369 results on '"Pawitan, Y."'
Search Results
52. Computational / bioinformatics
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Peach, H. F., primary, Johnson, P. W. M., additional, Johnson, S., additional, Jones, L. K., additional, Jones, M., additional, Sharpe, R., additional, Shaw, E., additional, Turtiainen, T., additional, Tuff, A., additional, Pernemalm, A., additional, Branca, M., additional, Petris, D. E., additional, Forshed, J., additional, Lewensohn, R., additional, Besse, B., additional, Lazar, V., additional, Van den Oord, J., additional, Pawitan, Y., additional, Lehtio, J., additional, Saber, M., additional, Akel, Y., additional, Ali, T., additional, Ibrahim, H., additional, Hu, X. D., additional, Dubus, E., additional, Billaud, J. N., additional, Richards, D., additional, Flannery, R., additional, Kramer, A., additional, Lerman, J., additional, and Kutchma, A., additional
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- 2012
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53. A new paradigm emerges from the study of de novo mutations in the context of neurodevelopmental disease
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Ku, C S, primary, Polychronakos, C, additional, Tan, E K, additional, Naidoo, N, additional, Pawitan, Y, additional, Roukos, D H, additional, Mort, M, additional, and Cooper, D N, additional
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- 2012
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54. Re-expression of microRNA-375 reverses both tamoxifen resistance and accompanying EMT-like properties in breast cancer
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Ward, A, primary, Balwierz, A, additional, Zhang, J D, additional, Küblbeck, M, additional, Pawitan, Y, additional, Hielscher, T, additional, Wiemann, S, additional, and Sahin, Ö, additional
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- 2012
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55. Estimating the number of true discoveries in genome-wide association studies
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Lee, Woojoo, primary, Gusnanto, A., additional, Salim, A., additional, Magnusson, P., additional, Sim, Xueling, additional, Tai, E.S., additional, and Pawitan, Y., additional
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- 2011
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56. RSI: A Novel Biomarker Predicts RT Therapeutic Benefit in Breast Cancer
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Torres-Roca, J.F., primary, Fulp, W.J., additional, Pawitan, Y., additional, Kamath, V., additional, Lee, J., additional, Harris, E.E., additional, Bergh, J., additional, and Eschrich, S., additional
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- 2011
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57. Svensson et al. Respond to "Maternal Genes and Environment in Preterm Birth"
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Svensson, A. C., primary, Sandin, S., additional, Cnattingius, S., additional, Reilly, M., additional, Pawitan, Y., additional, Hultman, C. M., additional, and Lichtenstein, P., additional
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- 2009
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58. The Singapore Genome Variation Project
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Teo, Y.Y., primary, Sim, X.L., additional, Ku, C.S., additional, Ong, R.T.H., additional, Tan, A., additional, Tantoso, E., additional, Pawitan, Y., additional, Seielstad, M., additional, Lee, E.J.D., additional, and Chia, K.S., additional
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- 2008
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59. Nine-Gene Molecular Signature Is Not Associated with Prostate Cancer Death in a Watchful Waiting Cohort
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Mucci, L. A., primary, Pawitan, Y., additional, Demichelis, F., additional, Fall, K., additional, Stark, J. R., additional, Adami, H.-O., additional, Andersson, S.-O., additional, Andren, O., additional, Eisenstein, A. S., additional, Holmberg, L., additional, Huang, W., additional, Kantoff, P. W., additional, Perner, S., additional, Stampfer, M. J., additional, Johansson, J.-E., additional, and Rubin, M. A., additional
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- 2008
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60. Filtering genes to improve sensitivity in oligonucleotide microarray data analysis
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Calza, S., primary, Raffelsberger, W., additional, Ploner, A., additional, Sahel, J., additional, Leveillard, T., additional, and Pawitan, Y., additional
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- 2007
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61. Estimation of genetic and environmental factors for melanoma onset using population-based family data
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Lindström, L., primary, Pawitan, Y., additional, Reilly, M., additional, Hemminki, K., additional, Lichtenstein, P., additional, and Czene, K., additional
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- 2006
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62. Bias in the estimation of false discovery rate in microarray studies
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Pawitan, Y., primary, Murthy, K. R. K., additional, Michiels, S., additional, and Ploner, A., additional
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- 2005
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63. Gene profile and response to treatment
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Smeds, J., primary, Miller, L.D., additional, Bjöhle, J., additional, Hall, P., additional, Klaar, S., additional, Liu, E.T., additional, Pawitan, Y., additional, Ploner, A., additional, and Bergh, J., additional
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- 2005
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64. False discovery rate, sensitivity and sample size for microarray studies
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Pawitan, Y., primary, Michiels, S., additional, Koscielny, S., additional, Gusnanto, A., additional, and Ploner, A., additional
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- 2005
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65. Modelling Association Between Two Irregularly Observed Spatiotemporal Processes by Using Maximum Covariance Analysis
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Salim, A., primary, Pawitan, Y., additional, and Bond, K., additional
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- 2005
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66. Authors' Reply
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Pawitan, Y., primary, Reilly, M., additional, Nilsson, E., additional, Cnattingius, S., additional, and Lichtenstein, P., additional
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- 2005
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67. Multicomponent variance estimation for binary traits in family-based studies
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Noh, M., primary, Yip, B., additional, Lee, Y., additional, and Pawitan, Y., additional
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- 2005
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68. Protein profiles (proteomics) discriminating between relapses versus relapse-free survival after adjuvant tamoxifen in 272 patients with primary estrogen receptor (ER) and progesterone receptor (PgR) positive breast cancer
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Linderholm, B. K., primary, Lehtio, J., additional, Ploner, A., additional, Pawitan, Y., additional, Skoog, L., additional, and Lewensohn, R., additional
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- 2004
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69. Gene expression profiling for prognosis using Cox regression
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Pawitan, Y., primary, Bjöhle, J., additional, Wedren, S., additional, Humphreys, K., additional, Skoog, L., additional, Huang, F., additional, Amler, L., additional, Shaw, P., additional, Hall, P., additional, and Bergh, J., additional
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- 2004
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70. Estimation of genetic and environmental factors for binary traits using family data
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Pawitan, Y., primary, Reilly, M., additional, Nilsson, E., additional, Cnattingius, S., additional, and Lichtenstein, P., additional
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- 2004
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71. Mixed Inverse Problems Arising in the Estimation of Calibration Factors in Positron Emission Tomography
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Pawitan, Y., primary
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- 1998
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72. Automatic estimation of the cross-spectrum of a bivariate time series
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Pawitan, Y, primary
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- 1996
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73. Data-dependent bandwidth selection for emission computed tomography reconstruction
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Pawitan, Y., primary and O'Sullivan, F., additional
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- 1993
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74. Reducing negativity artifacts in emission tomography: post-processing filtered backprojection solutions
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O'Sullivan, F., primary, Pawitan, Y., additional, and Haynor, D., additional
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- 1993
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75. Estimating the number of true discoveries in genome-wide association studies.
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Lee, Woojoo, Gusnanto, A., Salim, A., Magnusson, P., Sim, Xueling, Tai, E.S., and Pawitan, Y.
- Abstract
Recent genome-wide association studies have reported the discoveries of genetic variants of small to moderate effects. However, most studies of complex diseases face a great challenge because the number of significant variants is less than what is required to explain the disease heritability. A new approach is needed to recognize all potential discoveries in the data. In this paper, we present a practical model-free procedure to estimate the number of true discoveries as a function of the number of top-ranking SNPs together with the confidence bounds. This approach allows a practical methodology of general utility and produces relevant statistical quantities with simple interpretation. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]
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- 2012
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76. Genetic and shared environmental factors do not confound the association between birth weight and hypertension: a study among Swedish twins.
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Bergvall N, Iliadou A, Johansson S, de Faire U, Kramer MS, Pawitan Y, Pedersen NL, Lichtenstein P, and Cnattingius S
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- 2007
77. Risk and protective factors for Parkinson's disease: a study in Swedish twins.
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Wirdefeldt K, Gatz M, Pawitan Y, Pedersen NL, Wirdefeldt, Karin, Gatz, Margaret, Pawitan, Yudi, and Pedersen, Nancy L
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- 2005
78. Computing empirical likelihood from the bootstrap
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Pawitan, Y.
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- 2000
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79. Analysis of p53 mutation status in human cancer cell lines: A paradigm for cell line cross-contamination
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Berglind, H., Pawitan, Y., Kato, S., Ishioka, C., and thierry soussi
80. DEFINING AN mRNA EXPRESSION SIGNATURE OF GLEASON GRADE
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Penney, Kl, Sinnott, Ja, Falla, K., Pawitan, Y., Hoshida, Y., Kraft, P., Fiorentino, M., Perner, S., Finn, S., Stefano Calza, Flavin, R., Freedman, Ml, Setlur, S., Andersson, So, Martin, N., Kantoff, Pw, Johansson, Je, Adami, Ho, Rubin, M., Loda, M., Golub, Tr, Andre, O., Stampfer, Mj, and Mucci, La
81. Comprehensive landscape of subtype-specific coding and noncoding RNA transcripts in breast cancer
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Vu, T. N., Setia Pramana, Calza, S., Suo, C., Lee, D., and Pawitan, Y.
82. Modeling mortality fluctuations in los angeles as functions of pollution and weather effects
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Shumway, R.H., primary, Azari, A.S., additional, and Pawitan, Y., additional
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- 1988
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83. Pet Reconstruction: Improving Least Squares Solutions
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O'Sullivan, F., primary, Pawitan, Y., additional, Harrison, R.L., additional, and Lewellen, T.K., additional
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84. Metabolic imaging techniques for dynamic PET data.
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O'Sullivan, F., Pawitan, Y., Haynor, D.L., Muzi, M., and Graham, M.M.
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- 1991
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85. Pet Reconstruction: Improving Least Squares Solutions.
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O'Sullivan, F., Pawitan, Y., Harrison, R.L., and Lewellen, T.K.
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- 1990
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86. Incidence, mortality and survival patterns of prostate cancer among residents in Singapore from 1968 to 2002.
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Chia SE, Tan CS, Lim GH, Sim X, Pawitan Y, Reilly M, Mohamed Ali S, Lau W, Chia KS, Chia, Sin Eng, Tan, Chuen Seng, Lim, Gek Hsiang, Sim, Xueling, Pawitan, Yudi, Reilly, Marie, Mohamed Ali, Safiyya, Lau, Weber, and Chia, Kee Seng
- Abstract
Background: From 1968 to 2002, Singapore experienced an almost four-fold increase in prostate cancer incidence. This paper examines the incidence, mortality and survival patterns for prostate cancer among all residents in Singapore from 1968 to 2002.Methods: This is a retrospective population-based cohort study including all prostate cancer cases aged over 20 (n = 3613) reported to the Singapore Cancer Registry from 1968 to 2002. Age-standardized incidence, mortality rates and 5-year Relative Survival Ratios (RSRs) were obtained for each 5-year period. Follow-up was ascertained by matching with the National Death Register until 2002. A weighted linear regression was performed on the log-transformed age-standardized incidence and mortality rates over period.Results: The percentage increase in the age-standardized incidence rate per year was 5.0%, 5.6%, 4.0% and 1.9% for all residents, Chinese, Malays and Indians respectively. The percentage increase in age-standardized mortality rate per year was 5.7%, 6.0%, 6.6% and 2.5% for all residents, Chinese, Malays and Indians respectively. When all Singapore residents were considered, the RSRs for prostate cancer were fairly constant across the study period with slight improvement from 1995 onwards among the Chinese.Conclusion: Ethnic differences in prostate cancer incidence, mortality and survival patterns were observed. There has been a substantial improvement in RSRs since the 1990s for the Chinese. [ABSTRACT FROM AUTHOR]- Published
- 2008
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87. Tobacco use, body mass index, and the risk of leukemia and multiple myeloma: a nationwide cohort study in Sweden
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Johanna Adami, Rino Bellocco, Paolo Boffetta, Yudi Pawitan, Kazem Zendehdel, Pia Fernberg, Asa Odenbro, Fernberg, P., Odenbro, Å., Bellocco, R., Boffetta, P., Pawitan, Y., Zendehdel, K., Adami, J., Fernberg, P, Odenbro, A, Bellocco, R, Beffetta, P, Pawitan, Y, Zendehdel, K, and Adami, J
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Adult ,Male ,Cancer Research ,medicine.medical_specialty ,Tobacco, Smokeless ,Adolescent ,Rate ratio ,Body Mass Index ,Cohort Studies ,Risk Factors ,hemic and lymphatic diseases ,Internal medicine ,Acute lymphocytic leukemia ,Medicine ,Humans ,Snuff ,Prospective Studies ,Registries ,Risk factor ,Prospective cohort study ,Tobacco use body mass index risk leukemia multiple myeloma nationwide cohort study Sweden ,Aged ,Aged, 80 and over ,Sweden ,Leukemia ,business.industry ,Smoking ,Cohort Study, smoking, leukemia ,Middle Aged ,medicine.disease ,Surgery ,Cancer registry ,Oncology ,Female ,business ,Multiple Myeloma ,Body mass index ,Cohort study - Abstract
In a prospective cohort study of more than 330,000 Swedish construction workers, we explored the effect of tobacco smoking, oral moist snuff use, and body mass index (BMI) on the risk of developing leukemia (excluding chronic lymphocytic leukemia) and multiple myeloma (MM). Study subjects were participants of a health surveillance system within the building industry. Record linkage to the nationwide Swedish cancer registry, migration registry, and cause of death registry made a comprehensive follow-up available. A total of 372 incident cases of leukemia and 520 subjects with MM was ascertained. An increase in risk of acute myelogenous leukemia (AML) was observed in current smokers (incidence rate ratio, 1.50; 95% confidence interval, 1.06–2.11). Furthermore, there was an indication of a possible association between smoking intensity and risk of acute lymphocytic leukemia. Results on snuff use as well as BMI showed no association. This study confirms the role of smoking as a risk factor for AML and gives no support to the hypothesis of a role of snuff use or BMI level on the risk of leukemia or MM. [Cancer Res 2007;67(12):5983–6]
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- 2007
88. Tobacco use, body mass index and the risk of malignant lymphomas - A nationwide cohort study in Sweden
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Johanna Adami, Yudi Pawitan, Asa Odenbro, Paolo Boffetta, Pia Fernberg, Rino Bellocco, Fernberg, P., Odenbro, Å., Bellocco, R., Boffetta, P., Pawitan Y, Y., Adami, J., Fernberg, P, Odenbro, A, Bellocco, R, Boffetta, P, Pawitan, Y, and Adami, J
- Subjects
Registrie ,Adult ,Male ,Cancer Research ,medicine.medical_specialty ,Adolescent ,Body Mass Index ,Cohort Studies ,Risk Factors ,Internal medicine ,medicine ,Humans ,Registries ,Risk factor ,Prospective cohort study ,Aged ,Aged, 80 and over ,Sweden ,Tobacco use, body mass index and the risk of malignant lymphomas ,business.industry ,Risk Factor ,Smoking Tobacco ,Incidence ,Lymphoma, Non-Hodgkin ,Smoking ,Absolute risk reduction ,Middle Aged ,Hodgkin Disease ,Surgery ,Cancer registry ,Oncology ,Smokeless tobacco ,Female ,Cohort Studie ,business ,Body mass index ,Human ,Cohort study - Abstract
In the search for risk factors involved in the etiology of lymphoproliferative malignancies there is still inconsistent evidence regarding effects of smoking tobacco, and the role of smokeless tobacco is poorly investigated. New evidence indicates that excess body weight increases the risk of NHL and HD. To determine if tobacco use of various forms and high Body Mass Index (BMI) affect the occurrence of these neoplasms, we conducted a prospective cohort study on over 330,000 Swedish construction workers included in the Construction Industry Working Environment and Health program. Information on smoking, snuff dipping, height and weight was gathered by self administered questionnaires together with personal interviews. Cancer incidence was ascertained through the year 2000 by record linkage to the nationwide Swedish Cancer Registry, Migration Registry and Cause of Death Registry. At the end of follow up, 1,309 subjects had been diagnosed with NHL (including chronic lymphocytic leukemia) and 205 with HD respectively. Age adjusted incidence rate ratios were computed using Cox proportional Hazard regression modeling. Smoking cigarette, pipe or cigar was not associated with NHL or HD. There was no evidence indicating a relation between quantity and duration of smoking and NHL or HD risk. No link was found between NHL and usage of smokeless tobacco. Having a BMI of 30 or higher did not convey excess risk of developing NHL or HD compared to normal weight (BMI 18.6-24.9). We conclude that tobacco smoking and high BMI do not entail an increased risk of NHL and HD. Our findings of a relation between the duration of snuff dipping and HD need further investigation. © 2005 Wiley-Liss, Inc.
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- 2006
89. Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture
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Zhaoming Wang, André Scherag, James F. Wilson, Nancy L. Heard-Costa, Ingrid B. Borecki, Sang Hong Lee, Veronique Vitart, Zoltán Kutalik, Jeffrey R. O'Connell, Mieke D. Trip, Lu Qi, Peter Vollenweider, Jennifer L. Bragg-Gresham, Davide Gentilini, Kees Hovingh, Lynda M. Rose, Carolin Pütter, Martin Farrall, Albert V. Smith, Nicholas G. Martin, Tõnu Esko, David J. Hunter, Georg Homuth, Liming Liang, Yudi Pawitan, Winfried März, George Dedoussis, Irene Mateo Leach, Nicholas J. Wareham, Lars Lind, Thomas Illig, Andrew P. Morris, Daniele Cusi, Jouke-Jan Hottenga, Tove Fall, Themistocles L. Assimes, Massimo Mangino, Dmitry Shungin, Kari Stefansson, Anne U. Jackson, Inês Barroso, Sarah E. Medland, Lude Franke, Karen L. Mohlke, Folkert W. Asselbergs, Sarah E. Hunt, Gudmar Thorleifsson, Pablo V. Gejman, Serena Sanna, Mark I. McCarthy, David M. Evans, Joel N. Hirschhorn, Alan F. Wright, Sarah H. Wild, Patricia B. Munroe, Marcel Bruinenberg, Gonneke Willemsen, Ulf de Faire, Markku Laakso, Marja-Liisa Lokki, Andrew C. Heath, Jing Hua Zhao, Lavinia Paternoster, Jana V. van Vliet-Ostaptchouk, Sailaja Vedantam, Danyu Lin, Eric E. Schadt, Stefano Signorini, Harald Grallert, Tsegaselassie Workalemahu, Jonathan Tyrer, Albert Hofman, George Nicholson, Patrik K. E. Magnusson, Arthur W. Musk, Jian Yang, Vilmundur Gudnason, Robert C. Kaplan, Panos Deloukas, Nilesh J. Samani, Inke R. König, Frank B. Hu, Paul M. Ridker, Tamara B. Harris, Bruce H. R. Wolffenbuttel, Ellen A. Nohr, Sarah Edkins, Lambertus A. Kiemeney, Anke Hinney, Eric Boerwinkle, Klaus Stark, Ben A. Oostra, Barbara Thorand, Unnur Thorsteinsdottir, Meena Kumari, Evelin Mihailov, Caroline S. Fox, Michael Boehnke, Aroon D. Hingorani, Jonathan Stephens, Kathleen Stirrups, Inga Prokopenko, Anke Tönjes, Lili Milani, John Beilby, Carlos Iribarren, Kari E. North, Cécile Lecoeur, So-Youn Shin, Marjo-Riitta Järvelin, Matti Uusitupa, Åsa Johansson, Nancy L. Pedersen, Krista Fischer, Fernando Rivadeneira, Wolfgang Koenig, Fredrik Karpe, Antti Jula, Lindsay L. Waite, Gérard Waeber, Mustafa Atalay, Heribert Schunkert, Narisu Narisu, Sita H. Vermeulen, Bernhard R. Winkelmann, Guo Li, Anders Hamsten, Elizabeth K. Speliotes, Ivonne Jarick, Sirkka Keinänen-Kiukaanniemi, L. Adrienne Cupples, Ruth J. F. Loos, Martina Müller-Nurasyid, David-Alexandre Trégouët, Claudia Langenberg, Willem H. Ouwehand, Julius S. Ngwa, Jennifer E. Huffman, H-Erich Wichmann, Amy J. Swift, Marco M Ferrario, Leif Groop, Henrik Grönberg, Peter M. Visscher, Claes Ohlsson, Markku S. Nieminen, Aparna Radhakrishnan, Harold Snieder, Devin Absher, Albertine J. Oldehinkel, Erik Ingelsson, Anna Maria Di Blasio, M. Carola Zillikens, Veikko Salomaa, Colin N. A. Palmer, Lori L. Bonnycastle, Teresa Ferreira, Ronald P. Stolk, Annette Peters, Philippe Froguel, Michael Stumvoll, David Schlessinger, Maria Dimitriou, Timo Saaristo, Cristen J. Willer, Jarmo Virtamo, Jorma Viikari, Alena Stančáková, Mika Kivimäki, Paolo Brambilla, Jaakko Tuomilehto, Dorret I. Boomsma, Harry Campbell, Jianjun Liu, Daniel I. Chasman, Gonçalo R. Abecasis, Ilja M. Nolte, Karl-Heinz Jöckel, Reedik Mägi, Pamela A. F. Madden, Jaana Laitinen, Sonja I. Berndt, Frank Kee, Marcus E. Kleber, Jacqueline C.M. Witteman, Jouko Saramies, Francis S. Collins, Johan G. Eriksson, Melanie M. van der Klauw, Yi-Juan Hu, John F. Peden, Markus Perola, Henri Wallaschofski, Jean Ferrières, Elena Tremoli, Marjolein J. Peters, Olli T. Raitakari, Claudia Lamina, Sekar Kathiresan, Mary F. Feitosa, Diana Kuh, Tim D. Spector, Paul W. Franks, Gerjan Navis, Martin den Heijer, Christian Gieger, Kevin B. Jacobs, Andrea Ganna, Timothy M. Frayling, Iris M. Heid, Bernhard O. Boehm, Eleanor Wheeler, Sonali Pechlivanis, Miriam F. Moffatt, Brenda W.J.H. Penninx, Anna-Liisa Hartikainen, Augusto Rendon, Stefan Schreiber, Stephen J. Chanock, Andrew R. Wood, Jianxin Shi, Najaf Amin, Lenore J. Launer, Michael A. Province, Jeanette Erdmann, Mattias Lorentzon, Hugh Watkins, Johanna Kuusisto, John-Olov Jansson, David P. Strachan, Anne E. Justice, Toby Johnson, Cornelia M. van Duijn, Niina Eklund, Samuli Ripatti, Aarno Palotie, Aldi T. Kraja, Michael Preuss, Rona J. Strawbridge, Ozren Polasek, Elisabeth Widen, Barbara McKnight, Mariano Dei, Vincent Mooser, Josine L. Min, Caroline Hayward, Mika Kähönen, Peter P. Pramstaller, Femmie de Vegt, Rainer Rauramaa, Douglas F. Levinson, Diana Marek, Antonio Liuzzi, Stefan Gustafsson, Andrew A. Hicks, Gemma Cadby, Damien C. Croteau-Chonka, Mark J. Caulfield, Boris Skrobek, Lyle J. Palmer, Alexander Teumer, Ken K. Ong, Ulf Gyllensten, Anneli Pouta, Anuj Goel, Eva Albrecht, Kristian Hveem, Inger Njølstad, David Meyre, Ida Surakka, Francesca Frau, Paolo Manunta, Sabine Schipf, Carolina Medina-Gomez, Kay-Tee Khaw, Alan R. Sanders, Thorkild I. A. Sørensen, André G. Uitterlinden, Alistair S. Hall, Felix R. Day, Karol Estrada, Jennifer G. Sambrook, Eirini V. Theodoraki, Valgerdur Steinthorsdottir, Cecilia M. Lindgren, Talin Haritunian, Benjamin M. Neale, Juha Sinisalo, Kati Kristiansson, Thomas W. Winkler, Pim van der Harst, Peter S. Chines, Joyce B. J. van Meurs, Wendy L. McArdle, Andrew Wong, Grant W. Montgomery, Terho Lehtimäki, Igor Rudan, Keri L. Monda, John M. C. Connell, Jian'an Luan, Per Hall, Joshua C. Randall, Anthony J. Balmforth, Chris Power, Philippe Amouyel, Andres Metspalu, Johannes Hebebrand, Andrew D. Morris, Jaana Lindström, Liesbeth Vandenput, William O.C.M. Cookson, Hanneke Basart, Stavroula Kanoni, Elina Hyppönen, Christian Hengstenberg, Thomas W. Mühleisen, Kari Kuulasmaa, Timo A. Lakka, Nicole Soranzo, Bruce M. Psaty, Antony P. Attwood, Epidemiology, Clinical Genetics, Surgery, Erasmus School of Social and Behavioural Sciences, Public Health, Internal Medicine, Immunology, Child and Adolescent Psychiatry / Psychology, Internal medicine, Psychiatry, NCA - Brain mechanisms in health and disease, NCA - Neurobiology of mental health, EMGO - Lifestyle, overweight and diabetes, ACS - Amsterdam Cardiovascular Sciences, Cardiology, Other departments, Vascular Medicine, Biological Psychology, Cognitive Psychology, AIMMS, Neuroscience Campus Amsterdam - Neurobiology of Mental Health, EMGO+ - Lifestyle, Overweight and Diabetes, Neuroscience Campus Amsterdam - Brain Mechanisms in Health & Disease, Berndt, S, Gustafsson, S, Mägi, R, Ganna, A, Wheeler, E, Feitosa, M, Justice, A, Monda, K, Croteau Chonka, D, Day, F, Esko, T, Fall, T, Ferreira, T, Gentilini, D, Jackson, A, Luan, J, Randall, J, Vedantam, S, Willer, C, Winkler, T, Wood, A, Workalemahu, T, Hu, Y, Lee, S, Liang, L, Lin, D, Min, J, Neale, B, Thorleifsson, G, Yang, J, Albrecht, E, Amin, N, Bragg Gresham, J, Cadby, G, den Heijer, M, Eklund, N, Fischer, K, Goel, A, Hottenga, J, Huffman, J, Jarick, I, Johansson, Å, Johnson, T, Kanoni, S, Kleber, M, König, I, Kristiansson, K, Kutalik, Z, Lamina, C, Lecoeur, C, Li, G, Mangino, M, Mcardle, W, Medina Gomez, C, Müller Nurasyid, M, Ngwa, J, Nolte, I, Paternoster, L, Pechlivanis, S, Perola, M, Peters, M, Preuss, M, Rose, L, Shi, J, Shungin, D, Smith, A, Strawbridge, R, Surakka, I, Teumer, A, Trip, M, Tyrer, J, Van Vliet Ostaptchouk, J, Vandenput, L, Waite, L, Zhao, J, Absher, D, Asselbergs, F, Atalay, M, Attwood, A, Balmforth, A, Basart, H, Beilby, J, Bonnycastle, L, Brambilla, P, Bruinenberg, M, Campbell, H, Chasman, D, Chines, P, Collins, F, Connell, J, Cookson, W, De, F, U, D, Vegt, F, Dei, M, Dimitriou, M, Edkins, S, Estrada, K, Evans, D, Farrall, M, Ferrario, M, Ferrières, J, Franke, L, Frau, F, Gejman, P, Grallert, H, Grönberg, H, Gudnason, V, Hall, A, Hall, P, Hartikainen, A, Hayward, C, Heard Costa, N, Heath, A, Hebebrand, J, Homuth, G, Hu, F, Hunt, S, Hyppönen, E, Iribarren, C, Jacobs, K, Jansson, J, Jula, A, Kähönen, M, Kathiresan, S, Kee, F, Khaw, K, Kivimäki, M, Koenig, W, Kraja, A, Kumari, M, Kuulasmaa, K, Kuusisto, J, Laitinen, J, Lakka, T, Langenberg, C, Launer, L, Lind, L, Lindström, J, Liu, J, Liuzzi, A, Lokki, M, Lorentzon, M, Madden, P, Magnusson, P, Manunta, P, Marek, D, März, W, Mateo Leach, I, Mcknight, B, Medland, S, Mihailov, E, Milani, L, Montgomery, G, Mooser, V, Mühleisen, T, Munroe, P, Musk, A, Narisu, N, Navis, G, Nicholson, G, Nohr, E, Ong, K, Oostra, B, Palmer, C, Palotie, A, Peden, J, Pedersen, N, Peters, A, Polasek, O, Pouta, A, Pramstaller, P, Prokopenko, I, Pütter, C, Radhakrishnan, A, Raitakari, O, Rendon, A, Rivadeneira, F, Rudan, I, Saaristo, T, Sambrook, J, Sanders, A, Sanna, S, Saramies, J, Schipf, S, Schreiber, S, Schunkert, H, Shin, S, Signorini, S, Sinisalo, J, Skrobek, B, Soranzo, N, Stančáková, A, Stark, K, Stephens, J, Stirrups, K, Stolk, R, Stumvoll, M, Swift, A, Theodoraki, E, Thorand, B, Tregouet, D, Tremoli, E, Van der Klauw, M, van Meurs, J, Vermeulen, S, Viikari, J, Virtamo, J, Vitart, V, Waeber, G, Wang, Z, Widén, E, Wild, S, Willemsen, G, Winkelmann, B, Witteman, J, Wolffenbuttel, B, Wong, A, Wright, A, Zillikens, M, Amouyel, P, Boehm, B, Boerwinkle, E, Boomsma, D, Caulfield, M, Chanock, S, Cupples, L, Cusi, D, Dedoussis, G, Erdmann, J, Eriksson, J, Franks, P, Froguel, P, Gieger, C, Gyllensten, U, Hamsten, A, Harris, T, Hengstenberg, C, Hicks, A, Hingorani, A, Hinney, A, Hofman, A, Hovingh, K, Hveem, K, Illig, T, Jarvelin, M, Jöckel, K, Keinanen Kiukaanniemi, S, Kiemeney, L, Kuh, D, Laakso, M, Lehtimäki, T, Levinson, D, Martin, N, Metspalu, A, Morris, A, Nieminen, M, Njølstad, I, Ohlsson, C, Oldehinkel, A, Ouwehand, W, Palmer, L, Penninx, B, Power, C, Province, M, Psaty, B, Qi, L, Rauramaa, R, Ridker, P, Ripatti, S, Salomaa, V, Samani, N, Snieder, H, Sørensen, T, Spector, T, Stefansson, K, Tönjes, A, Tuomilehto, J, Uitterlinden, A, Uusitupa, M, van der Harst, P, Vollenweider, P, Wallaschofski, H, Wareham, N, Watkins, H, Wichmann, H, Wilson, J, Abecasis, G, Assimes, T, Barroso, I, Boehnke, M, Borecki, I, Deloukas, P, Fox, C, Frayling, T, Groop, L, Haritunian, T, Heid, I, Hunter, D, Kaplan, R, Karpe, F, Moffatt, M, Mohlke, K, O'Connell, J, Pawitan, Y, Schadt, E, Schlessinger, D, Steinthorsdottir, V, Strachan, D, Thorsteinsdottir, U, Van, D, Cm, Visscher, P, Di Blasio, A, Hirschhorn, J, Lindgren, C, Meyre, D, Scherag, A, Mccarthy, M, Speliotes, E, North, K, Loos, R, Ingelsson, E, Life Course Epidemiology (LCE), Center for Liver, Digestive and Metabolic Diseases (CLDM), Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Stem Cell Aging Leukemia and Lymphoma (SALL), Lifestyle Medicine (LM), Groningen Kidney Center (GKC), Vascular Ageing Programme (VAP), Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Cardiovascular Centre (CVC), Medical Research Council (MRC), Berndt, Sonja I, Gustafsson, Stefan, Mägi, Reedik, Ganna, Andrea, Lee, Sang Hong, Hyppönen, Elina Tuulikki, Ingelsson, Erik, Berndt, Si, Feitosa, Mf, Justice, Ae, Monda, Kl, CROTEAU CHONKA, Dc, Day, Fr, Jackson, Au, Randall, Jc, Willer, Cj, Winkler, Tw, Wood, Ar, Hu, Yj, Lee, Sh, Lin, Dy, Min, Jl, Neale, Bm, BRAGG GRESHAM, Jl, DEN HEIJER, M, Hottenga, Jj, Huffman, Je, Johansson, A, Kleber, Me, König, Ir, Mcardle, Wl, MEDINA GOMEZ, C, MÜLLER NURASYID, M, Nolte, Im, Peters, Mj, Rose, Lm, Smith, Av, Strawbridge, Rj, Trip, Md, VAN VLIET OSTAPTCHOUK, Jv, Waite, Ll, Zhao, Jh, Asselbergs, Fw, Attwood, Ap, Balmforth, Aj, Bonnycastle, Ll, Chasman, Di, Connell, Jm, Cookson, Wo, DE FAIRE, U, DE VEGT, F, Evans, Dm, Ferrario, Mm, Gejman, Pv, Hartikainen, Al, HEARD COSTA, Nl, Heath, Ac, Hu, Fb, Hunt, Se, Jacobs, Kb, Jansson, Jo, Khaw, Kt, Kraja, At, Laitinen, Jh, Lakka, Ta, Launer, Lj, Lokki, Ml, Madden, Pa, Magnusson, Pk, Manunta, Paolo, MATEO LEACH, I, Medland, Se, Montgomery, Gw, Mühleisen, Tw, Munroe, Pb, Musk, Aw, Nohr, Ea, Ong, Kk, Oostra, Ba, Palmer, Cn, Peden, Jf, Pramstaller, Pp, Saaristo, Te, Sambrook, Jg, Sanders, Ar, Shin, Sy, Stephens, Jc, Stolk, Rp, Swift, Aj, Theodoraki, Ev, Tregouet, Da, VAN DER KLAUW, Mm, VAN MEURS, Jb, Vermeulen, Sh, Wild, Sh, Winkelmann, Br, Witteman, Jc, Wolffenbuttel, Bh, Wright, Af, Zillikens, Mc, Boehm, Bo, Boomsma, Di, Caulfield, Mj, Chanock, Sj, Cupples, La, Dedoussis, Gv, Eriksson, Jg, Franks, Pw, Harris, Tb, Hicks, Aa, Hovingh, Kg, Jarvelin, Mr, Jöckel, Kh, KEINANEN KIUKAANNIEMI, Sm, Kiemeney, La, Levinson, Df, Martin, Ng, Morris, Ad, Oldehinkel, Aj, Ouwehand, Wh, Palmer, Lj, Province, Ma, Psaty, Bm, Ridker, Pm, Samani, Nj, Sørensen, Ti, Spector, Td, Uitterlinden, Ag, VAN DER HARST, P, Wareham, Nj, Wichmann, He, Wilson, Jf, Abecasis, Gr, Assimes, Tl, Borecki, Ib, Groop, Lc, Heid, Im, Kaplan, Rc, Moffatt, Mf, Mohlke, Kl, O'Connell, Jr, Schadt, Ee, Strachan, Dp, VAN DUIJN, Cm, Visscher, Pm, DI BLASIO, Am, Hirschhorn, Jn, Lindgren, Cm, Morris, Ap, Mccarthy, Mi, Speliotes, Ek, North, Ke, Loos, Rj, and Ingelsson, E.
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Netherlands Twin Register (NTR) ,Linkage disequilibrium ,SORTILIN ,BIO/12 - BIOCHIMICA CLINICA E BIOLOGIA MOLECOLARE CLINICA ,Medizin ,Genome-wide association study ,Aetiology, screening and detection [ONCOL 5] ,polymorphism ,Body Mass Index ,0302 clinical medicine ,Missing heritability problem ,MISSING HERITABILITY ,EXTREME OBESITY ,CONFER RISK ,POPULATION ,Genetics & Heredity ,2. Zero hunger ,Genetics ,Medical And Health Sciences ,0303 health sciences ,education.field_of_study ,Anthropometry ,COMMON VARIANTS ,Single Nucleotide ,ASSOCIATION ,Biological Sciences ,Anthropometry, Body Height ,genetics, Body Mass Index, Case-Control Studies, European Continental Ancestry Group ,genetics, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Meta-Analysis as Topic, Obesity ,genetics, Phenotype, Polymorphism ,genetics, Quantitative Trait Loci, Waist-Hip Ratio ,Phenotype ,Life Sciences & Biomedicine ,EXPRESSION ,Genotype ,Missing heritabillity ,Population ,European Continental Ancestry Group ,Quantitative Trait Loci ,EARLY-ONSET ,Genomics ,Biology ,Quantitative trait locus ,Polymorphism, Single Nucleotide ,Article ,White People ,Molecular epidemiology [NCEBP 1] ,03 medical and health sciences ,Meta-Analysis as Topic ,SDG 3 - Good Health and Well-being ,Humans ,Genetic Predisposition to Disease ,Obesity ,body height/genetics ,Polymorphism ,Allele ,Genetik ,education ,Molecular epidemiology Aetiology, screening and detection [NCEBP 1] ,030304 developmental biology ,Science & Technology ,Waist-Hip Ratio ,BMI, height, WHR, obesity, GWS ,ta3121 ,Genetic architecture ,Body Height ,BODY-MASS INDEX ,Case-Control Studies ,gene ,stature ,height ,030217 neurology & neurosurgery ,Developmental Biology ,Genome-Wide Association Study - Abstract
Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups. © 2013 Nature America, Inc. All rights reserved.
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- 2013
90. mRNA Expression Signature of Gleason Grade Predicts Lethal Prostate Cancer
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Michelangelo Fiorentino, Massimo Loda, Katja Fall, Swen Olof Andersson, Stephen P. Finn, Lorelei A. Mucci, Richard Flavin, Mark A. Rubin, Neil E. Martin, Jan-Erik Johansson, Jennifer R. Stark, Todd R. Golub, Hans-Olov Adami, Meir J. Stampfer, Sunita R. Setlur, Kathryn L. Penney, Sven Perner, Peter Kraft, Ove Andrén, Howard D. Sesso, Jennifer A. Sinnott, Matthew L. Freedman, Stefano Calza, Yujin Hoshida, Yudi Pawitan, Philip W. Kantoff, Penney KL, Sinnott JA, Fall K, Pawitan Y, Hoshida Y, Kraft P, Stark JR, Fiorentino M, Perner S, Finn S, Calza S, Flavin R, Freedman ML, Setlur S, Sesso HD, Andersson SO, Martin N, Kantoff PW, Johansson JE, Adami HO, Rubin MA, Loda M, Golub TR, Andrén O, Stampfer MJ, and Mucci LA
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Male ,Oncology ,Cancer Research ,Pathology ,medicine.medical_specialty ,medicine.medical_treatment ,Disease ,Gleason grade ,urologic and male genital diseases ,03 medical and health sciences ,Prostate cancer ,0302 clinical medicine ,Prostate ,Internal medicine ,Original Reports ,medicine ,Humans ,neoplasms ,Aged ,030304 developmental biology ,Aged, 80 and over ,0303 health sciences ,prostate cancer, gene expression, lethality ,business.industry ,Gene Expression Profiling ,Area under the curve ,Prostatic Neoplasms ,Cell Differentiation ,Middle Aged ,medicine.disease ,3. Good health ,Gene expression profiling ,medicine.anatomical_structure ,surgical procedures, operative ,030220 oncology & carcinogenesis ,Cohort ,Disease Progression ,business ,Watchful waiting - Abstract
Purpose Prostate-specific antigen screening has led to enormous overtreatment of prostate cancer because of the inability to distinguish potentially lethal disease at diagnosis. We reasoned that by identifying an mRNA signature of Gleason grade, the best predictor of prognosis, we could improve prediction of lethal disease among men with moderate Gleason 7 tumors, the most common grade, and the most indeterminate in terms of prognosis. Patients and Methods Using the complementary DNA–mediated annealing, selection, extension, and ligation assay, we measured the mRNA expression of 6,100 genes in prostate tumor tissue in the Swedish Watchful Waiting cohort (n = 358) and Physicians' Health Study (PHS; n = 109). We developed an mRNA signature of Gleason grade comparing individuals with Gleason ≤ 6 to those with Gleason ≥ 8 tumors and applied the model among patients with Gleason 7 to discriminate lethal cases. Results We built a 157-gene signature using the Swedish data that predicted Gleason with low misclassification (area under the curve [AUC] = 0.91); when this signature was tested in the PHS, the discriminatory ability remained high (AUC = 0.94). In men with Gleason 7 tumors, who were excluded from the model building, the signature significantly improved the prediction of lethal disease beyond knowing whether the Gleason score was 4 + 3 or 3 + 4 (P = .006). Conclusion Our expression signature and the genes identified may improve our understanding of the de-differentiation process of prostate tumors. Additionally, the signature may have clinical applications among men with Gleason 7, by further estimating their risk of lethal prostate cancer and thereby guiding therapy decisions to improve outcomes and reduce overtreatment.
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- 2011
91. Modeling mortality fluctuations in Los Angeles as functions of pollution and weather effects
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Pawitan, Y
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- 1988
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92. Statistical analysis of daily London mortality and associated weather and pollution effects. Final report
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Pawitan, Y
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- 1983
93. Reparametrized Firth's Logistic Regressions for Dose-Finding Study With the Biased-Coin Design.
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Kim H, Jung S, Pawitan Y, and Lee W
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Finding an adequate dose of the drug by revealing the dose-response relationship is very crucial and a challenging problem in the clinical development. The main concerns in dose-finding study are to identify a minimum effective dose (MED) in anesthesia studies and maximum tolerated dose (MTD) in oncology clinical trials. For the estimation of MED and MTD, we propose two modifications of Firth's logistic regression using reparametrization, called reparametrized Firth's logistic regression (rFLR) and ridge-penalized reparametrized Firth's logistic regression (RrFLR). The proposed methods are designed by directly reducing the small-sample bias of the maximum likelihood estimate for the parameter of interest. In addition, we develop a method on how to construct confidence intervals for rFLR and RrFLR using profile penalized likelihood. In the up-and-down biased-coin design, numerical studies confirm the superior performance of the proposed methods in terms of the mean squared error, bias, and coverage accuracy of confidence intervals., (© 2024 John Wiley & Sons Ltd.)
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- 2024
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94. Hospital-Treated Infections and Risk of Disability Worsening in Multiple Sclerosis.
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Hu Y, Frisell T, Alping P, Song H, Pawitan Y, Fang F, and Piehl F
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Objective: To investigate the association between infections and disability worsening in people with multiple sclerosis (MS) treated with either B-cell depleting therapy (rituximab) or interferon-beta/glatiramer acetate (IFN/GA)., Methods: This cohort study spanned from 2000 to 2021, using data from the Swedish MS Registry linked to national health care registries, comprising 8,759 rituximab and 7,561 IFN/GA treatment episodes. The risk of hospital-treated infection was estimated using multivariable Cox models. The association between infections and increase in Expanded Disability Status Scale (EDSS) scores was assessed using a doubly robust generalized estimating equations model. Additionally, a piece-wise exponential model analyzed events of increased disability beyond defined cut-off values, controlling for relapses, and MRI activity., Results: Compared with IFN/GA, rituximab displayed increased risk of both inpatient- and outpatient-treated infections (hazard ratio [HR], 2.08; 95% confidence interval [CI], 1.50-2.90 and HR, 1.37; 95% CI, 1.13-1.67, respectively). An inpatient-treated infection was associated with a 0.19-unit increase in EDSS (95% CI, 0.12-0.26). Degree of worsening was greatest for progressive MS, and under IFN/GA treatment, which unlike rituximab, was more commonly associated with MRI activity. After controlling for relapses and MRI activity, inpatient-treated infections were associated with disability worsening in people with relapsing-remitting MS treated with IFN/GA (HR, 2.01; 95% CI, 1.59-2.53), but not in those treated with rituximab., Interpretation: Compared to IFN/GA, rituximab doubled the infection risk, but reduced the risk of subsequent disability worsening. Further, the risk of worsening after hospital-treated infection was greater with progressive MS than with relapsing-remitting MS. Infection risk should be considered to improve long term outcomes. ANN NEUROL 2024., (© 2024 The Author(s). Annals of Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association.)
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- 2024
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95. Similarities and differences of bone marrow and peripheral blood samples from acute myeloid leukemia patients in terms of cellular heterogeneity and ex-vivo drug sensitivity.
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Caliskan G, Pawitan Y, and Vu TN
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Background: Bone marrow (BM) evaluation is the de facto standard for diagnosis, molecular analysis, risk stratification, and therapy response assessment in acute myeloid leukemia (AML), but in patients with a high number of circulating blast cells, the peripheral blood (PB) sample could provide similar information as BM. However, there is no large-scale molecular study comparing the two specimens in terms of their gene expression profiles, cellular heterogeneities, and ex-vivo drug sensitivity., Methodology: We used (i) the BEAT-AML cohort each with detailed molecular data; (ii) cell-type deconvolution to estimate leukemic and immune cell proportions between specimen types; (iii) differential expression (DE) and drug-cell type association analysis; and (iv) logistic regression models to assess the association between induction therapy response, cell-type composition and first-line drug treatment., Results: Results: We identified 207 patients having BM and 116 patients having PB samples. There was a total of 1271 DE genes (false discovery rate < 0.05) between BM and PB; the top enriched pathways in terms of DE genes belong to the immune system pathways. Aggregated ex-vivo drug response profiles from the two specimens were largely similar, as were the cellular components, except for the GMP-like cell type (17% in BM vs. 5% in PB, p -value = 2 × 10
-7 ). Among the specimen-specific results, the GMP-like subtype was associated with multiple drug resistance in BM and the ProMono-like subtype in PB. Several cell types were associated with the response to induction therapy, but the impact of specimen type on the interaction of cell type and cytarabine-associated induction therapy was not statistically significant for most cell types., Results: Conclusions: Even though there are molecular and cellular differences between BM and PB samples, they show many similarities in ex-vivo drug response profiles, indicating the clinical utility of the substantially less-invasive PB samples., Competing Interests: The authors declare no conflict of interest., (© 2024 The Author(s). eJHaem published by British Society for Haematology and John Wiley & Sons Ltd.)- Published
- 2024
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96. Gastrointestinal biopsy of normal mucosa or nonspecific inflammation and risk of neurodegenerative disease: Nationwide matched cohort study.
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Sun J, Ludvigsson JF, Roelstraete B, Pedersen NL, Pawitan Y, Wirdefeldt K, and Fang F
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- Humans, Cohort Studies, Inflammation, Biopsy, Mucous Membrane, Sweden epidemiology, Risk Factors, Neurodegenerative Diseases epidemiology, Parkinson Disease epidemiology, Alzheimer Disease
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Background and Purpose: Evidence has accumulated to support the early involvement of altered gastrointestinal (GI) function in neurodegenerative disease. However, risk of Alzheimer disease (AD) and Parkinson disease (PD) among individuals with a GI biopsy of normal mucosa or nonspecific inflammation is unknown., Methods: This matched cohort study included all individuals in Sweden with a GI biopsy of normal mucosa (n = 480,346) or nonspecific inflammation (n = 655,937) during 1965-2016 (exposed group) as well as their individually matched population references and unexposed full siblings. A flexible parametric model and stratified Cox model were used to estimate hazard ratio (HR) and its 95% confidence interval (CI)., Results: Individuals with normal mucosa or nonspecific inflammation had a higher risk of AD and PD during the 20 years after biopsy. Compared with the population references, individuals with normal mucosa had an increased risk of AD (incidence rate [IR] difference = 13.53 per 100,000 person-years, HR [95% CI] = 1.15 [1.11-1.20]) and PD (IR difference = 6.72, HR [95% CI] = 1.16 [1.10-1.23]). Elevated risk was also observed for nonspecific inflammation regarding AD (IR difference = 13.28, HR [95% CI] = 1.11 [1.08-1.14]) and PD (IR difference = 6.83, HR [95% CI] = 1.10 [1.06-1.14]). Similar results were observed in subgroup and sensitivity analyses and when comparing with their unexposed siblings., Conclusions: Individuals with a GI biopsy of normal mucosa or nonspecific inflammation had an increased risk of AD and PD. This adds new evidence of the early involvement of GI dysfunction in neurodegenerative disease., (© 2022 The Authors. European Journal of Neurology published by John Wiley & Sons Ltd on behalf of European Academy of Neurology.)
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- 2023
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97. Psychiatric disorders and subsequent risk of cardiovascular disease: a longitudinal matched cohort study across three countries.
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Shen Q, Mikkelsen DH, Luitva LB, Song H, Kasela S, Aspelund T, Bergstedt J, Lu Y, Sullivan PF, Ye W, Fall K, Tornvall P, Pawitan Y, Andreassen OA, Buil A, Milani L, Fang F, and Valdimarsdóttir U
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Background: Several psychiatric disorders have been associated with increased risk of cardiovascular disease (CVD), however, the role of familial factors and the main disease trajectories remain unknown., Methods: In this longitudinal cohort study, we identified a cohort of 900,240 patients newly diagnosed with psychiatric disorders during January 1, 1987 and December 31, 2016, their 1,002,888 unaffected full siblings, and 1:10 age- and sex-matched reference population from nationwide medical records in Sweden, who had no prior diagnosis of CVD at enrolment. We used flexible parametric models to determine the time-varying association between first-onset psychiatric disorders and incident CVD and CVD death, comparing rates of CVD among patients with psychiatric disorders to the rates of unaffected siblings and matched reference population. We also used disease trajectory analysis to identify main disease trajectories linking psychiatric disorders to CVD. Identified associations and disease trajectories of the Swedish cohort were validated in a similar cohort from nationwide medical records in Denmark (N = 875,634 patients, same criteria during January 1, 1969 and December 31, 2016) and in Estonian cohorts from the Estonian Biobank (N = 30,656 patients, same criteria during January 1, 2006 and December 31, 2020), respectively., Findings: During up to 30 years of follow-up of the Swedish cohort, the crude incidence rate of CVD was 9.7, 7.4 and 7.0 per 1000 person-years among patients with psychiatric disorders, their unaffected siblings, and the matched reference population. Compared with their siblings, patients with psychiatric disorders experienced higher rates of CVD during the first year after diagnosis (hazard ratio [HR], 1.88; 95% confidence interval [CI], 1.79-1.98) and thereafter (1.37; 95% CI, 1.34-1.39). Similar rate increases were noted when comparing with the matched reference population. These results were replicated in the Danish cohort. We identified several disease trajectories linking psychiatric disorders to CVD in the Swedish cohort, with or without mediating medical conditions, including a direct link between psychiatric disorders and hypertensive disorder, ischemic heart disease, venous thromboembolism, angina pectoris, and stroke. These trajectories were validated in the Estonian Biobank cohort., Interpretation: Independent of familial factors, patients with psychiatric disorders are at an elevated risk of subsequent CVD, particularly during first year after diagnosis. Increased surveillance and treatment of CVDs and CVD risk factors should be considered as an integral part of clinical management, in order to reduce risk of CVD among patients with psychiatric disorders., Funding: This research was supported by EU Horizon 2020 Research and Innovation Action Grant, European Research Council Consolidator grant, Icelandic Research fund, Swedish Research Council, US NIMH, the Outstanding Clinical Discipline Project of Shanghai Pudong, the Fundamental Research Funds for the Central Universities, and the European Union through the European Regional Development Fund; the Research Council of Norway; the South-East Regional Health Authority, the Stiftelsen Kristian Gerhard Jebsen, and the EEA-RO-NO-2018-0535., Competing Interests: OAA declares receiving grants or contracts from the South-East Norway Health Authority, NIH and KG Jebsen Stiftelsen, receiving consulting fees from Biogen, Cortechs.ai and Milken. OAA gets Speaker's honorarium from Janssen, Lundbeck and Sunovion, and has a patent on Intranasal Administration (US20160310683 A1). OAA participated in advisory board as National PI for JANSSEN trial depression, MAPS trial PTSD and BI trial schizophrenia. OAA declares having stock at Cortechs.ai. UAV declares receiving support from EPA2023, ISTSS2022 as keynote speaker, and serves on a NordForsk expert committee on Long COVID. FF declares receiving grants from the 10.13039/501100004359Swedish Research Council, Swedish Research Council for Health, Workinglife and Welfare, 10.13039/501100002794Swedish Cancer Society, 10.13039/501100000781European Research Council and the US CDC. FF declares getting payment from 10.13039/501100004359Swedish Research Council for grant review. All other authors declare no competing interests., (© 2023 The Author(s).)
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- 2023
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98. Comprehensive transcriptomic analysis to identify biological and clinical differences in cholangiocarcinoma.
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Silvestri M, Nghia Vu T, Nichetti F, Niger M, Di Cosimo S, De Braud F, Pruneri G, Pawitan Y, Calza S, and Cappelletti V
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- Humans, Transcriptome, Prognosis, Bile Ducts, Intrahepatic pathology, Cholangiocarcinoma pathology, Bile Duct Neoplasms pathology
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Background: Cholangiocarcinoma (CC) is a rare and aggressive disease with limited therapeutic options and a poor prognosis. All available public records of cohorts reporting transcriptomic data on intrahepatic cholangiocarcinoma (ICC) and extrahepatic cholangiocarcinoma (ECC) were collected with the aim to provide a comprehensive gene expression-based classification with clinical relevance., Methods: A total of 543 patients with primary tumor tissues profiled by RNAseq and microarray platforms from seven public datasets were used as a discovery set to identify distinct biological subgroups. Group predictors developed on the discovery sets were applied to a single cohort of 131 patients profiled with RNAseq for validation and assessment of clinical relevance leveraging machine learning techniques., Results: By unsupervised clustering analysis of gene expression data we identified both in the ICC and ECC discovery datasets four subgroups characterized by a distinct type of immune infiltrate and signaling pathways. We next developed class predictors using short gene list signatures and identified in an independent dataset subgroups of ICC tumors at different prognosis., Conclusions: The developed class-predictor allows identification of CC subgroups with specific biological features and clinical behavior at single-sample level. Such results represent the starting point for a complete molecular characterization of CC, including integration of genomics data to develop in clinical practice., (© 2023 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.)
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- 2023
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99. Prediction model for drug response of acute myeloid leukemia patients.
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Trac QT, Pawitan Y, Mou T, Erkers T, Östling P, Bohlin A, Österroos A, Vesterlund M, Jafari R, Siavelis I, Bäckvall H, Kiviluoto S, Orre LM, Rantalainen M, Lehtiö J, Lehmann S, Kallioniemi O, and Vu TN
- Abstract
Despite some encouraging successes, predicting the therapy response of acute myeloid leukemia (AML) patients remains highly challenging due to tumor heterogeneity. Here we aim to develop and validate MDREAM, a robust ensemble-based prediction model for drug response in AML based on an integration of omics data, including mutations and gene expression, and large-scale drug testing. Briefly, MDREAM is first trained in the BeatAML cohort (n = 278), and then validated in the BeatAML (n = 183) and two external cohorts, including a Swedish AML cohort (n = 45) and a relapsed/refractory acute leukemia cohort (n = 12). The final prediction is based on 122 ensemble models, each corresponding to a drug. A confidence score metric is used to convey the uncertainty of predictions; among predictions with a confidence score >0.75, the validated proportion of good responders is 77%. The Spearman correlations between the predicted and the observed drug response are 0.68 (95% CI: [0.64, 0.68]) in the BeatAML validation set, -0.49 (95% CI: [-0.53, -0.44]) in the Swedish cohort and 0.59 (95% CI: [0.51, 0.67]) in the relapsed/refractory cohort. A web-based implementation of MDREAM is publicly available at https://www.meb.ki.se/shiny/truvu/MDREAM/ ., (© 2023. The Author(s).)
- Published
- 2023
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100. Hidden Genetic Regulation of Human Complex Traits via Brain Isoforms.
- Author
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Pan L, Zheng C, Yang Z, Pawitan Y, Vu TN, and Shen X
- Abstract
Alternative splicing exists in most multi-exonic genes, and exploring these complex alternative splicing events and their resultant isoform expressions is essential. However, it has become conventional that RNA sequencing results have often been summarized into gene-level expression counts mainly due to the multiple ambiguous mapping of reads at highly similar regions. Transcript-level quantification and interpretation are often overlooked, and biological interpretations are often deduced based on combined transcript information at the gene level. Here, for the most variable tissue of alternative splicing, the brain, we estimate isoform expressions in 1,191 samples collected by the Genotype-Tissue Expression (GTEx) Consortium using a powerful method that we previously developed. We perform genome-wide association scans on the isoform ratios per gene and identify isoform-ratio quantitative trait loci (irQTL), which could not be detected by studying gene-level expressions alone. By analyzing the genetic architecture of the irQTL, we show that isoform ratios regulate educational attainment via multiple tissues including the frontal cortex (BA9), cortex, cervical spinal cord, and hippocampus. These tissues are also associated with different neuro-related traits, including Alzheimer's or dementia, mood swings, sleep duration, alcohol intake, intelligence, anxiety or depression, etc. Mendelian randomization (MR) analysis revealed 1,139 pairs of isoforms and neuro-related traits with plausible causal relationships, showing much stronger causal effects than on general diseases measured in the UK Biobank (UKB). Our results highlight essential transcript-level biomarkers in the human brain for neuro-related complex traits and diseases, which could be missed by merely investigating overall gene expressions., Supplementary Information: The online version contains supplementary material available at 10.1007/s43657-023-00100-6., Competing Interests: Conflict of interestsThe authors declare no competing financial interest., (© The Author(s) 2023.)
- Published
- 2023
- Full Text
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