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  1. Cigarette smoking behavior may have a genetic basis. We assessed evidence for quantitative trait loci (QTLs) affecting the maximum number of cigarettes smoked per day, a trait meant to quantify this behavior, ...

    Authors: Ellen L Goode, Michael D Badzioch, Helen Kim, France Gagnon, Laura S Rozek, Karen L Edwards and Gail P Jarvik
    Citation: BMC Genetics 2003 4(Suppl 1):S102

    This article is part of a Supplement: Volume 4 Supplement 1

  2. The metabolic syndrome is characterized by the clustering of several traits, including obesity, hypertension, decreased levels of HDL cholesterol, and increased levels of glucose and triglycerides. Because the...

    Authors: Catherine M Stein, Yeunjoo Song, Robert C Elston, Gyungah Jun, Hemant K Tiwari and Sudha K Iyengar
    Citation: BMC Genetics 2003 4(Suppl 1):S99

    This article is part of a Supplement: Volume 4 Supplement 1

  3. Genome-wide scan data from a community-based sample was used to identify the genetic factors that affect body mass index (BMI). BMI was defined as weight (kg) over the square of height (m), where weight and he...

    Authors: Roxana Moslehi, Alisa M Goldstein, Michael Beerman, Lynn Goldin and Andrew W Bergen
    Citation: BMC Genetics 2003 4(Suppl 1):S97

    This article is part of a Supplement: Volume 4 Supplement 1

  4. Because high blood pressure, altered lipid levels, obesity, and diabetes so frequently occur together, they are sometimes collectively referred to as the metabolic syndrome. While there have been many studies ...

    Authors: Matthew B McQueen, Lars Bertram, Eric B Rimm, Deborah Blacker and Susan L Santangelo
    Citation: BMC Genetics 2003 4(Suppl 1):S96

    This article is part of a Supplement: Volume 4 Supplement 1

  5. The multiple metabolic syndrome is defined by a clustering of risk factors for cardiovascular disease. We sought to evaluate the familial correlations of the components of the syndrome using data from the Fram...

    Authors: Kristine E Lee, Barbara EK Klein and Ronald Klein
    Citation: BMC Genetics 2003 4(Suppl 1):S94

    This article is part of a Supplement: Volume 4 Supplement 1

  6. Genes have been found to influence the age of onset of several diseases and traits. The occurrence of many chronic diseases, obesity included, appears to be strongly age-dependent. However, an analysis of pote...

    Authors: Corinne D Engelman, Heather L Brady, Anna E Baron and Jill M Norris
    Citation: BMC Genetics 2003 4(Suppl 1):S90

    This article is part of a Supplement: Volume 4 Supplement 1

  7. Systolic blood pressure (SBP) is an age-dependent complex trait for which both environmental and genetic factors may play a role in explaining variability among individuals. We performed a genome-wide scan of ...

    Authors: Dushanthi Pinnaduwage, Joseph Beyene and Shafagh Fallah
    Citation: BMC Genetics 2003 4(Suppl 1):S86

    This article is part of a Supplement: Volume 4 Supplement 1

  8. Genetic studies of complex disorders such as hypertension often utilize families selected for this outcome, usually with information obtained at a single time point. Since age-at-onset for diagnosed hypertensi...

    Authors: Karen A Kopciuk, Laurent Briollais, Florence Demenais and Shelley B Bull
    Citation: BMC Genetics 2003 4(Suppl 1):S84

    This article is part of a Supplement: Volume 4 Supplement 1

  9. Current linkage analysis methods for quantitative traits do not usually incorporate imprinting effects. Here, we carried out genome-wide linkage analysis for loci influencing adult height in the Framingham Hea...

    Authors: Nandita Mukhopadhyay and Daniel E Weeks
    Citation: BMC Genetics 2003 4(Suppl 1):S76

    This article is part of a Supplement: Volume 4 Supplement 1

  10. This paper presents a method of performing model-free LOD-score based linkage analysis on quantitative traits. It is implemented in the QMFLINK program. The method is used to perform a genome screen on the Fra...

    Authors: Jo Knight, Bernard V North, Pak C Sham and David Curtis
    Citation: BMC Genetics 2003 4(Suppl 1):S74

    This article is part of a Supplement: Volume 4 Supplement 1

  11. An empirical comparison between three different methods for estimation of pair-wise identity-by-descent (IBD) sharing at marker loci was conducted in order to quantify the resulting differences in power and lo...

    Authors: Harald HH Göring, Jeff T Williams, Thomas D Dyer and John Blangero
    Citation: BMC Genetics 2003 4(Suppl 1):S72

    This article is part of a Supplement: Volume 4 Supplement 1

  12. The goal of this study is to evaluate, compare, and contrast several standard and new linkage analysis methods. First, we compare a recently proposed confidence set approach with MAPMAKER/SIBS. Then, we evalua...

    Authors: Swati Biswas, Charalampos Papachristou, Mark E Irwin and Shili Lin
    Citation: BMC Genetics 2003 4(Suppl 1):S70

    This article is part of a Supplement: Volume 4 Supplement 1

  13. Current statistical methods for sib-pair linkage analysis of complex diseases include linear models, generalized linear models, and novel data mining techniques. The purpose of this study was to further invest...

    Authors: Zheng Guo, Xia Li, Shaoqi Rao, Kathy L Moser, Tianwen Zhang, Binsheng Gong, Gongqing Shen, Lin Li, Ruth Cannata, Erich Zirzow, Eric J Topol and Qing Wang
    Citation: BMC Genetics 2003 4(Suppl 1):S68

    This article is part of a Supplement: Volume 4 Supplement 1

  14. Our goal was to identify subgroups of sib pairs from the Framingham Heart Study data set that provided higher evidence of linkage to particular candidate regions for cardiovascular disease traits. The focus of...

    Authors: Tracy Jennifer Costello, Michael David Swartz, Mahyar Sabripour, Xiangjun Gu, Rishika Sharma and Carol Jean Etzel
    Citation: BMC Genetics 2003 4(Suppl 1):S66

    This article is part of a Supplement: Volume 4 Supplement 1

  15. Random Forest is a prediction technique based on growing trees on bootstrap samples of data, in conjunction with a random selection of explanatory variables to define the best split at each node. In the case o...

    Authors: Alexandre Bureau, Josée Dupuis, Brooke Hayward, Kathleen Falls and Paul Van Eerdewegh
    Citation: BMC Genetics 2003 4(Suppl 1):S64

    This article is part of a Supplement: Volume 4 Supplement 1

  16. A genome-wide linkage scan was performed on Replicate 1 of the simulated data for fasting triglyceride levels. The aim of this study was to implement mixed-model methodology to estimate breeding values for eac...

    Authors: Delilah Zabaneh and Ian J Mackay
    Citation: BMC Genetics 2003 4(Suppl 1):S61

    This article is part of a Supplement: Volume 4 Supplement 1

  17. Multivariate variance-components analysis provides several advantages over univariate analysis when studying correlated traits. It can test for pleiotropy or (in the longitudinal context) gene × age interactio...

    Authors: Peter Kraft, Lara Bauman, Jin Ying Yuan and Steve Horvath
    Citation: BMC Genetics 2003 4(Suppl 1):S55

    This article is part of a Supplement: Volume 4 Supplement 1

  18. A standard multivariate principal components (PCs) method was utilized to identify clusters of variables that may be controlled by a common gene or genes (pleiotropy). Heritability estimates were obtained and ...

    Authors: Jeannette T Bensen, Leslie A Lange, Carl D Langefeld, Bao-Li Chang, Eugene R Bleecker, Deborah A Meyers and Jianfeng Xu
    Citation: BMC Genetics 2003 4(Suppl 1):S53

    This article is part of a Supplement: Volume 4 Supplement 1

  19. We propose a statistical method that includes the use of longitudinal regression models and estimation procedures for adjusting for covariate effects in applying the Haseman-Elston (HE) method for linkage anal...

    Authors: Colin O Wu, Gang Zheng, Eric Leifer, Dean Follmann and Jing-Ping Lin
    Citation: BMC Genetics 2003 4(Suppl 1):S51

    This article is part of a Supplement: Volume 4 Supplement 1

  20. Family-based association testing is an important part of genetic epidemiology. Tests are available to include multiple siblings, unaffected offspring, and to adjust for environmental covariates. We explore a s...

    Authors: Laila M Poisson, Benjamin A Rybicki, Steven W Coon, Jill S Barnholtz-Sloan and Gary A Chase
    Citation: BMC Genetics 2003 4(Suppl 1):S49

    This article is part of a Supplement: Volume 4 Supplement 1

  21. Genetic heterogeneity and complex biologic mechanisms of blood pressure regulation pose significant challenges to the identification of susceptibility loci influencing hypertension. Previous linkage studies ha...

    Authors: Denise Daley, Shannon R Edwards, Yeunjoo Song, Dan Baechle, Sobha Puppala, JH Schick, Jane M Olson and Katrina AB Goddard
    Citation: BMC Genetics 2003 4(Suppl 1):S45

    This article is part of a Supplement: Volume 4 Supplement 1

  22. Missing data are a great concern in longitudinal studies, because few subjects will have complete data and missingness could be an indicator of an adverse outcome. Analyses that exclude potentially informative...

    Authors: Terri Kang, Peter Kraft, W James Gauderman and Duncan Thomas
    Citation: BMC Genetics 2003 4(Suppl 1):S43

    This article is part of a Supplement: Volume 4 Supplement 1

  23. Informative missingness of parental genotype data occurs when the genotype of a parent influences the probability of the parent's genotype data being observed. Informative missingness can occur in a number of ...

    Authors: Andrew S Allen, Julianne S Collins, Paul J Rathouz, Craig L Selander and Glen A Satten
    Citation: BMC Genetics 2003 4(Suppl 1):S39

    This article is part of a Supplement: Volume 4 Supplement 1

  24. Using the longitudinal Framingham Heart Study data on blood pressure, we analyzed the reproducibility of linkage measures from serial cross-sectional surveys of a defined population by performing genome-wide m...

    Authors: Sanjay R Patel, Juan C Celedon, Scott T Weiss and Lyle J Palmer
    Citation: BMC Genetics 2003 4(Suppl 1):S37

    This article is part of a Supplement: Volume 4 Supplement 1

  25. The purpose of this study was to estimate both cross-sectional sibling recurrence risk ratio (λ s ) and lifetime λ s for the metabolic s...

    Authors: Wei J Chen, Pi-Hua Liu, Yen-Yi Ho, Kuo-Liong Chien, Min-Tzu Lo, Wei-Liang Shih, Yu-Chun Yen and Wen-Chung Lee
    Citation: BMC Genetics 2003 4(Suppl 1):S33

    This article is part of a Supplement: Volume 4 Supplement 1

  26. With the availability of longitudinal data, age-specific (stratified) or age-adjusted genetic analyses have the potential to localize different putative trait influencing loci. If age does not influence the lo...

    Authors: Stephanie R Beck, W Mark Brown, Adrienne H Williams, June Pierce, Stephen S Rich and Carl D Langefeld
    Citation: BMC Genetics 2003 4(Suppl 1):S31

    This article is part of a Supplement: Volume 4 Supplement 1

  27. We explored three approaches to heritability and linkage analyses of longitudinal total cholesterol levels (CHOL) in the Genetic Analysis Workshop 13 simulated data without knowing the answers. The first two w...

    Authors: Qiong Yang, Irmarie Chazaro, Jing Cui, Chao-Yu Guo, Serkalem Demissie, Martin Larson, Larry D Atwood, L Adrienne Cupples and Anita L DeStefano
    Citation: BMC Genetics 2003 4(Suppl 1):S29

    This article is part of a Supplement: Volume 4 Supplement 1

  28. We propose a statistical model for linkage analysis of the longitudinal data. The proposed model is a mixed model based on the new Haseman and Elston model and allows several random effects. Specifically, the ...

    Authors: Young Ju Suh, Taesung Park and Soo Yeon Cheong
    Citation: BMC Genetics 2003 4(Suppl 1):S27

    This article is part of a Supplement: Volume 4 Supplement 1

  29. This paper describes an analysis of systolic blood pressure (SBP) in the Genetic Analysis Workshop 13 (GAW13) simulated data. The main aim was to assess evidence for both general and specific genetic effects o...

    Authors: Katrina J Scurrah, Martin D Tobin and Paul R Burton
    Citation: BMC Genetics 2003 4(Suppl 1):S25

    This article is part of a Supplement: Volume 4 Supplement 1

  30. Longitudinal data often have multiple (repeated) measures recorded along a time trajectory. For example, the two cohorts from the Framingham Heart Study (GAW13 Problem 1) contain 21 and 5 repeated measures for...

    Authors: Shaoqi Rao, Lin Li, Xia Li, Kathy L Moser, Zheng Guo, Gongqing Shen, Ruth Cannata, Erich Zirzow, Eric J Topol and Qing Wang
    Citation: BMC Genetics 2003 4(Suppl 1):S24

    This article is part of a Supplement: Volume 4 Supplement 1

  31. Family studies are often conducted in a cross-sectional manner without long-term follow-up data. The relative contribution of a gene to a specific trait could change over the lifetime. The Framingham Heart Stu...

    Authors: Rong Cheng, Naeun Park, Susan E Hodge and Suh-Hang Hank Juo
    Citation: BMC Genetics 2003 4(Suppl 1):S20

    This article is part of a Supplement: Volume 4 Supplement 1

  32. Gene × environment models are widely used to assess genetic and environmental risks and their association with a phenotype of interest for many complex diseases. Mixed generalized linear models were used to as...

    Authors: Jill S Barnholtz-Sloan, Laila M Poisson, Steven W Coon, Gary A Chase and Benjamin A Rybicki
    Citation: BMC Genetics 2003 4(Suppl 1):S18

    This article is part of a Supplement: Volume 4 Supplement 1

  33. There has been a lack of consistency in detecting chromosomal loci that are linked to obesity-related traits. This may be due, in part, to the phenotype definition. Many studies use a one-time, single measurem...

    Authors: Lisa Strug, Lei Sun and Mary Corey
    Citation: BMC Genetics 2003 4(Suppl 1):S14

    This article is part of a Supplement: Volume 4 Supplement 1

  34. The study of change in intermediate phenotypes over time is important in genetics. In this paper we explore a new approach to phenotype definition in the genetic analysis of longitudinal phenotypes. We utilize...

    Authors: Lyle J Palmer, Katrina J Scurrah, Martin Tobin, Sanjay R Patel, Juan C Celedon, Paul R Burton and Scott T Weiss
    Citation: BMC Genetics 2003 4(Suppl 1):S12

    This article is part of a Supplement: Volume 4 Supplement 1

  35. Complex diseases are generally caused by intricate interactions of multiple genes and environmental factors. Most available linkage and association methods are developed to identify individual susceptibility g...

    Authors: Sung Kim, Kui Zhang and Fengzhu Sun
    Citation: BMC Genetics 2003 4(Suppl 1):S9

    This article is part of a Supplement: Volume 4 Supplement 1

  36. The Genetic Analysis Workshop 13 simulated data aimed to mimic the major features of the real Framingham Heart Study data that formed Problem 1, but under a known inheritance model and with 100 replicates, so ...

    Authors: E Warwick Daw, John Morrison, Xiaojun Zhou and Duncan C Thomas
    Citation: BMC Genetics 2003 4(Suppl 1):S3

    This article is part of a Supplement: Volume 4 Supplement 1

  37. Since the cloning in 1990 of cDNA corresponding to mRNA transcribed at the blood-group ABO locus, polymorphisms due to ethnic and/or phenotypic variations have been reported. Some subgroups have been explained...

    Authors: Bahram Hosseini-Maaf, Åsa Hellberg, Maria J Rodrigues, M Alan Chester and Martin L Olsson
    Citation: BMC Genetics 2003 4:17
  38. Anopheles gambiae females are the world's most successful vectors of human malaria. However, a fraction of these mosquitoes is refractory to Plasmodium development. L3-5, a laboratory selected refractory strain, ...

    Authors: Liangbiao Zheng, Shuang Wang, Patricia Romans, Hongyu Zhao, Coralia Luna and Mark Q Benedict
    Citation: BMC Genetics 2003 4:16
  39. World-wide phylogeographic distribution of human complete mitochondrial DNA sequences suggested a West Asian origin for the autochthonous North African lineage U6. We report here a more detailed analysis of th...

    Authors: Nicole Maca-Meyer, Ana M González, José Pestano, Carlos Flores, José M Larruga and Vicente M Cabrera
    Citation: BMC Genetics 2003 4:15
  40. Aberrant and non-functional RHD alleles are much more frequent in Africans than in Europeans. The DAU cluster of RHD alleles exemplifies that the alleles frequent in Africans have evaded recognition until recentl...

    Authors: Franz F Wagner, Joann M Moulds, Anatole Tounkara, Bourema Kouriba and Willy A Flegel
    Citation: BMC Genetics 2003 4:14
  41. SP-A, SP-B, and SP-D are pulmonary surfactant proteins. Several linkage and association studies have been done using these genes as markers to locate pulmonary disease susceptibility genes, but few have studie...

    Authors: Wenlei Liu, Christy M Bentley and Joanna Floros
    Citation: BMC Genetics 2003 4:13
  42. The ARE insertion/deletion polymorphism of PPP1R3A has been associated with variation in glycaemic parameters and prevalence of diabetes. We have investigated its role in age of diagnosis, body weight and glycaem...

    Authors: Alex SF Doney, Bettina Fischer, Joanne E Cecil, Patricia TW Cohen, Douglas I Boyle, Graham Leese, Andrew D Morris and Colin NA Palmer
    Citation: BMC Genetics 2003 4:11
  43. It has been reported in the quantitative trait locus (QTL) literature that when testing for QTL location and effect, the statistical power supporting methodologies based on two markers and their estimated gene...

    Authors: Cynthia J Coffman, RW Doerge, Marta L Wayne and Lauren M McIntyre
    Citation: BMC Genetics 2003 4:10
  44. Cul1 is a core component of the evolutionarily conserved SCF-type ubiquitin ligases that target specific proteins for destruction. SCF action contributes to cell cycle progression but few of the key targets of...

    Authors: Jean-Karim Hériché, Dan Ang, Ethan Bier and Patrick H O'Farrell
    Citation: BMC Genetics 2003 4:9
  45. Autosomal dominant optic atrophy type 1 (DOA) is the most common form of hereditary optic atrophy in human. We have previously identified the OPA1 gene and shown that it was mutated in patients with DOA. OPA1 is ...

    Authors: Cécile Delettre, Guy Lenaers, Pascale Belenguer and Christian P Hamel
    Citation: BMC Genetics 2003 4:8
  46. Triglyceride/HDL cholesterol ratio (TG/HDL-C) is considered as a risk factor for cardiovascular events. Genetic components were important in controlling the variation in western countries. But the mode of inhe...

    Authors: Kuo-Liong Chien, Hsiu-Ching Hsu, Ta-Chen Su, Chi-Yu Yang and Yuan-Teh Lee
    Citation: BMC Genetics 2003 4:7
  47. Mutations in the gene encoding human myocilin (MYOC) have been shown to cause juvenile- and adult-onset glaucoma. In addition, myocilin has been associated with glucocorticoid-induced ocular hypertension and ster...

    Authors: Allan R Shepard, Nasreen Jacobson, Ruifang Sui, H Thomas Steely, Andrew J Lotery, Edwin M Stone and Abbot F Clark
    Citation: BMC Genetics 2003 4:5
  48. Copper is an essential trace element that plays a critical role in the survival of all living organisms. Menkes disease and occipital horn syndrome (OHS) are allelic disorders of copper transport caused by def...

    Authors: Po-Ching Liu, David M Koeller and Stephen G Kaler
    Citation: BMC Genetics 2003 4:4

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