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  1. The genes PTPN22 and HLA-DRB1 have been found by a number of studies to confer an increased risk for rheumatoid arthritis (RA), which indicates that both genes play an important role in RA etiology. It is believe...

    Authors: Bo Qiao, Chien Hsun Huang, Lei Cong, Jun Xie, Shaw-Hwa Lo and Tian Zheng
    Citation: BMC Proceedings 2009 3(Suppl 7):S132
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  2. Genome-wide association studies are widely used today to discover genetic factors that modify the risk of complex diseases. Usually, these methods work in a SNP-by-SNP fashion. We present a gene-based test tha...

    Authors: Alfonso Buil, Angel Martinez-Perez, Alexandre Perera-Lluna, Leonor Rib, Pere Caminal and Jose Manuel Soria
    Citation: BMC Proceedings 2009 3(Suppl 7):S130
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  3. Evaluation of the association between single-nucleotide polymorphisms (SNPs) and disease outcomes is widely used to identify genetic risk factors for complex diseases. Although this analysis paradigm has made ...

    Authors: Joseph Beyene, Pingzhao Hu, Jemila S Hamid, Elena Parkhomenko, Andrew D Paterson and David Tritchler
    Citation: BMC Proceedings 2009 3(Suppl 7):S128
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  4. We propose to use the rough set theory to identify genes affecting rheumatoid arthritis risk from the data collected by the North American Rheumatoid Arthritis Consortium. For each gene, we employ generalized ...

    Authors: Chatchawit Aporntewan, David H Ballard, Ji Young Lee, Joon Sang Lee, Zheyang Wu and Hongyu Zhao
    Citation: BMC Proceedings 2009 3(Suppl 7):S126
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  5. Genome-wide association studies (GWAS) have quickly become the norm in dissecting the genetic basis of complex diseases. Family-based association approaches have the advantages of being robust to possible hidd...

    Authors: Hongyan Xu, George Mathew and Varghese George
    Citation: BMC Proceedings 2009 3(Suppl 7):S124
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  6. We used Genetic Analysis Workshop 16 Problem 3 Framingham Heart Study simulated data set to compare methods for association analysis of quantitative traits in related individuals. More specifically, we investi...

    Authors: Aude Saint Pierre, Zulma Vitezica and Maria Martinez
    Citation: BMC Proceedings 2009 3(Suppl 7):S122
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  7. The power of linkage analysis of a quantitative disease endophenotype was compared for the following family selection designs: 1) Random samples: randomly chosen nuclear families, 2) "coronary artery calcifica...

    Authors: Chengrui Huang, Ke Li, Rose Saint Fleur, Su-Wei Chang, Seung Hoan Choi, Tong Shen, So Youn Shin, Stephen J Finch and Nancy R Mendell
    Citation: BMC Proceedings 2009 3(Suppl 7):S120
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  8. In order to evaluate the population impact of putative causal genetic variants over the life course of disease, we extended the static estimation of population-attributable risk fraction and developed a novel ...

    Authors: Yu Yan, Yijuan Hu, Kari E North, Nora Franceschini and Danyu Lin
    Citation: BMC Proceedings 2009 3(Suppl 7):S118
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  9. We investigated the association of metabolic syndrome (MetS) with a 500 k and a 50 k single-nucleotide polymorphism (SNP) gene chip in the Framingham Heart Study. We cross-sectionally evaluated the MetS longit...

    Authors: Yong-Moon Park, Michael A Province, Xiaoyi Gao, Mary Feitosa, Jun Wu, Duanduan Ma, DC Rao and Aldi T Kraja
    Citation: BMC Proceedings 2009 3(Suppl 7):S116
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  10. To account for population stratification in association studies, principal-components analysis is often performed on single-nucleotide polymorphisms (SNPs) across the genome. Here, we use Framingham Heart Stud...

    Authors: Sun Jung Kang, Emma K Larkin, Yeunjoo Song, Jill Barnholtz-Sloan, Dan Baechle, Tao Feng and Xiaofeng Zhu
    Citation: BMC Proceedings 2009 3(Suppl 7):S107
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  11. Linkage disequilibrium (LD) is an important measure used in the analysis of single-nucleotide polymorphism (SNP) data. We used the Genetic Analysis Workshop 16 (GAW16) Framingham Heart Study 500 k SNP data to ...

    Authors: Qimei He and Bradley J Willcox
    Citation: BMC Proceedings 2009 3(Suppl 7):S105
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  12. The power of genome-wide association studies can be improved by incorporating information from previous study findings, for example, results of genome-wide linkage analyses. Weighted false-discovery rate (FDR)...

    Authors: Yun Joo Yoo, Dushanthi Pinnaduwage, Daryl Waggott, Shelley B Bull and Lei Sun
    Citation: BMC Proceedings 2009 3(Suppl 7):S103
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  13. We performed association analysis under a previous linkage peak on chromosome 16 with genome-wide single-nucleotide polymorphism (SNP) data to identify genetic variants underlying body mass index (BMI). Data f...

    Authors: Xiaohui Li, Ling Mei, Kai Yang, Jerome I Rotter and Xiuqing Guo
    Citation: BMC Proceedings 2009 3(Suppl 7):S101
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  14. Complex traits are often manifested by multiple correlated traits. One example of this is hypertension (HTN), which is measured on a continuous scale by systolic blood pressure (SBP). Predisposition to HTN is ...

    Authors: Courtney Gray-McGuire, Yeunjoo Song, Nathan J Morris and Catherine M Stein
    Citation: BMC Proceedings 2009 3(Suppl 7):S99
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  15. In genome-wide association studies (GWAS) genetic markers are often ranked to select genes for further pursuit. Especially for moderately associated and interrelated genes, information on genes and pathways ma...

    Authors: Melanie Sohns, Albert Rosenberger and Heike Bickeböller
    Citation: BMC Proceedings 2009 3(Suppl 7):S95
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  16. Genome-wide association studies (GWAS) test hundreds of thousands of single-nucleotide polymorphisms (SNPs) for association to a trait, treating each marker equally and ignoring prior evidence of association t...

    Authors: Francesca Lantieri, Min A Jhun, Jungsun Park, Taesung Park and Marcella Devoto
    Citation: BMC Proceedings 2009 3(Suppl 7):S93
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  17. The identification of several hundred genomic regions affecting disease risk has proven the ability of genome-wide association studies have proven their ability to identify genetic contributors to disease. Cur...

    Authors: David H Ballard, Chatchawit Aporntewan, Ji Young Lee, Joon Sang Lee, Zheyang Wu and Hongyu Zhao
    Citation: BMC Proceedings 2009 3(Suppl 7):S91
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  18. Longitudinal studies that collect repeated measurements on the same subjects over time have long been considered as being more powerful and providing much better information on individual changes than cross-se...

    Authors: Gang Shi, Treva K Rice, Chi Charles Gu and Debeeru C Rao
    Citation: BMC Proceedings 2009 3(Suppl 7):S89
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  19. Age-dependent genetic effects on susceptibility to hypertension have been documented. We present a novel variance-component method for the estimation of age-dependent genetic effects on longitudinal systolic b...

    Authors: Bonnie R Joubert, Guoqing Diao, Danyu Lin, Kari E North and Nora Franceschini
    Citation: BMC Proceedings 2009 3(Suppl 7):S87
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  20. The HLA region is considered to be the main genetic risk factor for rheumatoid arthritis. Previous research demonstrated that HLA-DRB1 alleles encoding the shared epitope are specific for disease that is characte...

    Authors: Yen-Feng Chiu, Hui-Yi Kao, Yi-Shin Chen, Fang-Chi Hsu and Hsin-Chou Yang
    Citation: BMC Proceedings 2009 3(Suppl 7):S85
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  21. The aim of this study was to detect the effect of interactions between single-nucleotide polymorphisms (SNPs) on incidence of heart diseases. For this purpose, 2912 subjects with 350,160 SNPs from the Framingh...

    Authors: Li Yao, Wenjun Zhong, Zhumin Zhang, Matthew J Maenner and Corinne D Engelman
    Citation: BMC Proceedings 2009 3(Suppl 7):S83
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  22. For the Framingham Heart Study (FHS) and simulated FHS (FHSsim) data, we tested for gene-gene interaction in quantitative traits employing a longitudinal nonparametric association test (LNPT) and, for comparis...

    Authors: Dörthe Malzahn, Yesilda Balavarca, Jingky P Lozano and Heike Bickeböller
    Citation: BMC Proceedings 2009 3(Suppl 7):S80
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  23. Although several genes (including a strong effect in the human leukocyte antigen (HLA) region) and some environmental factors have been implicated to cause susceptibility to rheumatoid arthritis (RA), the etio...

    Authors: Xueying Liang, Ying Gao, Tram K Lam, Qizhai Li, Cathy Falk, Xiaohong R Yang, Alisa M Goldstein and Lynn R Goldin
    Citation: BMC Proceedings 2009 3(Suppl 7):S79
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  24. The detection of gene-gene interaction is an important approach to understand the etiology of rheumatoid arthritis (RA). The goal of this study is to identify gene-gene interaction of SNPs at the allelic level...

    Authors: Jeesun Jung, Joon Jin Song and Deukwoo Kwon
    Citation: BMC Proceedings 2009 3(Suppl 7):S76
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  25. Many phenotypes of public health importance (e.g., diabetes, coronary artery disease, major depression, obesity, and addictions to alcohol and nicotine) involve complex pathways of action. Interactions between...

    Authors: Robert Culverhouse, Wu Jin, Carol H Jin, Anthony L Hinrichs and Brian K Suarez
    Citation: BMC Proceedings 2009 3(Suppl 7):S74
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  26. Gene × gene interactions play important roles in the etiology of complex multi-factorial diseases like rheumatoid arthritis (RA). In this paper, we describe our use of a two-stage search strategy consisting of...

    Authors: Pritam Chanda, Aidong Zhang, Lara Sucheston and Murali Ramanathan
    Citation: BMC Proceedings 2009 3(Suppl 7):S72
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  27. Genetic analysis of complex diseases demands novel analytical methods to interpret data collected on thousands of variables by genome-wide association studies. The complexity of such analysis is multiplied whe...

    Authors: Wei (Will) Yang and C Charles Gu
    Citation: BMC Proceedings 2009 3(Suppl 7):S70
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  28. Random forest (RF) analysis of genetic data does not require specification of the mode of inheritance, and provides measures of variable importance that incorporate interaction effects. In this paper we descri...

    Authors: Rui Tang, Jason P Sinnwell, Jia Li, David N Rider, Mariza de Andrade and Joanna M Biernacka
    Citation: BMC Proceedings 2009 3(Suppl 7):S68
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  29. Based on a "training" sample of 1,042 subjects genotyped for 5,728 single-nucleotide polymorphisms (SNPs) of a conventional 0.4-Mb genome scan and a "test" sample of 746 subjects genotyped for 545,080 SNPs on ...

    Authors: Hans H Stassen, Katrin Hoffmann and Christian Scharfetter
    Citation: BMC Proceedings 2009 3(Suppl 7):S66
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  30. Random forests (RF) is one of a broad class of machine learning methods that are able to deal with large-scale data without model specification, which makes it an attractive method for genome-wide association ...

    Authors: Yoonhee Kim, Robert Wojciechowski, Heejong Sung, Rasika A Mathias, Li Wang, Alison P Klein, Rhoshel K Lenroot, James Malley and Joan E Bailey-Wilson
    Citation: BMC Proceedings 2009 3(Suppl 7):S64
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  31. Variable selection in genome-wide association studies can be a daunting task and statistically challenging because there are more variables than subjects. We propose an approach that uses principal-component a...

    Authors: Gina M D'Angelo, DC Rao and C Charles Gu
    Citation: BMC Proceedings 2009 3(Suppl 7):S62
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  32. In this paper, we apply the gradient-boosting machine predictive model to the rheumatoid arthritis data for predicting the case-control status. QQ-plot suggests severe population stratification. In univariate ...

    Authors: Niloofar Arshadi, Billy Chang and Rafal Kustra
    Citation: BMC Proceedings 2009 3(Suppl 7):S60
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  33. Lu and Elston have recently proposed a procedure for developing optimal receiver operating characteristic curves that maximize the area under a receiver operating characteristic curve in the setting of a predi...

    Authors: Neal Jeffries and Gang Zheng
    Citation: BMC Proceedings 2009 3(Suppl 7):S56
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  34. Genome-wide association is a powerful tool for the identification of genes that underlie common diseases. Genome-wide association studies generate billions of genotypes and pose significant computational chall...

    Authors: Xiang Chen, Meizhuo Zhang, Minghui Wang, Wensheng Zhu, Kelly Cho and Heping Zhang
    Citation: BMC Proceedings 2009 3(Suppl 7):S54
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  35. Problems associated with medication use and the consequent effects on genome-wide association analyses were explored using the Genetic Analysis Workshop 16 Problem 3 data. Lipid phenotypes were simulated in th...

    Authors: Treva K Rice, Yun Ju Sung, Gang Shi, C Charles Gu and DC Rao
    Citation: BMC Proceedings 2009 3(Suppl 7):S52
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  36. The Metabolic Syndrome (MetSyn), which is a clustering of traits including insulin resistance, obesity, hypertension and dyslipidemia, is estimated to have a substantial genetic component, yet few specific gen...

    Authors: Nora L Nock, Xuefeng Wang, Cheryl L Thompson, Yeunjoo Song, Dan Baechle, Paola Raska, Catherine M Stein and Courtney Gray-McGuire
    Citation: BMC Proceedings 2009 3(Suppl 7):S50
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  37. Genetic epidemiology studies often adjust for numerous potential confounders, yet the influences of confounder misclassification and selection bias are rarely considered. We used simulated data to evaluate the...

    Authors: Christy L Avery, Keri L Monda and Kari E North
    Citation: BMC Proceedings 2009 3(Suppl 7):S48
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  38. Multiple single-nucleotide polymorphisms have been associated with low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglyceride (TG) levels. In this paper, we eva...

    Authors: Stephen R Piccolo, Ryan P Abo, Kristina Allen-Brady, Nicola J Camp, Stacey Knight, Jeffrey L Anderson and Benjamin D Horne
    Citation: BMC Proceedings 2009 3(Suppl 7):S46
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  39. The high genomic density of the single-nucleotide polymorphism (SNP) sets that are typically surveyed in genome-wide association studies (GWAS) now allows the application of haplotype-based methods. Although t...

    Authors: Heejung Shim, Hyonho Chun, Corinne D Engelman and Bret A Payseur
    Citation: BMC Proceedings 2009 3(Suppl 7):S35
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  40. Using single-nucleotide polymorphisms (SNPs), we sought to predict classical class I and class II human leukocyte antigen (HLA) alleles, and test for their associations with rheumatoid arthritis (RA) in the No...

    Authors: Mathieu Lemire
    Citation: BMC Proceedings 2009 3(Suppl 7):S33
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  41. Many autoimmune diseases share similar underlying pathology and have a tendency to cluster within families, giving rise to the concept of shared susceptibility genes among them. In the Genetic Analysis Worksho...

    Authors: Harshal Deshmukh, Xana Kim-Howard and Swapan K Nath
    Citation: BMC Proceedings 2009 3(Suppl 7):S31
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  42. The interaction among multiple genes and environmental factors can affect an individual's susceptibility to disease. Some genes may not show strong marginal associations when they affect disease risk through i...

    Authors: Zheyang Wu, Chatchawit Aporntewan, David H Ballard, Ji Young Lee, Joon Sang Lee and Hongyu Zhao
    Citation: BMC Proceedings 2009 3(Suppl 7):S29
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  43. We compared family-based single-marker association analysis using Merlin and multi-marker analysis using LASSO (least absolute shrinkage and selection operator) for the low-density lipoprotein phenotype at the...

    Authors: Yun Ju Sung, Treva K Rice, Gang Shi, C Charles Gu and DC Rao
    Citation: BMC Proceedings 2009 3(Suppl 7):S27
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  44. The current trend in genome-wide association studies is to identify regions where the true disease-causing genes may lie by evaluating thousands of single-nucleotide polymorphisms (SNPs) across the whole genom...

    Authors: Seoae Cho, Haseong Kim, Sohee Oh, Kyunga Kim and Taesung Park
    Citation: BMC Proceedings 2009 3(Suppl 7):S25
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  45. Because multiple loci control complex diseases, there is great interest in testing markers simultaneously instead of one by one. In this paper, we applied two model selection algorithms: the stochastic search ...

    Authors: Sudeep Srivastava and Liang Chen
    Citation: BMC Proceedings 2009 3(Suppl 7):S21
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  46. Many phenotypes may be influenced by the prenatal environment of the mother and/or maternal care, and these maternal effects may have a heritable component. We have implemented in the computer program SOLAR a ...

    Authors: Jack W Kent Jr, Charles P Peterson, Thomas D Dyer, Laura Almasy and John Blangero
    Citation: BMC Proceedings 2009 3(Suppl 7):S19
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  47. We conducted a search for non-chromosome 6 genes that may increase risk for rheumatoid arthritis (RA). Our approach was to retrospectively ascertain three "extreme" subsamples from the North American Rheumatoi...

    Authors: Brian K Suarez, Robert Culverhouse, Carol H Jin and Anthony L Hinrichs
    Citation: BMC Proceedings 2009 3(Suppl 7):S15
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  48. Several methods have been proposed to impute genotypes at untyped markers using observed genotypes and genetic data from a reference panel. We used the Genetic Analysis Workshop 16 rheumatoid arthritis case-co...

    Authors: Joanna M Biernacka, Rui Tang, Jia Li, Shannon K McDonnell, Kari G Rabe, Jason P Sinnwell, David N Rider, Mariza de Andrade, Ellen L Goode and Brooke L Fridley
    Citation: BMC Proceedings 2009 3(Suppl 7):S5
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  49. Genetic Analysis Workshop 16 (GAW16) Problem 2 presented data from the Framingham Heart Study (FHS), an observational, prospective study of risk factors for cardiovascular disease begun in 1948. Data have been...

    Authors: L Adrienne Cupples, Nancy Heard-Costa, Monica Lee and Larry D Atwood
    Citation: BMC Proceedings 2009 3(Suppl 7):S3
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

  50. Authors: L Adrienne Cupples, Joseph Beyene, Heike Bickeböller, E Warwick Daw, M Daniele Fallin, W James Gauderman, Saurabh Ghosh, Ellen L Goode, Elizabeth R Hauser, Anthony Hinrichs, Jack W Kent Jr, Lisa J Martin, Maria Martinez, Rosalind J Neuman, Michael Province, Silke Szymczak…
    Citation: BMC Proceedings 2009 3(Suppl 7):S1
    Content type: Proceedings Published on:

    This article is part of a Supplement: Volume 3 Supplement 7

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