• ICARES: a real-time automated detection tool for clusters of infectious diseases in the Netherlands.

      Groeneveld, Geert H; Dalhuijsen, Anton; Kara-Zaïtri, Chakib; Hamilton, Bob; de Waal, Margot W; van Dissel, Jaap T; van Steenbergen, Jim E (2017)
      Clusters of infectious diseases are frequently detected late. Real-time, detailed information about an evolving cluster and possible associated conditions is essential for local policy makers, travelers planning to visit the area, and the local population. This is currently illustrated in the Zika virus outbreak.
    • ICTV Virus Taxonomy Profile: .

      Vinje, J; Vennema, H (2019-10-01)
      The family Caliciviridae includes viruses with single-stranded, positive-sense RNA genomes of 7.4-8.3 kb. The most clinically important representatives are human noroviruses, which are a leading cause of acute gastroenteritis in humans. Virions are non-enveloped with icosahedral symmetry. Members of seven genera infect mammals (Lagovirus, Norovirus, Nebovirus, Recovirus, Sapovirus, Valovirus and Vesivirus), members of two genera infect birds (Bavovirus and Nacovirus), and members of two genera infect fish (Minovirus and Salovirus). This is a summary of the International Committee on Taxonomy of Viruses (ICTV) Report on the family Caliciviridae, which is available at ictv.global/report/caliciviridae.
    • Identificatie van bofclusters op basis van moleculaire typering

      Gouma S; Veldhuijzen I; Binnendijk R van (2016-12)
    • Identification and ranking of environmental threats with ecosystem vulnerability distributions.

      Zijp, Michiel C; Huijbregts, Mark A J; Schipper, Aafke M; Mulder, Christian; Posthuma, Leo (2017-08-24)
      Responses of ecosystems to human-induced stress vary in space and time, because both stressors and ecosystem vulnerabilities vary in space and time. Presently, ecosystem impact assessments mainly take into account variation in stressors, without considering variation in ecosystem vulnerability. We developed a method to address ecosystem vulnerability variation by quantifying ecosystem vulnerability distributions (EVDs) based on monitoring data of local species compositions and environmental conditions. The method incorporates spatial variation of both abiotic and biotic variables to quantify variation in responses among species and ecosystems. We show that EVDs can be derived based on a selection of locations, existing monitoring data and a selected impact boundary, and can be used in stressor identification and ranking for a region. A case study on Ohio's freshwater ecosystems, with freshwater fish as target species group, showed that physical habitat impairment and nutrient loads ranked highest as current stressors, with species losses higher than 5% for at least 6% of the locations. EVDs complement existing approaches of stressor assessment and management, which typically account only for variability in stressors, by accounting for variation in the vulnerability of the responding ecosystems.
    • Identification of atopic dermatitis subgroups in children from 2 longitudinal birth cohorts.

      Paternoster, Lavinia; Savenije, Olga E M; Heron, Jon; Evans, David M; Vonk, Judith M; Brunekreef, Bert; Wijga, Alet H; Henderson, A John; Koppelman, Gerard H; Brown, Sara J (2018-03)
      Atopic dermatitis (AD) is a prevalent disease with variable natural history. Longitudinal birth cohort studies provide an opportunity to define subgroups on the basis of disease trajectories, which may represent different genetic and environmental pathomechanisms.
    • Identification of data-driven Dutch dietary patterns that benefit the environment and are healthy

      Biesbroek, Sander; Monique Verschuren, W. M.; van der Schouw, Yvonne T.; Sluijs, Ivonne; Boer, Jolanda M. A.; Temme, Elisabeth H. M. (2018-02-16)
    • Identification of differences in health impact modelling of salt reduction.

      Hendriksen, Marieke A H; Geleijnse, Johanna M; van Raaij, Joop M A; Cappuccio, Francesco P; Cobiac, Linda C; Scarborough, Peter; Nusselder, Wilma J; Jaccard, Abbygail; Boshuizen, Hendriek C (2017)
      We examined whether specific input data and assumptions explain outcome differences in otherwise comparable health impact assessment models. Seven population health models estimating the impact of salt reduction on morbidity and mortality in western populations were compared on four sets of key features, their underlying assumptions and input data. Next, assumptions and input data were varied one by one in a default approach (the DYNAMO-HIA model) to examine how it influences the estimated health impact. Major differences in outcome were related to the size and shape of the dose-response relation between salt and blood pressure and blood pressure and disease. Modifying the effect sizes in the salt to health association resulted in the largest change in health impact estimates (33% lower), whereas other changes had less influence. Differences in health impact assessment model structure and input data may affect the health impact estimate. Therefore, clearly defined assumptions and transparent reporting for different models is crucial. However, the estimated impact of salt reduction was substantial in all of the models used, emphasizing the need for public health actions.
    • Identification of emerging safety and sustainability issues of advanced materials: Proposal for a systematic approach

      Peijnenburg, WJGM; Oomen, A; Soeteman-Hernandez, LG; Groenewold, M; Sips, AJAM; Noorlander, CW; Kettelarij, JAB; Bleeker, EAJ (2021-06-30)
    • Identification of naturally processed mumps virus epitopes by mass spectrometry: Confirmation of multiple CD8+ T cell responses in mumps patients.

      de Wit, Jelle; Emmelot, Maarten E; Meiring, Hugo; van Gaans-van den Brink, Jacqueline A M; van Els, Cécile A C M; Kaaijk, Patricia (2019-09-27)
    • The identification of prevalent TB disease through TBI screening among high TB risk migrants in The Netherlands.

      Spruijt, Ineke; Joren, Chantal; Schimmel, Henrieke; Procee, Frouke; Alam, Yalda; van den Hof, Susan; Erkens, Connie (2022-02-24)
    • Identification of proteome markers for drug-induced liver injury in zebrafish embryos.

      Driessen, Marja; van der Plas-Duivesteijn, Suzanne; Kienhuis, Anne S; van den Brandhof, Evert-Jan; Roodbergen, Marianne; van de Water, Bob; Spaink, Herman P; Palmblad, Magnus; van der Ven, Leo T M; Pennings, Jeroen L A (2022-07-20)
    • Identification of Requirements for Computer-Supported Matching of Food Consumption Data with Food Composition Data.

      Koroušić Seljak, Barbara; Korošec, Peter; Eftimov, Tome; Ocke, Marga; van der Laan, Jan; Roe, Mark; Berry, Rachel; Crispim, Sandra Patricia; Turrini, Aida; Krems, Carolin; et al. (2018-03-30)
      This paper identifies the requirements for computer-supported food matching, in order to address not only national and European but also international current related needs and represents an integrated research contribution of the FP7 EuroDISH project. The available classification and coding systems and the specific problems of food matching are summarized and a new concept for food matching based on optimization methods and machine-based learning is proposed. To illustrate and test this concept, a study has been conducted in four European countries (i.e., Germany, The Netherlands, Italy and the UK) using different classification and coding systems. This real case study enabled us to evaluate the new food matching concept and provide further recommendations for future work. In the first stage of the study, we prepared subsets of food consumption data described and classified using different systems, that had already been manually matched with national food composition data. Once the food matching algorithm was trained using this data, testing was performed on another subset of food consumption data. Experts from different countries validated food matching between consumption and composition data by selecting best matches from the options given by the matching algorithm without seeing the result of the previously made manual match. The evaluation of study results stressed the importance of the role and quality of the food composition database as compared to the selected classification and/or coding systems and the need to continue compiling national food composition data as eating habits and national dishes still vary between countries. Although some countries managed to collect extensive sets of food consumption data, these cannot be easily matched with food composition data if either food consumption or food composition data are not properly classified and described using any classification and coding systems. The study also showed that the level of human expertise played an important role, at least in the training stage. Both sets of data require continuous development to improve their quality in dietary assessment.
    • Identification of TUB as a novel candidate gene influencing body weight in humans.

      Shiri-Sverdlov, Ronit; Custers, Anne; Vliet-Ostaptchouk, Jana V van; Gorp, Patrick J J van; Lindsey, Patrick J; Tilburg, Jonathan H O van; Zhernakova, Sasha; Feskens, Edith J M; A, Daphne L van der; Dollé, Martijn E T; et al. (2006-02-01)
      Previously, we identified a locus on 11p influencing obesity in families with type 2 diabetes. Based on mouse studies, we selected TUB as a functional candidate gene and performed association studies to determine whether this controls obesity. We analyzed the genotypes of 13 single nucleotide polymorphisms (SNPs) around TUB in 492 unrelated type 2 diabetic patients with known BMI values. One SNP (rs1528133) was found to have a significant effect on BMI (1.54 kg/m(2), P = 0.006). This association was confirmed in a population enriched for type 2 diabetes, using 750 individuals who were not selected for type 2 diabetes. Two SNPs in linkage disequilibrium with rs1528133 and mapping to the 3' end of TUB, rs2272382, and rs2272383 also affected BMI by 1.3 kg/m2 (P = 0.016 and P = 0.010, respectively). Combined analysis confirmed this association (P = 0.005 and P = 0.002, respectively). Moreover, comparing 349 obese subjects (BMI >30 kg/m(2)) from the combined cohort with 289 normal subjects (BMI <25 kg/m(2)) revealed that the protective alleles have a lower frequency in obese subjects (odds ratio 1.32 [95% CI 1.04-1.67], P = 0.022). Altogether, data from the tubby mouse as well as these data suggest that TUB could be an important factor in controlling the central regulation of body weight in humans.
    • Identifying and correcting epigenetics measurements for systematic sources of variation.

      Perrier, Flavie; Novoloaca, Alexei; Ambatipudi, Srikant; Baglietto, Laura; Ghantous, Akram; Perduca, Vittorio; Barrdahl, Myrto; Harlid, Sophia; Ong, Ken K; Cardona, Alexia; et al. (2018)
      Methylation measures quantified by microarray techniques can be affected by systematic variation due to the technical processing of samples, which may compromise the accuracy of the measurement process and contribute to bias the estimate of the association under investigation. The quantification of the contribution of the systematic source of variation is challenging in datasets characterized by hundreds of thousands of features.In this study, we introduce a method previously developed for the analysis of metabolomics data to evaluate the performance of existing normalizing techniques to correct for unwanted variation. Illumina Infinium HumanMethylation450K was used to acquire methylation levels in over 421,000 CpG sites for 902 study participants of a case-control study on breast cancer nested within the EPIC cohort. The principal component partial R-square (PC-PR2) analysis was used to identify and quantify the variability attributable to potential systematic sources of variation. Three correcting techniques, namely ComBat, surrogate variables analysis (SVA) and a linear regression model to compute residuals were applied. The impact of each correcting method on the association between smoking status and DNA methylation levels was evaluated, and results were compared with findings from a large meta-analysis.
    • Identifying and delineating the type 2 diabetes population in the Netherlands using an all-payer claims database: characteristics, healthcare utilisation and expenditures.

      Geurten, Rose J; Elissen, Arianne M J; Bilo, Henk J G; Struijs, Jeroen N; van Tilburg, Chantal; Ruwaard, Dirk (2021-12-07)
    • Identifying germ cell mutagens using OECD test guideline 488 (transgenic rodent somatic and germ cell gene mutation assays) and integration with somatic cell testing

      Marchetti, Francesco; Aardema, Marilyn J.; Beevers, Carol; van Benthem, Jan; Godschalk, Roger; Williams, Andrew; Yauk, Carole L.; Young, Robert; Douglas, George R. (2018-08)
    • Identifying STI risk groups based on behavioral and psychological characteristics among heterosexuals during the COVID-19 pandemic.

      van Wees, Daphne A; Godijk, Noortje G; den Daas, Chantal; Kretzschmar, Mirjam E E; Heijne, Janneke C M (2021-08-31)
    • Identifying the source of food-borne disease outbreaks: An application of Bayesian variable selection.

      Jacobs, Rianne; Lesaffre, Emmanuel; Teunis, Peter Fm; Höhle, Michael; van de Kassteele, Jan (2017-01-01)
      Early identification of contaminated food products is crucial in reducing health burdens of food-borne disease outbreaks. Analytic case-control studies are primarily used in this identification stage by comparing exposures in cases and controls using logistic regression. Standard epidemiological analysis practice is not formally defined and the combination of currently applied methods is subject to issues such as response misclassification, missing values, multiple testing problems and small sample estimation problems resulting in biased and possibly misleading results. In this paper, we develop a formal Bayesian variable selection method to account for misclassified responses and missing covariates, which are common complications in food-borne outbreak investigations. We illustrate the implementation and performance of our method on a Salmonella Thompson outbreak in the Netherlands in 2012. Our method is shown to perform better than the standard logistic regression approach with respect to earlier identification of contaminated food products. It also allows relatively easy implementation of otherwise complex methodological issues.
    • If you were a policymaker, which treatment would you disinvest? A participatory value evaluation on public preferences for active disinvestment of health care interventions in the Netherlands.

      Rotteveel, A H; Lambooij, M S; Over, E A B; Hernández, J I; Suijkerbuijk, A W M; de Blaeij, A T; de Wit, G A; Mouter, N (2022-06-07)