Hauke Thomsen

Publications

• 4.11

  Impact points

  Determinants of unfavorable presentation of primary cutaneous melanoma.

  Mahdi Fallah, Elham Kharazmi, Hauke Thomsen, Jan Sundquist, Kari Hemminki

  Journal of the American Academy of Dermatology. 07/2011; 65(1):e5-6.
• 6.70

  Impact points

  What do prostate cancer patients die of?

  Matias Riihimäki, Hauke Thomsen, Andreas Brandt, Jan Sundquist, Kari Hemminki

  The oncologist. 01/2011; 16(2):175-81.

  A recent rise in the incidence of prostate cancer and a more favorable outcome have increased the proportions of other causes of death in affected men. Extending the survival of prostate cancer patients thus requires knowledge of all causes of death. Data on the population, cancers, and causes of de... [more] A recent rise in the incidence of prostate cancer and a more favorable outcome have increased the proportions of other causes of death in affected men. Extending the survival of prostate cancer patients thus requires knowledge of all causes of death. Data on the population, cancers, and causes of death were gathered from the nationwide Swedish Family-Cancer Database. A Cox regression model, comparing prostate cancer patients with all other men, was applied. Hazard ratios (HR) were calculated both for the underlying cause and for dying with a specific cause listed among multiple causes of death. Among 686,500 observed deaths, 62,500 were prostate cancer patients. For underlying causes other than prostate cancer, the highest cause-specific HRs were found for external causes (HR, 1.24; 95% confidence interval [CI], 1.16-1.31), diseases of the pulmonary circulation (HR, 1.22; 95% CI, 1.09-1.37), and heart failure (HR, 1.18; 95% CI, 1.11-1.24). For specific multiple causes, the highest HRs were found for anemia (HR, 2.28; 95% CI, 2.14-2.42), diseases of the pulmonary circulation (HR, 1.61; 95% CI, 1.55-1.68), and urinary system disease (HR, 1.90; 95% CI, 1.84-1.96). Prostate cancer patients have a higher risk for dying from various causes other than prostate cancer, including external causes and heart failure. Mechanisms have been proposed linking these elevated risks to both cancer and treatment. More attention should be paid to comorbidities in men with prostate cancer. The present study fulfills a gap in the knowledge of death causes in prostate cancer patients.
• 2.74

  Impact points

  Influence of family size and birth order on risk of cancer: a population-based study.

  Melanie Bevier, Marianne Weires, Hauke Thomsen, Jan Sundquist, Kari Hemminki

  BMC cancer. 01/2011; 11:163.

  Family size and birth order are known to influence the risk of some cancers. However, it is still unknown whether these effects change from early to later adulthood. We used the data of the Swedish Family-Cancer Database to further analyze these effects. We selected over 5.7 million offspring with i... [more] Family size and birth order are known to influence the risk of some cancers. However, it is still unknown whether these effects change from early to later adulthood. We used the data of the Swedish Family-Cancer Database to further analyze these effects. We selected over 5.7 million offspring with identified parents but no parental cancer. We estimated the effect of birth order and family size by Poisson regression adjusted for age, sex, period, region and socioeconomic status. We divided the age at diagnosis in two groups, below and over 50 years, to identify the effect of family size and birth order for different age periods. Negative associations for increasing birth order were found for endometrial, testicular, skin, thyroid and connective tissue cancers and melanoma. In contrast, we observed positive association between birth order and lung, male and female genital cancers. Family size was associated with decreasing risk for endometrial and testicular cancers, melanoma and squamous cell carcinoma; risk was increased for leukemia and nervous system cancer. The effect of birth order decreased for lung and endometrial cancer from age at diagnosis below to over 50 years. Combined effects for birth order and family size were marginally significant for thyroid gland tumors. Especially, the relative risk for follicular thyroid gland tumors was significantly decreased for increasing birth order. Our findings suggest that the effect of birth order decreases from early to late adulthood for lung and endometrial cancer.
• 2.74

  Impact points

  Tumor location and patient characteristics of colon and rectal adenocarcinomas in relation to survival and TNM classes.

  Kari Hemminki, Irene Santi, Marianne Weires, Hauke Thomsen, Jan Sundquist, Justo Lorenzo Bermejo

  BMC cancer. 01/2010; 10:688.

  Old age at diagnosis is associated with poor survival in colorectal cancer (CRC) for unknown reasons. Recent data show that colonoscopy is efficient in preventing left-sided cancers only. We examine the association of Tumor Node Metastasis (TNM) classes with diagnostic age and patient characteristic... [more] Old age at diagnosis is associated with poor survival in colorectal cancer (CRC) for unknown reasons. Recent data show that colonoscopy is efficient in preventing left-sided cancers only. We examine the association of Tumor Node Metastasis (TNM) classes with diagnostic age and patient characteristics. The Swedish Family-Cancer Database has data on TNM classes on 6,105 CRC adenocarcinoma patients. Ordinal logistic regression analysis was performed to model tumor characteristics according to age at diagnosis, tumor localization, gender, socioeconomic status, medical region and family history. The results were compared to results from survival analysis. The only parameters systematically associated with TNM classes were age and tumor localization. Young age at diagnosis was a risk factor for aggressive CRC, according to stage, N and M with odds ratios (ORs) ranging from 1.80 to 1.93 for diagnosis before age 50 years compared to diagnosis at 80+ years. All tumor characteristics, particularly T, were worse for colon compared to rectal tumors. Right-sided tumors showed worse characteristics for all classifiers but M. The survival analysis on patients diagnosed since 2000 showed a hazard ratio of 0.55 for diagnosis before age 50 years compared to diagnosis at over 80 years and a modestly better prognosis for left-sided compared to right-sided tumors. The results showed systematically more aggressive tumors in young compared to old patients. The poorer survival of old patients in colon cancer was not related to the available tumor characteristics. However, these partially agreed with the limited colonoscopic success with right-sided tumors.
• 1.25

  Impact points

  Combined line-cross and half-sib QTL analysis of crosses between outbred lines.

  Jong-Joo Kim, Honghua Zhao, Hauke Thomsen, Max F Rothschild, Jack C M Dekkers

  Genetical research. 06/2005; 85(3):235-48.

  Data from an F 2 cross between breeds of livestock are typically analysed by least squares line-cross or half-sib models to detect quantitative trait loci (QTL) that differ between or segregate within breeds. These models can also be combined to increase power to detect QTL, while maintaining the co... [more] Data from an F 2 cross between breeds of livestock are typically analysed by least squares line-cross or half-sib models to detect quantitative trait loci (QTL) that differ between or segregate within breeds. These models can also be combined to increase power to detect QTL, while maintaining the computational efficiency of least squares. Tests between models allow QTL to be characterized into those that are fixed (LC QTL), or segregating at similar (HS QTL) or different (CB QTL) frequencies in parental breeds. To evaluate power of the combined model, data wih various differences in QTL allele frequencies (FD) between parental breeds were simulated. Use of all models increased power to detect QTL. The line-cross model was the most powerful model to detect QTL for FD>0.6. The combined and half-sib models had similar power for FD<0.4. The proportion of detected QTL declared as LC QTL decreased with FD. The opposite was observed for HS QTL. The proportion of CB QTL decreased as FD deviated from 0.5. Accuracy of map position tended to be greatest for CB QTL. Models were applied to a cross of Berkshire and Yorkshire pig breeds and revealed 160 (40) QTL at the 5% chromosome (genome)-wise level for the 39 growth, carcass composition and quality traits, of which 72, 54, and 34 were declared as LC, HS and CB QTL. Fourteen CB QTL were detected only by the combined model. Thus, the combined model can increase power to detect QTL and mapping accuracy and enable characterization of QTL that segregate within breeds.
• 4.95

  Impact points

  Investigation of obesity candidate genes on porcine fat deposition quantitative trait loci regions.

  Kwan-Suk Kim, Hauke Thomsen, John Bastiaansen, Nguyet Thu Nguyen, Jack C M Dekkers, Graham S Plastow, Max F Rothschild

  Obesity research. 01/2005; 12(12):1981-94.

  OBJECTIVES: To investigate possible obesity candidate genes in regions of porcine quantitative trait loci (QTL) for fat deposition and obesity-related phenotypes. RESEARCH METHODS AND PROCEDURES: Chromosome mapping and QTL analyses of obesity candidate genes were performed using DNA panels from a re... [more] OBJECTIVES: To investigate possible obesity candidate genes in regions of porcine quantitative trait loci (QTL) for fat deposition and obesity-related phenotypes. RESEARCH METHODS AND PROCEDURES: Chromosome mapping and QTL analyses of obesity candidate genes were performed using DNA panels from a reference pig family. Statistical association analyses of these genes were performed for fat deposition phenotypes in several other commercial pig populations. RESULTS: Eight candidate genes were mapped to QTL regions of pig chromosomes in this study. These candidate genes also served as anchor loci to determine homologous human chromosomal locations of pig fat deposition QTL. Preliminary analyses of relationships among polymorphisms of individual candidate genes and a variety of phenotypic measurements in a large number of pigs were performed. On the basis of available data, gene-gene interactions were also studied. DISCUSSION: Comparative analysis of obesity-related genes in the pig is not only important for development of marker-assisted selection on growth and fat deposition traits in the pig but also provides for an understanding of their genetic roles in the development of human obesity.
• 3.89

  Impact points

  Multiple quantitative trait loci mapping with cofactors and application of alternative variants of the false discovery rate in an enlarged granddaughter design.

  Jörn Bennewitz, Norbert Reinsch, Volker Guiard, Sebastien Fritz, Hauke Thomsen, Christian Looft, Christa Kühn, Manfred Schwerin, Christina Weimann, Georg Erhardt, Fritz Reinhardt, Reinhard Reents, Didier Boichard, Ernst Kalm

  Genetics. 10/2004; 168(2):1019-27.

  The experimental power of a granddaughter design to detect quantitative trait loci (QTL) in dairy cattle is often limited by the availability of progeny-tested sires, by the ignoring of already identified QTL in the statistical analysis, and by the application of stringent experimentwise significanc... [more] The experimental power of a granddaughter design to detect quantitative trait loci (QTL) in dairy cattle is often limited by the availability of progeny-tested sires, by the ignoring of already identified QTL in the statistical analysis, and by the application of stringent experimentwise significance levels. This study describes an experiment that addressed these points. A large granddaughter design was set up that included sires from two countries (Germany and France), resulting in almost 2000 sires. The animals were genotyped for markers on nine different chromosomes. The QTL analysis was done for six traits separately using a multimarker regression that included putative QTL on other chromosomes as cofactors in the model. Different variants of the false discovery rate (FDR) were applied. Two of them accounted for the proportion of truly null hypotheses, which were estimated to be 0.28 and 0.3, respectively, and were therefore tailored to the experiment. A total of 25 QTL could be mapped when cofactors were included in the model-7 more than without cofactors. Controlling the FDR at 0.05 revealed 31 QTL for the two FDR methods that accounted for the proportion of truly null hypotheses. The relatively high power of this study can be attributed to the size of the experiment, to the QTL analysis with cofactors, and to the application of an appropriate FDR.
• 1.40

  Impact points

  Combined analysis of data from two granddaughter designs: A simple strategy for QTL confirmation and increasing experimental power in dairy cattle.

  Jörn Bennewitz, Norbert Reinsch, Cécile Grohs, Hubert Levéziel, Alain Malafosse, Hauke Thomsen, Ningying Xu, Christian Looft, Christa Kühn, Gudrun A Brockmann, [......], Ivica Medjugorac, Ingolf Russ, Martin Förster, Bertram Brenig, Fritz Reinhardt, Reinhard Reents, Gottfried Averdunk, Jürgen Blümel, Didier Boichard, Ernst Kalm

  Genetics, selection, evolution. : GSE. 35(3):319-38.

  A joint analysis of five paternal half-sib Holstein families that were part of two different granddaughter designs (ADR- or Inra-design) was carried out for five milk production traits and somatic cell score in order to conduct a QTL confirmation study and to increase the experimental power. Data we... [more] A joint analysis of five paternal half-sib Holstein families that were part of two different granddaughter designs (ADR- or Inra-design) was carried out for five milk production traits and somatic cell score in order to conduct a QTL confirmation study and to increase the experimental power. Data were exchanged in a coded and standardised form. The combined data set (JOINT-design) consisted of on average 231 sires per grandsire. Genetic maps were calculated for 133 markers distributed over nine chromosomes. QTL analyses were performed separately for each design and each trait. The results revealed QTL for milk production on chromosome 14, for milk yield on chromosome 5, and for fat content on chromosome 19 in both the ADR- and the Inra-design (confirmed within this study). Some QTL could only be mapped in either the ADR- or in the Inra-design (not confirmed within this study). Additional QTL previously undetected in the single designs were mapped in the JOINT-design for fat yield (chromosome 19 and 26), protein yield (chromosome 26), protein content (chromosome 5), and somatic cell score (chromosome 2 and 19) with genomewide significance. This study demonstrated the potential benefits of a combined analysis of data from different granddaughter designs.

• Investigations on bovine marker maps, blood groups and QTL in the ADR granddaughter design /

  Hauke. Thomsen

  Thesis (doctoral)--Christian-Albrechts-Universität zu Kiel, 2000. Vita. Includes bibliographical references.