European Human Genetics Conference 2007 June 16 – 19, 2007 ...

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Normal variation, population genetics, genetic epidemiology ção e Colonização do Estado de São Paulo” in the early 70´s of the last century. From the collected data, information on gender, familial relationship, housing conditions, age and serological diagnostics were used. Statistical analyses were performed using some lab made programs, as well as SPSS and POINTER programs. Multiple regression analyses showed that gender have no influence on T. cruzi infection, while age and housing conditions presented significant effects. Correlation of related pairs of individuals, showed consistent positive and significant values, indicating familial aggregation. Complex segregation analysis, suggested that the best model is the dominant one, but the environmental influence cannot be excluded. The current study provides evidence of a major gene for T. cruzi infection, suggesting that it is an appropriate trait for further genetic analysis on the causal factors acting on the variability of Chagas disease. Model d t q H τ1 τ2 τ3 -2 ln L χ 2 P test ep AIC 1.Mixed* 1.000 2.096 0.605 0.421 [1] [0.5] [0] 672.40 - - - 4 680.397 2.Sporadic [0] [0] [0] [0] - - - 838.63 166.238 0.000 2vs1 0 838.635 3.No major effect** [0] [0] [0] 0.995 [1] [0.5] [0] 696.37 23.974 0.000 3vs1 1 698.372 4.No multifatorial 0.097 3.250 0.296 [0] [1] [0.5] [0] 712.27 39.869 0.000 4vs1 3 718.266 5.Recessive (d=0) [0] 2.389 0.383 0.279 [1] [0.5] [0] 682.78 10.381 0.001 5vs1 3 688.778 6.Aditive (d=0.5) [0.5] 2.782 0.454 0.019 [1] [0.5] [0] 674.09 1.688 0.194 6vs1 3 680.085 7.Dominant (d=1) [1] 2.096 0.605 0.421 [1] [0.5] [0] 672.40 0.000 1.000 7vs1 3 678.397 * „d“ value was set to upper limit. **Model estimated by lower „-2 ln L“. Supported by CNPq, FAPESP. P1161. Genetic-epidemiology study of reported number of malaria episodes in a sample from Monte Negro, RO, Brazil. A. La Luna1 , R. G. M. Ferreira1 , C. E. M. Kawamata1 , M. M. Moura2 , L. M. A. Camargo1 , H. Krieger1 ; 1 2 Instituto de Ciências Biomédicas, São Paulo, Brazil, Universidade Federal de Rondonia, Porto Velho, Brazil. Malaria is one of the main human infectious disease that affects 300 to 500 million people per year, causing the death of 1.5 to 2.7 million people in Africa, Asia and the Americas. In Brazil around 70% of the cases are due to Plasmodium vivax infection. The reported number of malaria episodes was studied on a sample of 924 individuals from Monte Negro/RO, Brazil (malaria hypo-endemic region) in order to test previous reports on a riverine population from the Western Amazonian Region (Portuchuelo, RO). The effects of gender, inbreeding, age were evaluated before a correlation study of pairs of relative was conducted. All estimates were relatively high and statistically significant showing a significant familial aggregation. It could be observed that the greatest number of malaria episodes occurs in male individuals with more than 45 years of age, probably due to a longer exposition to the causal agent. Complex segregation analysis was applied to the data, and although the free τs model showed the best fit, with somewhat non-mendelian τs values, the action of a heritable multifactorial component has to be present in order to explain the familial aggregation. The results are the same whether Duffy negative individuals are excluded from the sample or not. Further linkage studies are being conducted in order to identify probable genetic mechanisms associated to this treat. Model D t q H τ 1 τ 2 τ 3 -2 ln L χ 2 P test AIC 1.Mixed 1.000 1.513 0.230 0.065 [1] [0.5] [0] 1179.38 1187.380 3.No major effect [0] [0] [0] 0.435 [1] [0.5] [0] 1229.74 50.360 0.000 3 vs. 1 1231.740 4.No multifactorial 0.092 1.510 0.623 [0] [1] [0.5] [0] 1201.29 21.910 0.000 4 vs. 1 1207.290 5.Recessive (d=0) [0] 3.065 0.211 0.259 [1] [0.5] [0] 1170.99 8.390 0.004 5 vs.1 1176.990 7. Dominant (d=1) [1] 1.515 0.230 0.065 [1] [0.5] [0] 1179.48 0.100 0.752 7 vs. 1 1185.480 8.Free τs 1.000 1.332 0.301 0.447 1.000 1.000 0.000 962.30 208.690 0.000 8 vs 5 976.300 Supported by CNPq, FAPESP P1162. Uncovering German genetic landscapes of Ychromosome A. N. Diaz Lacava; Institute for Medical Biometry, Informatics, and Epidemiology, University of Bonn, Bonn, Germany. Widespread population data on Y-chromosomal short tandem repeats (STR) haplotypes are public available. World-wide as well as continent-wide studies of Y-STR haplotypes confirm its applicability to quantification of population genetic differentiation. 2 2 Europe evidences Y-chromosomal diversity in form of clines, primarily influenced by geography (Rosser et al., 2000). While genetic differentiation has been accounted between major European populations (Ploski et al., 2002), along present-day political borders (Kayser et al., 2005) or even between micro-geographic regions (Brion et al., 2004), Germany is regarded as quite homogeneous. Small but statistically significant differences were detected between Eastern and Western Germany (Kayser, 2005). German genetic landscapes of Y-chromosome are assessed. A genetic geographical Information system (GenGIS) was built. Y-chromosomal geographical patterns were portrayed examining 7 STR (3070 samples, recruited along 12 German locations; http://www.yhrd.org). Following the stepwise mutation model (SMM), thus taking haplotype molecular distance into account, haplotype groups were defined. First, most frequent haplotypes were identified, and then nearest neighbours, in terms of mutation steps, were clustered. Genetic landscapes were built based on spatial interpolation of haplotype and haplotypegroup frequencies with GRASS GIS. Regional patterns are analyzed. The relatively genetic homogeneity attributed to German population may be interpreted as a product of superimposed genetic landscapes. GenGIS assessment of genetic landscapes provides an insight into the spatial composition of extant, highly admixed German population. References Brion et al., Gene. 2004;329:17-25. Kayser et al., Hum Genet. 2005;117(5):428-43. Ploski et al. Hum Genet. 2002;110(6):592-600. Rosser et al., Am J Hum Genet. 2000;67(6):1526-43. P1163. Genetic polymorphism of Y chromosome short tandems repeats (Y-STRs) in the Latvian population L. Pliss 1 , A. Puzuka 2 , L. Timsa 1 , I. Pelnena 1 , V. Baumanis 1 , A. Krumina 2 ; 1 Latvian Biomedical Research and Study Centre, Riga, Latvia, 2 Riga Stradins University, Department of Medical Biology and Genetics, Riga, Latvia. Biallelic loci and short tandem repeats (STRs) positioned in the nonrecombining part of Y chromosome and paternal inheritance make it a powerful tool for studying population genetics and evolution. The aim of the present study was to evaluate Y-STRs variation in two haplogroups, I and R1a1 that form 46.6% from the total Latvian sample. A sample of 74 paternally unrelated Latvians belonging to haplogroups (hgs) I and R1a1 were analyzed at 12 Y-STR loci. One trinucleotide STR (DYS392) and 11 tetranucleotide STRs (DYS19, DYS385a, DYS385b, DYS389I, DYS389II, DYS390, DYS391, DYS393, DYS437, DYS438, and DYS439) were determined using PowerPlex ® Y System (Promega, USA). Haplotype diversity was calculated using the Arlequin 2.0 package. Y-STR analyses of Latvian hg I lineages revealed 12 different haplotypes (haplotype diversity: 0.957±0.016), 14-13-14-12-28-22-10-11- 13-16-10-11 (defined by DYS19-385a-385b-389I-389II-390-391-392- 393-437-438-439) of which occurred more frequently (25%). Among hg I Y-STRs two microsatellites were less diverse and only one allele for each of them was found (DYS392 locus-11 repeats, DYS438-10 repeats). In contrast to hg I, the haplotype diversity of haplogroup R1a1 was 0.986±0.003, where 51 distinct haplotypes were detected and six of them were found in more than one individual, comprising 11.8% of hg R1a1 Y chromosomes in Latvian males. We have detected two predominant alleles at DYS392 and DYS 393 loci (11 and 12) that make up 94% of the total microsatellite variation in the Latvian population. The analysis of associated Y-STRs revealed differences between microsatellite diversity within two distinct phylogenetic branches, haplogroups R1a1 and I, in the Latvian population. P1164. The association of gene variants with physical performance in middle school-age children I. V. Astratenkova, I. I. Ahmetov, D. N. Gavrilov, A. M. Druzhevskaya, A. V. Malinin, E. E. Romanova, V. A. Rogozkin; St Petersburg Research Institute of Physical Culture, St Petersburg, Russian Federation. The aim of the study was to determine the association between ACE I/D, ACTN3 R577X and PPARA intron 7 G/C gene variants and anthropometrical and performance-related traits in 457 middle school-age children. The assessment of physical performance and anthropometry was conducted with a number of physical and physiological tests.
Normal variation, population genetics, genetic epidemiology Gene variants were determined by PCR. The discovered correlations concerned primarily sprint performance traits, being in agreement with the generally accepted data: the ACE D, ACTN3 R and PPARA C alleles and their different combinations were associated with the maximal values of height, weight, BMI, standing long-jump and handgrip strength, increased resting heart rate (RHR) and systolic blood pressure (SBP), whereas the ACE I and PPARA G alleles correlated with decreased RHR and SBP. In conclusion, ACE, ACTN3 and PPARA gene variants are strongly associated with several anthropometrical and performance-related traits in physically active middle school-age children. P1165. Investigating human genome-wide heterozygosity and its effects on health-related quantitative traits using dense genomewide scans O. Polasek1 , A. Carothers2 , A. Vorko-Jovic1 , Z. Biloglav1 , I. Kolcic1 , L. Zgaga1 , N. Hastie3 , C. Hayward3 , A. Wright3 , H. Campbell2 , I. Rudan2 ; 1 2 Faculty of Medicine, Zagreb, Croatia, Faculty of Medicine, Edinburgh, United Kingdom, 3MRC Human Genetics Unit, Edinburgh, United Kingdom. Aim. To investigate concordance of different measures of human heterozygosity (internal relatedness, multilocus heterozygosity - MLH) using genome wide scans of 800 STR and 317.000 SNP genetic markers; to study patterns of heterozygosity in the human genome and investigate effects on health-related traits. Materials and methods. A sample of 1026 examinees from isolated island of Vis, Croatia, with high prevalence of consanguinity was studied. Genome-wide scan using 800 STR markers was performed in all examinees, and using 317.000 SNP markers in a subset of examinees. A set of 31 health-related quantitative phenotypes was measured (e.g. blood pressure, anthropometric measurements, spirometry and biochemical parameters). Results. The average MLH (standard deviation) in 1026 examinees was 0.754 (±0.020) using STR markers (range 0.693 - 0.810), and 0.343 (±0.006) using SNP markers (0.317 - 0.352). The correlation between genealogical and marker-based (STR, SNP) estimates of individual genome-wide heterozygosity was statistically significant in all cases, but generally weaker than expected. The coefficient of correlation between residuals of estimates based on STR and SNP markers from the linear fit was r=0.434 (p
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Volume 15 Supplement 1 June 2007 ww
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Table of Contents Spoken Presentati
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Plenary Lectures Plenary Lectures P
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Plenary Lectures labile iron can be
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Concurrent Symposia S07. Vertebrate
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Concurrent Symposia S17. Towards a
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Concurrent Symposia 11 at E13.5 sim
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Concurrent Symposia 1 phomagenesis.
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cover cryptic mutations in Drosophi
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Concurrent Sessions first excluded
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Concurrent Sessions of 210 ancestry
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Concurrent Sessions C23. Literature
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Concurrent Sessions a boy with a ty
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Concurrent Sessions C40. Mutation o
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Concurrent Sessions C48. CHROMSCAN:
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Concurrent Sessions C57. RNAi-based
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Concurrent Sessions been replicated
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Concurrent Sessions involved in an
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Concurrent Sessions tion considers
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Clinical genetics lateral neurosens
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Clinical genetics apparently sporad
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Clinical genetics itar syndrome, wh
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Clinical genetics diseases, Foundat
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Clinical genetics P0041. The first
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Clinical genetics EFNB1 was found t
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Clinical genetics of the CSB gene.
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Clinical genetics growth retardatio
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Clinical genetics PCR with a modifi
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Clinical genetics pound heterozygou
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Clinical genetics plicated: two cou
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Clinical genetics P0105. APC gene m
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Clinical genetics an indication of
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Clinical genetics great importance
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Clinical genetics P0133. Hidrotic e
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Clinical genetics eight patients as
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Clinical genetics P0152. Kabuki syn
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Clinical genetics P0161. Intrafamil
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Clinical genetics matter and normal
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Clinical genetics type at 550 bands
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Clinical genetics will be confirmed
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Clinical genetics nosed. Accurate r
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Clinical genetics which has not bee
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Clinical genetics P0217. Partial mo
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Clinical genetics fested progeroid
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Clinical genetics A 29 years old ma
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Clinical genetics ing loss (HHL). I
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Clinical genetics dació Son Llatze
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Clinical genetics These preliminary
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Clinical genetics P0272. Williams S
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Cytogenetics Po02. Cytogenetics P02
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Cytogenetics to reports from Saudi
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Cytogenetics P0298. Female-specific
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Cytogenetics P0306. Lipoatrophic pa
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Cytogenetics 22 leading to the form
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Cytogenetics somal sperm and that o
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Cytogenetics University of Belgrade
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Cytogenetics Within the same metaph
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Cytogenetics Less than 10 cases of
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Cytogenetics lar markers taken from
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Cytogenetics Brain Unaffected Schiz
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Cytogenetics ability with no speech
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Cytogenetics P0389. An age based cy
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Cytogenetics P0399. Molecular Chara
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Cytogenetics ing of complex examina
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Cytogenetics letion in 5q33 in all
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Cytogenetics and his son carried th
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Prenatal diagnosis tion about famil
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Prenatal diagnosis P0443. The risk
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Prenatal diagnosis in house PCR pro
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Prenatal diagnosis P0462. Increased
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Prenatal diagnosis P0471. Preimplan
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Prenatal diagnosis agreement with w
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Prenatal diagnosis of Turner Syndro
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Cancer genetics ously defined for d
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Cancer genetics Their frequencies w
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Cancer genetics tion Clinic-Portugu
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Cancer genetics tric carcinogenesis
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Cancer genetics P0532. Secondary ch
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Cancer genetics P0542. Differential
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Cancer genetics gastric cancer risk
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Cancer genetics ania, 3 The Institu
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Cancer genetics low: 8% (8/98 sampl
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Cancer genetics P0578. Somatic mito
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Cancer genetics P0587. Differential
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Cancer genetics cinoma (ESCC), whic
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Cancer genetics method to measure t
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Cancer genetics pression (compared
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Cancer genetics to available biolog
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Molecular and biochemical basis of
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Genetic analysis, linkage, and asso
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Page 243 and 244: Genetic analysis, linkage, and asso
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Page 309 and 310: Genomics, technology, bioinformatic
Page 327 and 328: Genetic counselling, education, gen
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Genetic counselling, education, gen
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Therapy for genetic disease Po10. T
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Therapy for genetic disease P1405.
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Therapy for genetic disease exon 7
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Author Index 1 Arslan-Krichner, M.:
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Author Index Borkowska, A.: P1089 B
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Author Index Coviello, D.: P0078, P
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Author Index Estivill, X.: P1216, P
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Author Index Graf, S. A.: P0021 Gra
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Author Index 1 Josifiova, D.: PL07
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Author Index Laurier, V.: C03 Lauri
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Author Index Melo, D. G.: P0260, P0
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Author Index Osorio, P.: P0218 Osta
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Author Index Reese, T.: C06 Regal,
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Author Index 1 Shaposhnikov, S.: P0
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Author Index Touitou, I.: P0733 Tou
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Author Index Xiao, C.: P1241 Xie, G
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Keyword Index ARMR: P0907 array CGH
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Keyword Index Consanguineous marria
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Keyword Index 1 Fronto-temporal dem
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Keyword Index IRF5: P1086 IRF6: P07
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Keyword Index NBS1 gene: P0567 NBS-
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Keyword Index P1085 Rep1: P1104 rep
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Keyword Index vision: P0632 Vitamin
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Notes 1
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A natural choice in Fabry Disease P
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European Human Genetics Conference 2007 June 16 – 19, 2007 ...

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