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  • 1. Almqvist, Catarina
    et al.
    Adami, Hans-Olov
    Franks, Paul W.
    Groop, Leif
    Ingelsson, Erik
    Kere, Juha
    Lissner, Lauren
    Litton, Jan-Eric
    Maeurer, Markus
    Michaelsson, Karl
    Palmgren, Juni
    Stockholm University, Faculty of Science, Department of Mathematics.
    Pershagen, Goran
    Ploner, Alexander
    Sullivan, Patrick F.
    Tybring, Gunnel
    Pedersen, Nancy L.
    LifeGene-a large prospective population-based study of global relevance2011In: European Journal of Epidemiology, ISSN 0393-2990, E-ISSN 1573-7284, Vol. 26, no 1, p. 67-77Article in journal (Refereed)
    Abstract [en]

    Studying gene-environment interactions requires that the amount and quality of the lifestyle data is comparable to what is available for the corresponding genomic data. Sweden has several crucial prerequisites for comprehensive longitudinal biomedical research, such as the personal identity number, the universally available national health care system, continuously updated population and health registries and a scientifically motivated population. LifeGene builds on these strengths to bridge the gap between basic research and clinical applications with particular attention to populations, through a unique design in a research-friendly setting. LifeGene is designed both as a prospective cohort study and an infrastructure with repeated contacts of study participants approximately every 5 years. Index persons aged 18-45 years old will be recruited and invited to include their household members (partner and any children). A comprehensive questionnaire addressing cutting-edge research questions will be administered through the web with short follow-ups annually. Biosamples and physical measurements will also be collected at baseline, and re-administered every 5 years thereafter. Event-based sampling will be a key feature of LifeGene. The household-based design will give the opportunity to involve young couples prior to and during pregnancy, allowing for the first study of children born into cohort with complete pre-and perinatal data from both the mother and father. Questions and sampling schemes will be tailored to the participants' age and life events. The target of LifeGene is to enrol 500,000 Swedes and follow them longitudinally for at least 20 years.

  • 2. Brunedal, Boel
    et al.
    Duvefelt, Kristina
    Jonasdottir, Gudrun
    Lorentzen,
    Masterman,
    Åkesson,
    Palmgren, Juni
    Stockholm University, Faculty of Science, Department of Mathematics.
    HLA-A confers an HLA-DRB1 independent influence on the risk for multiple sclerosis2007In: Plos OneArticle in journal (Refereed)
  • 3. Dahlström, Lisen Arnheim
    et al.
    Ylitalo, Nathalie
    Sundström, Karin
    Palmgren, Juni
    Stockholm University, Faculty of Science, Department of Mathematics.
    Ploner, Alexander
    Eloranta, Sandra
    Sanjeevi, Carani B.
    Andersson, Sonia
    Rohan, Thomas
    Dillner, Joakim
    Adami, Hans-Olov
    Sparen, Pär
    Prospective study of human papillomavirus and risk of cervical adenocarcinoma2010In: International Journal of Cancer, ISSN 0020-7136, E-ISSN 1097-0215, Vol. 127, no 8, p. 1923-1930Article in journal (Refereed)
    Abstract [en]

    Human papillomaviruses (HPV) are established as a major cause of cervical carcinoma. However, causality inference is dependent on prospective evidence showing that exposure predicts risk for future disease. Such evidence is available for squamous cell carcinoma, but not for cervical adenocarcinoma. We followed a population-based cohort of 994,120 women who participated in cytological screening in Sweden for a median of 6.7 years. Baseline smears from women who developed adenocarcinoma during follow-up (118 women with in situ disease and 164 with invasive disease) and their individually matched controls (1,434 smears) were analyzed for HPV using PCR. Conditional logistic regression was used to estimate odds ratios (OR) of future adenocarcinoma with 95% confidence intervals (CI). Being positive for HPV 16 in the first cytologically normal smear was associated with increased risks for both future adenocarcinoma in situ (OR: 11.0, 95% CI: 2.6-46.8) and invasive adenocarcinoma (OR: 16.0, 95% CI: 3.8-66.7), compared to being negative for HPV 16. Similarly, an HPV 18 positive smear was associated with increased risks for adenocarcinoma in situ (OR: 26.0, 95% CI: 3.5-192) and invasive adenocarcinoma (OR: 28.0, 95% CI: 3.8-206), compared to an HPV 18 negative smear. Being positive for HPV 16/18 in 2 subsequent smears was associated with an infinite risk of both in situ and invasive adenocarcinoma. In conclusion, infections with HPV 16 and 18 are detectable up to at least 14 years before diagnosis of cervical adenocarcinoma. Our data provide prospective evidence that the association of HPV 16/18 with cervical adenocarcinoma is strong and causal.

  • 4.
    Dominicus, Annica
    et al.
    Stockholm University, Faculty of Science, Department of Mathematics.
    Palmgren, Juni
    Stockholm University, Faculty of Science, Department of Mathematics.
    Pedersen, Nancy L.
    Bias in variance components due to nonresponse in twin studies2006In: Twin Research and Human Genetics, ISSN 1832-4274, E-ISSN 1839-2628, Vol. 9, no 2, p. 185-193Article in journal (Refereed)
    Abstract [en]

    Incomplete data on trait values may bias estimates of genetic and environmental variance components obtained from twin analyses. If the nonresponse mechanism is 'ignorable' then methods such as full information maximum likelihood estimation will produce consistent variance component estimates. If, however, nonresponse is 'nonignorable', then the situation is more complicated. We demonstrate that a within-pair correlation of nonresponse, possibly different for monozygotic (MZ) and dizygotic (DZ) twins, may well be compatible with 'ignorability'. By means of Monte Carlo simulation, we assess the potential bias in variance component estimates for different types of nonresponse mechanisms. The simulation results guide the interpretation of analyses of data on perceptual speed from the Swedish Adoption/Twin Study of Aging. The results suggest that the dramatic decrease in genetic influences on perceptual speed observed after 13 years of follow-up is not attributable solely to dropout from the study, and thus support the hypothesis that genetic influences on some cognitive abilities decrease with age in late life.

  • 5. Dominicus, Annica
    et al.
    Ripatti, Samuli
    Pedersen, Nancy L
    Palmgren, Juni
    Stockholm University, Faculty of Science, Department of Mathematics. Stockholm University, Faculty of Science, Department of Mathematics.
    A random change-pont model for assessing variability in repeated measures of cognitive function2008In: Statistics in Medicine, Vol. 27, p. 5786-5798Article in journal (Refereed)
  • 6.
    Dominicus, Annica
    et al.
    Stockholm University, Faculty of Science, Department of Mathematics.
    Skrondal, Anders
    Gjessing, Håkon K.
    Pedersen, Nancy L.
    Palmgren, Juni
    Stockholm University, Faculty of Science, Department of Mathematics.
    Likelihood ratio tests in behavioral genetics: Problems and solutions2006In: Behavior Genetics, ISSN 0001-8244, E-ISSN 1573-3297, Behavior Genetics, ISSN 0001-8244, Vol. 36, no 2, p. 331-340Article in journal (Refereed)
    Abstract [en]

     

     

    The likelihood ratio test of nested models for family data plays an important role in the assessment of genetic and environmental influences on the variation in traits. The test is routinely based on the assumption that the test statistic follows a chi-square distribution under the null, with the number of restricted parameters as degrees of freedom. However, tests of variance components constrained to be non-negative correspond to tests of parameters on the boundary of the parameter space. In this situation the standard test procedure provides too large

    p-values and the use of the Akaike Information Criterion (AIC) or the Bayesian Information Criterion (BIC) for model selection is problematic. Focusing on the classical ACE twin model for univariate traits, we adapt existing theory to show that the asymptotic distribution for the likelihood ratio statistic is a mixture of chi-square distributions, and we derive the mixing probabilities. We conclude that when testing the AE or the CE model against the ACE model, the p-values obtained from using the v2 (1 df) as the reference distribution should be halved. When the E model is tested against the ACE model, a mixture of v2(0 df), v2(1 df) and v2 (2 df) should be used as the reference distribution, and we provide a simple formula to compute the mixing probabilities. Similar results for tests of the AE, DE and E models against the ADE model are also derived. Failing to use the appropriate reference distribution can lead to invalid conclusions.

  • 7. Humphreys, Keith
    et al.
    Grankvist, Alexander
    Leu, Monica
    Hall, Per
    Liu, Jianjun
    Ripatti, Samuli
    Rehnstroem, Karola
    Groop, Leif
    Klareskog, Lars
    Ding, Bo
    Gronberg, Henrik
    Xu, Jianfeng
    Pedersen, Nancy L.
    Lichtenstein, Paul
    Mattingsdal, Morten
    Andreassen, Ole A.
    O'Dushlaine, Colm
    Purcell, Shaun M.
    Sklar, Pamela
    Sullivan, Patrick F.
    Hultman, Christina M.
    Palmgren, Juni
    Stockholm University, Faculty of Science, Department of Mathematics.
    Magnusson, Patrik K. E.
    The Genetic Structure of the Swedish Population2011In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 6, no 8, p. e22547-Article in journal (Refereed)
    Abstract [en]

    Patterns of genetic diversity have previously been shown to mirror geography on a global scale and within continents and individual countries. Using genome-wide SNP data on 5174 Swedes with extensive geographical coverage, we analyzed the genetic structure of the Swedish population. We observed strong differences between the far northern counties and the remaining counties. The population of Dalarna county, in north middle Sweden, which borders southern Norway, also appears to differ markedly from other counties, possibly due to this county having more individuals with remote Finnish or Norwegian ancestry than other counties. An analysis of genetic differentiation (based on pairwise F(st)) indicated that the population of Sweden's southernmost counties are genetically closer to the HapMap CEU samples of Northern European ancestry than to the populations of Sweden's northernmost counties. In a comparison of extended homozygous segments, we detected a clear divide between southern and northern Sweden with small differences between the southern counties and considerably more segments in northern Sweden. Both the increased degree of homozygosity in the north and the large genetic differences between the south and the north may have arisen due to a small population in the north and the vast geographical distances between towns and villages in the north, in contrast to the more densely settled southern parts of Sweden. Our findings have implications for future genome-wide association studies (GWAS) with respect to the matching of cases and controls and the need for within-county matching. We have shown that genetic differences within a single country may be substantial, even when viewed on a European scale. Thus, population stratification needs to be accounted for, even within a country like Sweden, which is often perceived to be relatively homogenous and a favourable resource for genetic mapping, otherwise inferences based on genetic data may lead to false conclusions.

  • 8. Jonasdottir, Gudrun
    et al.
    Becker, Tim
    Humphreys, Keith
    Palmgren, Juni
    Stockholm University, Faculty of Science, Department of Mathematics. Stockholm University, Faculty of Science, Department of Mathematics.
    Testing association in the presence of linkage using multiple markers2008In: Genetic Epidemiology, Vol. 32, p. 425-433Article in journal (Refereed)
  • 9. Leu, Monica
    et al.
    Humphreys, Keith
    Surakka, Ida
    Rehnberg, Emil
    Muilu, Juha
    Rosenstrom, Paivi
    Almgren, Peter
    Jaaskelainen, Juha
    Lifton, Richard P.
    Kyvik, Kirsten Ohm
    Kaprio, Jaakko
    Pedersen, Nancy L.
    Palotie, Aarno
    Hall, Per
    Gronberg, Henrik
    Groop, Leif
    Peltonen, Leena
    Palmgren, Juni
    Stockholm University, Faculty of Science, Department of Mathematics.
    Ripatti, Samuli
    NordicDB: a Nordic pool and portal for genome-wide control data2010In: European Journal of Human Genetics, ISSN 1018-4813, E-ISSN 1476-5438, Vol. 18, no 12, p. 1322-1326Article in journal (Refereed)
    Abstract [en]

    A cost-efficient way to increase power in a genetic association study is to pool controls from different sources. The genotyping effort can then be directed to large case series. The Nordic Control database, NordicDB, has been set up as a unique resource in the Nordic area and the data are available for authorized users through the web portal (http://www.nordicdb.org). The current version of NordicDB pools together high-density genome-wide SNP information from similar to 5000 controls originating from Finnish, Swedish and Danish studies and shows country-specific allele frequencies for SNP markers. The genetic homogeneity of the samples was investigated using multidimensional scaling (MDS) analysis and pairwise allele frequency differences between the studies. The plot of the first two MDS components showed excellent resemblance to the geographical placement of the samples, with a clear NW-SE gradient. We advise researchers to assess the impact of population structure when incorporating NordicDB controls in association studies. This harmonized Nordic database presents a unique genome-wide resource for future genetic association studies in the Nordic countries. European Journal of Human Genetics (2010) 18, 1322-1326; doi: 10.1038/ejhg.2010.112; published online 28 July 2010

  • 10. Ripatti, Samuli
    et al.
    Becker, Tim
    Bickeboeller, Heike
    Dominicus, Annica
    Fischer, Christine
    Humphreys, Keith
    Jonasdottir, Gudrun
    Moreau, Yves
    Olsson, Marita
    Ploner, Alexander
    Sheehan, Nuala
    Van Steen, Kristel
    Baur, Max
    van Duijn, Cornelia
    Palmgren, Juni
    Stockholm University, Faculty of Science, Department of Mathematics.
    GENESTAT: an information portal for design and analysis of genetic association studies2009In: European Journal of Human Genetics, ISSN 1018-4813, E-ISSN 1476-5438, Vol. 17, no 4, p. 533-536Article in journal (Refereed)
    Abstract [en]

    We present the rationale, the background and the structure for version 2.0 of the GENESTAT information portal (www.genestat.org) for statistical genetics. The fast methodological advances, coupled with a range of standalone software, makes it difficult for expert as well as non-expert users to orientate when designing and analysing their genetic studies. The ultimate ambition of GENESTAT is to guide on statistical methodology related to the broad spectrum of research in genetic epidemiology. GENESTAT 2.0 focuses on genetic association studies. Each entry provides a summary of a topic and gives links to key papers, websites and software. The flexibility of the internet is utilised for cross-referencing and for open editing. This paper gives an overview of GENESTAT and gives short introductions to the current main topics in GENESTAT, with additional entries on the website. Methods and software developers are invited to contribute to the portal, which is powered by a Wikipedia-type engine and allows easy additions and editing.

  • 11. Ripatti, Samuli
    et al.
    Becker, Tim
    Bickeböller, Heike
    Dominicus, Annica
    Fischer, Christine
    Humphreys, Keith
    Jonasdottir, Gudrun
    Moreau, Yves
    Olsson, Marita
    Ploner, Alexander
    Sheehan, Nuala
    van Steen, Kristel
    Baur, Max
    van Duijn, Cornelia
    Palmgren, Juni
    Stockholm University, Faculty of Science, Department of Mathematics. Stockholm University, Faculty of Science, Department of Mathematics.
    Genestat: An information portal for design and analysis of genetic association studies2008In: European Journal of Human GeneticsArticle in journal (Refereed)
  • 12. Sjolander, Arvid
    et al.
    Humphreys, Keith
    Vansteelandt, Stijn
    Bellocco, Rino
    Palmgren, Juni
    Stockholm University, Faculty of Science, Department of Mathematics.
    Sensitivity Analysis for Principal Stratum Direct Effects, with an Application to a Study of Physical Activity and Coronary Heart Disease2009In: Biometrics, ISSN 0006-341X, E-ISSN 1541-0420, Vol. 65, no 2, p. 514-520Article in journal (Refereed)
    Abstract [en]

    In many studies, the aim is to learn about the direct exposure effect, that is, the effect not mediated through an intermediate variable. For example, in circulation disease studies it may be of interest to assess whether a suitable level of physical activity can prevent disease, even if it fails to prevent obesity. It is well known that stratification on the intermediate may introduce a so-called posttreatment selection bias. To handle this problem, we use the framework of principal stratification (Frangakis and Rubin, 2002, Biometrics 58, 21-29) to define a causally relevant estimand-the principal stratum direct effect (PSDE). The PSDE is not identified in our setting. We propose a method of sensitivity analysis that yields a range of plausible values for the causal estimand. We compare our work to similar methods proposed in the literature for handling the related problem of ""truncation by death."".

  • 13. Sjölander, Arvid
    et al.
    Humphreys, Keith
    Palmgren, Juni
    Stockholm University, Faculty of Science, Department of Mathematics. Stockholm University, Faculty of Science, Department of Mathematics.
    On informative detection bias in screening studies2008In: Statistics in Medicine, Vol. 27, p. 2635-2650Article in journal (Refereed)
  • 14. Sjölander, Arvid
    et al.
    Humphreys, Keith
    Palmgren, Juni
    Stockholm University, Faculty of Science, Department of Mathematics.
    On informative detection bias in screening studies2008In: Statistics in MedicineArticle in journal (Refereed)
  • 15. Sjölander, Arvid
    et al.
    Humphreys, Keith
    Vansteelandt, Stijn
    Bellocco, Rino
    Palmgren, Juni
    Stockholm University, Faculty of Science, Department of Mathematics. Stockholm University, Faculty of Science, Department of Mathematics.
    Sensitivity Analysis for Principal Stratum Direct Effects: with an Application to a Study of Physical Activity and Coronary Heart Disease2008In: BiometricsArticle in journal (Refereed)
  • 16. Smedstad,
    et al.
    Brynedal,
    Jonasdottir,
    Lorentzen,
    Masterman,
    Åkesson,
    Spurkland,
    lie,
    Palmgren,
    Stockholm University, Faculty of Science, Department of Mathematics.
    The impact of HLA-A and -DRB1 alleles on age at onset, disease course and severity in Scandinativan multiple sclerosis patients.2007In: European Journal of NeurologyArticle in journal (Refereed)
  • 17.
    Wienke, Andreas
    et al.
    Stockholm University, Faculty of Science, Department of Mathematics.
    Ripatti, Samuli
    Palmgren, Juni
    Stockholm University, Faculty of Science, Department of Mathematics.
    Yashin, Anatoli
    A bivariate survival model with compound Poisson frailty2010In: Statistics in Medicine, ISSN 0277-6715, E-ISSN 1097-0258, Vol. 29, no 2, p. 275-283Article in journal (Refereed)
    Abstract [en]

    A correlated frailty model is suggested for analysis of bivariate time-to-event data. The model is an extension of the correlated power variance function (PVF) frailty model (correlated three-parameter frailty model) (J. Epidemiol. Biostat. 1999; 4:53-60). It is based on a bivariate extension of the compound Poisson frailty model in univariate survival analysis (Ann. Appl. Probab. 1992; 4:951-972). It allows for a non-susceptible fraction (of zero frailty) in the population, overcoming the common assumption in survival analysis that all individuals are susceptible to the event under study. The model contains the correlated gamma frailty model and the correlated inverse Gaussian frailty model as special cases. A maximum likelihood estimation procedure for the parameters is presented and its properties are studied in a small simulation study. This model is applied to breast cancer incidence data of Swedish twins. The proportion of women susceptible to breast cancer is estimated to be 15 per cent.

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