjected to personality traits assessment via TCI-125 (Cloninger et al., 1993). Involved individuals are Caucasians from Russian (N=409), Tatar (N=290), Bashkir (N=130) and Udmurt populations (N=189). Socio-demographic data including gender, ethnicity, order and season of birth (SOB), place of residence, level of income, childhood maltreatment were obtained. Genotyping of 70 SNPs was performed with SNPlexTM platform (Applied Biosystems). Statistical analysis was conducted with PLINK v.1.07 corrected via FDR-procedure for multiple comparisons.
The present study revealed GxE models demonstrated BDNF Val66Met*SOB (PFDR=0.036), BDNF rs1519479*ethnicity (PFDR=0.042) and 5-HTTLPR*SOB (PFDR=0.05) interactions affected HA. Moreover, variations in SD were caused by interactions between BDNF Val66Met (PFDR=0.048), BDNF rs2030323 (PFDR=0.035) and ethnicity. Accordingly, genetic testing for BDNF and 5-HTT gene polymorphisms assuming gender, ethnicity and SOB confounding is necessary for psychopathologies prevention at early stages. This work was supported by Russian foundation for humanities grant 13-06-00583a.