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2. Effectiveness of a stigma awareness intervention on reemployment of people with mental health issues/mental illness: A cluster randomised controlled trial

Author

Janssens, K., Joosen, M., Henderson, C., Bakker, M., den Hollander, W., van Weeghel, J., Brouwers, E., Janssens, K., Joosen, M., Henderson, C., Bakker, M., den Hollander, W., van Weeghel, J., and Brouwers, E.

Abstract

Purpose A barrier for reemployment of people with mental health issues/mental illness (MHI) is workplace stigma and discrimination. In this RCT the effectiveness of a stigma-awareness intervention addressing finding work, retaining work and decisional stress were evaluated. Methods A cluster RCT was conducted in 8 Dutch municipal practices. Randomisation took place at practice level. Participants were unemployed people with MHI, receiving social benefits. The intervention consisted of a decision aid for workplace disclosure for participants and a 2 × 3 h stigma-awareness training for their employment specialists. Primary outcomes were measured at baseline, 3-, 6- and 12-months. Multilevel analyses, containing random intercepts of participants nested in organizations, were conducted to analyse the effects of the intervention. Results Participants (N = 153) were randomized to an experimental (n = 76) or control group (n = 77). At six months, significantly more participants of the experimental group (51%) had found work compared to the control group (26%). At twelve months, significantly more participants of the experimental group (49%) had retained work compared to the control group (23%). Intention-to-treat analyses showed that randomization to the experimental group was associated with finding (OR(95%CI) = 7.78(1.33–45.53), p = 0.02) and retaining (OR(95%CI) = 12.15(2.81–52.63), p < 0.01) work more often at twelve months. Analyses showed that the experimental and control group did not differ in decisional stress. Conclusions Our stigma awareness intervention was effective for finding and retaining work. As the percentage of people who found and retained work almost doubled, this suggests that on a societal level, a vast number of unemployed people could be reemployed with a relatively simple intervention. Trial Registration The study was retrospectively registered at the Dutch Trial Register (TRN: NL7798, da

Published
2024

6. What do we not know (yet) about recovery colleges?: A study protocol on their (cost-)effectiveness, mechanisms of action, fidelity and positioning

Author

van Wezel, M.M.C., Muusse, C., van de Mheen, D., Den Hollander, W., Kroon, H., van Wezel, M.M.C., Muusse, C., van de Mheen, D., Den Hollander, W., and Kroon, H.

Abstract

Background Recovery Colleges (RCs) have spread across the globe as a new way of supporting people with mental vulnerabilities in their recovery journey. RCs focus on ‘learning’ rather than ‘curing’ and in that line facilitate a transition from being a passive, dependent patient/client to an active, empowered student learning to live life, despite vulnerabilities. Peer support and co-creation are central in RCs, as peers learn from each other by sharing personal experiences with mental vulnerabilities in an accessible, inspiring and stimulating atmosphere. The implementation of RCs is highly encouraged internationally, and as a result RCs and related self-help initiatives increasingly emerge. However, high-quality research on RCs is scarce and there is a call for thorough investigation of (cost-)effectiveness, mechanisms of action, cross-border fidelity and positioning of RCs. In response, this research project aims to fill these gaps. Methods This research project entails (1) a prospective quasi-experimental effectiveness study and economic evaluation, (2) a multifaceted qualitative study to elaborate on the mechanisms of action of RCs for those involved (3) a study to develop a (Dutch) Fidelity Measure of Recovery Colleges, and (4) an organisational case study to describe the positioning of RCs in relation to other mental health care services and community-based initiatives. Following the ideals of co-creation and empowerment in RCs we conduct this research project in co-creation with RC students from Enik Recovery College in Utrecht, the Netherlands. Discussion This research project will lead to one of the first longitudinal controlled quantitative evaluations of both cost-effectiveness and effectiveness of RC attendance in a broad sense (beyond attending courses alone). Moreover, we will gather data on a micro level (i.e., impact on RC students), meso level (i.e., organisational fidelity) and macro level (i.e., positioning in the car

Published
2023

8. The human hepatocyte TXG-MAPr: gene co-expression network modules to support mechanism-based risk assessment

Author

Callegaro, G, Kunnen, S, Trairatphisan, P, Grosdidier, S, Niemeijer, M, den Hollander, W, Guney, E, Pinero Gonzalez, J, Furlong, L, Webster, Y, Saez-Rodriguez, J, Sutherland, J, Mollon, J, Stevens, J, van de Water, B, Callegaro G., Kunnen S. J., Trairatphisan P., Grosdidier S., Niemeijer M., den Hollander W., Guney E., Pinero Gonzalez J., Furlong L., Webster Y. W., Saez-Rodriguez J., Sutherland J. J., Mollon J., Stevens J. L., van de Water B., Callegaro, G, Kunnen, S, Trairatphisan, P, Grosdidier, S, Niemeijer, M, den Hollander, W, Guney, E, Pinero Gonzalez, J, Furlong, L, Webster, Y, Saez-Rodriguez, J, Sutherland, J, Mollon, J, Stevens, J, van de Water, B, Callegaro G., Kunnen S. J., Trairatphisan P., Grosdidier S., Niemeijer M., den Hollander W., Guney E., Pinero Gonzalez J., Furlong L., Webster Y. W., Saez-Rodriguez J., Sutherland J. J., Mollon J., Stevens J. L., and van de Water B.

Abstract

Mechanism-based risk assessment is urged to advance and fully permeate into current safety assessment practices, possibly at early phases of drug safety testing. Toxicogenomics is a promising source of mechanisms-revealing data, but interpretative analysis tools specific for the testing systems (e.g. hepatocytes) are lacking. In this study, we present the TXG-MAPr webtool (available at https://txg-mapr.eu/WGCNA_PHH/TGGATEs_PHH/), an R-Shiny-based implementation of weighted gene co-expression network analysis (WGCNA) obtained from the Primary Human Hepatocytes (PHH) TG-GATEs dataset. The 398 gene co-expression networks (modules) were annotated with functional information (pathway enrichment, transcription factor) to reveal their mechanistic interpretation. Several well-known stress response pathways were captured in the modules, were perturbed by specific stressors and showed preservation in rat systems (rat primary hepatocytes and rat in vivo liver), with the exception of DNA damage and oxidative stress responses. A subset of 87 well-annotated and preserved modules was used to evaluate mechanisms of toxicity of endoplasmic reticulum (ER) stress and oxidative stress inducers, including cyclosporine A, tunicamycin and acetaminophen. In addition, module responses can be calculated from external datasets obtained with different hepatocyte cells and platforms, including targeted RNA-seq data, therefore, imputing biological responses from a limited gene set. As another application, donors’ sensitivity towards tunicamycin was investigated with the TXG-MAPr, identifying higher basal level of intrinsic immune response in donors with pre-existing liver pathology. In conclusion, we demonstrated that gene co-expression analysis coupled to an interactive visualization environment, the TXG-MAPr, is a promising approach to achieve mechanistic relevant, cross-species and cross-platform evaluation of toxicogenomic data.

Published
2021

11. The human hepatocyte TXG-MAPr: WGCNA transcriptomic modules to support mechanism-based risk assessment

Author

Emre Guney, van de Water B, Julio Saez-Rodriguez, Laura I. Furlong, Steven J. Kunnen, Mollon J, den Hollander W, Giulia Callegaro, Janet Piñero Gonzalez, Yue Webster, Panuwat Trairatphisan, James L. Stevens, Solène Grosdidier, Jeffrey J. Sutherland, and Marije Niemeijer

Subjects
Transcriptome, Human hepatocyte, Microarray, Mechanism based, Computational biology, Biology, Toxicogenomics, Risk assessment, Gene, Transcription factor
Abstract

Mechanism-based risk assessment is urged to advance and fully permeate into current safety assessment practices, possibly at early phases of drug safety testing. Toxicogenomics is a promising source of comprehensive and mechanisms-revealing data, but analysis tools to interpret mechanisms of toxicity and specific for the testing systems (e.g. hepatocytes) are lacking. In this study we present the TXG-MAPr webtool (available at https://txg-mapr.eu/WGCNA_PHH/TGGATEs_PHH/), an R-Shiny-based implementation of weighted gene co-expression networks (WGCNA) obtained from the Primary Human Hepatocytes (PHH) TG-GATEs dataset. Gene co-expression networks (modules) were annotated with functional information (pathway enrichment, transcription factor) to reveal their mechanistic interpretation. Several well-known stress response pathways were captured in the modules, are perturbed by specific stressors and show preserved in rat systems (rat primary hepatocytes and rat in vivo liver), highlighting stress responses that translate across species/testing systems. The TXG-MAPr tool was successfully applied to investigate the mechanism of toxicity of TG-GATEs compounds and using external datasets obtained from different hepatocyte cells and microarray platforms. Additionally, we suggest that module responses can be calculated from targeted RNA-seq data therefore imputing biological responses from a limited gene. By analyzing 50 different PHH donors’ responses to a common stressor, tunicamycin, we were able to suggest modules associated with donor’s traits, e.g. pre-existing disease state, therefore connected to donors’ variability. In conclusion, we demonstrated that gene co-expression analysis coupled to an interactive visualization environment, the TXG-MAPr, is a promising approach to achieve mechanistic relevant, cross-species and cross-platform evaluation of toxicogenomic data.

Published
2021

14. Serum fatty acid chain length associates with prevalent symptomatic end-stage osteoarthritis, independent of BMI

Author

Meessen, J. M.T.A., Saberi-Hosnijeh, F., Bomer, N., den Hollander, W., van der Bom, J. G., van Hilten, J. A., van Spil, W. E., So-Osman, C., Uitterlinden, A. G., Kloppenburg, M., Nelissen, R. G.H.H., van Duijn, C. M., Slagboom, P. E., van Meurs, J. B.J., Meulenbelt, I., Meessen, J. M.T.A., Saberi-Hosnijeh, F., Bomer, N., den Hollander, W., van der Bom, J. G., van Hilten, J. A., van Spil, W. E., So-Osman, C., Uitterlinden, A. G., Kloppenburg, M., Nelissen, R. G.H.H., van Duijn, C. M., Slagboom, P. E., van Meurs, J. B.J., and Meulenbelt, I.

Abstract

Higher body mass index (BMI) is associated with osteoarthritis (OA) in both weight-bearing and non-weight-bearing joints, suggesting a link between OA and poor metabolic health beyond mechanical loading. This risk may be influenced by systemic factors accompanying BMI. Fluctuations in concentrations of metabolites may mark or even contribute to development of OA. This study explores the association of metabolites with radiographic knee/hip OA prevalence and progression. A 1H-NMR-metabolomics assay was performed on plasma samples of 1564 cases for prevalent OA and 2,125 controls collected from the Rotterdam Study, CHECK, GARP/NORREF and LUMC-arthroplasty cohorts. OA prevalence and 5 to 10 year progression was assessed by means of Kellgren-Lawrence (KL) score and the OARSI-atlas. End-stage knee/hip OA (TJA) was defined as indication for arthroplasty surgery. Controls did not have OA at baseline or follow-up. Principal component analysis of 227 metabolites demonstrated 23 factors, of which 19 remained interpretable after quality-control. Associations of factor scores with OA definitions were investigated with logistic regression. Fatty acids chain length (FALen), which was included in two factors which associated with TJA, was individually associated with both overall OA as well as TJA. Increased Fatty Acid chain Length is associated with OA.

Published
2020

15. Serum fatty acid chain length associates with prevalent symptomatic end-stage osteoarthritis, independent of BMI

Author

Meessen, J.M.T.A., Saberi-Hosnijeh, F., Bomer, N. (Nils), den Hollander, W, Bom, J.G., van Hilten, J.A., Spil, W.E. (Willem) van, So-Osman, C. (Cynthia), Uitterlinden, A.G. (André), Kloppenburg, M. (Margreet), Nelissen, R.G.H.H. (Rob), Duijn, C.M., Slagboom, PE, Meurs, J.B.J. (Joyce) van, Meulenbelt, I. (Ingrid), Meessen, J.M.T.A., Saberi-Hosnijeh, F., Bomer, N. (Nils), den Hollander, W, Bom, J.G., van Hilten, J.A., Spil, W.E. (Willem) van, So-Osman, C. (Cynthia), Uitterlinden, A.G. (André), Kloppenburg, M. (Margreet), Nelissen, R.G.H.H. (Rob), Duijn, C.M., Slagboom, PE, Meurs, J.B.J. (Joyce) van, and Meulenbelt, I. (Ingrid)

Published
2020
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16. Serum fatty acid chain length associates with prevalent symptomatic end-stage osteoarthritis, independent of BMI

Author

Leerstoel Dijkerman, Experimental Psychology (onderzoeksprogramma PF), Helmholtz Institute, IRAS OH Epidemiology Chemical Agents, dIRAS RA-2, Meessen, J. M.T.A., Saberi-Hosnijeh, F., Bomer, N., den Hollander, W., van der Bom, J. G., van Hilten, J. A., van Spil, W. E., So-Osman, C., Uitterlinden, A. G., Kloppenburg, M., Nelissen, R. G.H.H., van Duijn, C. M., Slagboom, P. E., van Meurs, J. B.J., Meulenbelt, I., Leerstoel Dijkerman, Experimental Psychology (onderzoeksprogramma PF), Helmholtz Institute, IRAS OH Epidemiology Chemical Agents, dIRAS RA-2, Meessen, J. M.T.A., Saberi-Hosnijeh, F., Bomer, N., den Hollander, W., van der Bom, J. G., van Hilten, J. A., van Spil, W. E., So-Osman, C., Uitterlinden, A. G., Kloppenburg, M., Nelissen, R. G.H.H., van Duijn, C. M., Slagboom, P. E., van Meurs, J. B.J., and Meulenbelt, I.

Published
2020

17. Serum fatty acid chain length associates with prevalent symptomatic end-stage osteoarthritis, independent of BMI

Author

Meessen, JMTA, Saberi Hosnijeh, Fatemeh, Bomer, N, den Hollander, W, Bom, Josine, van Hilten, JA, van Spil, WE, So-Osman, C, Uitterlinden, André, Kloppenburg, M, Nelissen, RGHH, Duijn, Cornelia, Slagboom, PE, van Meurs, Joyce, Meulenbelt, I, Meessen, JMTA, Saberi Hosnijeh, Fatemeh, Bomer, N, den Hollander, W, Bom, Josine, van Hilten, JA, van Spil, WE, So-Osman, C, Uitterlinden, André, Kloppenburg, M, Nelissen, RGHH, Duijn, Cornelia, Slagboom, PE, van Meurs, Joyce, and Meulenbelt, I

Published
2020

18. Factors associated with the progression of gastric intestinal metaplasia: a multicenter, prospective cohort study

Author

Mommersteeg, M. C., primary, Eikenboom, E. L., primary, Nieuwenburg, S. A. V., additional, Yu, B., additional, den Hollander, W. J., additional, Holster, I. Lisanne, additional, den Hoed, Caroline M., additional, Capelle, L. G, additional, Tang, Thjon J., additional, Anten, Marie-Paule, additional, Prytz-Berset, I., additional, Witteman, E. M., additional, ter Borg, F., additional, Burger, Jordy P. W., additional, Bruno, Marco J., additional, Fuhler, G. M., additional, Peppelenbosch, Maikel P., additional, Doukas, Michael, additional, Kuipers, Ernst J., additional, and Spaander, Manon C.W., additional

Published
2021
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25. Annotating Transcriptional Effects of Genetic Variants in Disease-Relevant Tissue: Transcriptome-Wide Allelic Imbalance in Osteoarthritic Cartilage

Author

den Hollander, W, Pulyakhina, I, de Boer, C, Bomer, N, van der Breggen, R, Arindrarto, W, de Almeida, RC, Lakenberg, N, Sentner, T, Laros, JFJ, 't Hoen, PAC, Slagboom, PE (Eline), Nelissen, R, van Meurs, Joyce, Ramos, YFM, Meulenbelt, I, den Hollander, W, Pulyakhina, I, de Boer, C, Bomer, N, van der Breggen, R, Arindrarto, W, de Almeida, RC, Lakenberg, N, Sentner, T, Laros, JFJ, 't Hoen, PAC, Slagboom, PE (Eline), Nelissen, R, van Meurs, Joyce, Ramos, YFM, and Meulenbelt, I

Published
2019

28. Genome-wide analyses identify a role for SLC17A4 and AADAT in thyroid hormone regulation

Author

Teumer, A, Chaker, Layal, Groeneweg, Stefan, Li, Yi, Di Munno, Celia, Barbieri, C, Schultheiss, UT, Traglia, M, Ahluwalia, TS, Akiyama, M, Appel, EVR, Arking, DE, Arnold, A, Astrup, A, Beekman, M, Beilby, JP, Bekaert, S, Boerwinkle, E, Brown, SJ, de Buyzere, M, Campbell, PJ, Ceresini, G, Cerqueira, C, Cucca, F, Deary, IJ, Deelen, J, Eckardt, KU, Ekici, AB, Eriksson, JG, Ferrrucci, L, Fiers, T, Fiorillo, E, Ford, I, Fox, CS, Fuchsberger, C, Galesloot, TE, Gieger, C, Gogele, M, De Grandi, A, Grarup, N, Greiser, KH, Haljas, K, Hansen, T, Harris, SE, van Heemst, D, Heijer, M, Hicks, AA, den Hollander, W, Homuth, G, Hui, JN, Ikram, Arfan, Ittermann, T, Jensen, RA, Jing, J, Jukema, JW, Kajalltie, E, Kamatani, Y, Kasbohm, E, Kaufman, JM, Kiemeney, LA, Kloppenburg, M, Kronenberg, F, Kubo, M, Lahti, J, Lapauw, B, Li, S, Liewald, DCM, Lim, EM, Linneberg, A, Marina, M, Mascalzoni, D, Matsuda, K, Medenwald, D, Meisinger, C, Meulenbelt, I, Meyer, T, zu Schwabedissen, HEM, Mikolajczyk, R, Moed, M, Netea-Maier, RT, Nolte, IM, Okadah, Y, Pala, M, Pattaro, C, Pedersen, O, Petersmann, A, Porcu, E, Postmus, I, Pramstaller, PP, Psaty, BM, Ramos, YFM, Rawal, R, Redmond, P, Richards, JB, Rietzschel, ER, Rivadeneira, Fernando, Roef, G, Rotter, JI, Sala, CF, Schlessinger, D, Selvin, E, Slagboom, PE (Eline), Soranzo, N, Sorensen, TIA, Spector, TD, Starr, JM, Stott, DJ, Taes, Y, Taliun, D, Tanaka, T, Thuesen, B, Tiller, D, Toniolo, D, Uitterlinden, André, Visser, Edward, Walsh, JP, Wilson, SG, Wolffenbuttel, BHR, Yang, Q, Zheng, HF, Cappola, A, Peeters, Robin, Naitza, S, Volzke, H, Sanna, S, Kottgen, A, Visser, Theo, Medici, Marco, Teumer, A, Chaker, Layal, Groeneweg, Stefan, Li, Yi, Di Munno, Celia, Barbieri, C, Schultheiss, UT, Traglia, M, Ahluwalia, TS, Akiyama, M, Appel, EVR, Arking, DE, Arnold, A, Astrup, A, Beekman, M, Beilby, JP, Bekaert, S, Boerwinkle, E, Brown, SJ, de Buyzere, M, Campbell, PJ, Ceresini, G, Cerqueira, C, Cucca, F, Deary, IJ, Deelen, J, Eckardt, KU, Ekici, AB, Eriksson, JG, Ferrrucci, L, Fiers, T, Fiorillo, E, Ford, I, Fox, CS, Fuchsberger, C, Galesloot, TE, Gieger, C, Gogele, M, De Grandi, A, Grarup, N, Greiser, KH, Haljas, K, Hansen, T, Harris, SE, van Heemst, D, Heijer, M, Hicks, AA, den Hollander, W, Homuth, G, Hui, JN, Ikram, Arfan, Ittermann, T, Jensen, RA, Jing, J, Jukema, JW, Kajalltie, E, Kamatani, Y, Kasbohm, E, Kaufman, JM, Kiemeney, LA, Kloppenburg, M, Kronenberg, F, Kubo, M, Lahti, J, Lapauw, B, Li, S, Liewald, DCM, Lim, EM, Linneberg, A, Marina, M, Mascalzoni, D, Matsuda, K, Medenwald, D, Meisinger, C, Meulenbelt, I, Meyer, T, zu Schwabedissen, HEM, Mikolajczyk, R, Moed, M, Netea-Maier, RT, Nolte, IM, Okadah, Y, Pala, M, Pattaro, C, Pedersen, O, Petersmann, A, Porcu, E, Postmus, I, Pramstaller, PP, Psaty, BM, Ramos, YFM, Rawal, R, Redmond, P, Richards, JB, Rietzschel, ER, Rivadeneira, Fernando, Roef, G, Rotter, JI, Sala, CF, Schlessinger, D, Selvin, E, Slagboom, PE (Eline), Soranzo, N, Sorensen, TIA, Spector, TD, Starr, JM, Stott, DJ, Taes, Y, Taliun, D, Tanaka, T, Thuesen, B, Tiller, D, Toniolo, D, Uitterlinden, André, Visser, Edward, Walsh, JP, Wilson, SG, Wolffenbuttel, BHR, Yang, Q, Zheng, HF, Cappola, A, Peeters, Robin, Naitza, S, Volzke, H, Sanna, S, Kottgen, A, Visser, Theo, and Medici, Marco

Published
2018

30. Kinetics of Radioiodinated Heptadecanoic Acid and Metabolites in the Normal and Ischaemic Canine Heart

Author

Visser, F. C., van Eenige, M. J., Westera, G., Den Hollander, W., Roos, J. P., Visser, F. C., van Eenige, M. J., Westera, G., Den Hollander, W., and Roos, J. P.

Abstract

This study was undertaken to elucidate if the myocardial elimination rate of the radioactivity after administration of radioiodinated heptadecanoic acid was related to beta-oxidation of the fatty acid or related to washout of free radioiodide. In samples of normal and ischaemic myocardium the distribution of the radioactivity over free radioiodide, heptadecanoic acid and lipids was determined. In normal myocardium the major component was free radioiodide, only a small percentage being heptadecanoic acid. In ischaemic myocardium more radiolabelled lipids were present and less free iodide when compared with normal myocardium. The percentage heptadecanoic acid was slightly increased. It is concluded that radioiodinated heptadecanoic acid behaves like the natural analogues regarding uptake and distribution. However, washout of free radioiodide determines the elimination rate as observed during a scintigraphic study

Published
2017

31. DNA Methylation in Osteoarthritis

Author

Ingrid Meulenbelt and den Hollander W

Subjects
DNA methylation, Transcriptomics, Context (language use), Osteoarthritis, Biology, GDF5, medicine.disease, Articular cartilage, Article, Transcriptome, CpG site, Genetics, medicine, Cancer research, Data integration, Epigenetics, Allele, Genetics (clinical)
Abstract

Osteoarthritis (OA) is a prevalent disease of articular joints and primarily characterized by degradation and calcification of articular cartilage. Presently, no effective treatment other than pain relief exists and patients ultimately need to undergo replacement surgery of the affected joint. During disease progression articular chondrocytes, the single cell type present in articular cartilage, show altered transcriptional profiles and undergo phenotypic changes that resemble the terminal differentiation route apparent in growth plate chondrocytes. Hence, given its prominent function in both regulating gene expression and maintaining cellular phenotypes, DNA methylation of CpG dinucleotides is intensively studied in the context of OA. An increasing number of studies have been published that employed a targeted approach on genes known to play a role in OA pathophysiology. As of such, it has become clear that OA responsive DNA methylation changes seem to mediate disease associated aberrant gene expression. Furthermore, established OA susceptibility alleles such as GDF5 and DIO2 appear to confer OA risk via DNA methylation and respective pathophysiological expression changes. In more recent years, genome wide profiling of DNA methylation in OA affected articular cartilage has emerged as a powerful tool to address the epigenetic changes in their entirety, which has resulted in the identification of putative patient subgroups as well as generic OA associated pathways.

Published
2015

32. WS13.1 QR-010, an investigational RNA therapeutic, improves CFTR activity in cystic fibrosis subjects homozygous for the F508del mutation

Author

Rowe, S., primary, Sermet-Gaudelus, I., additional, Clancy, J.P., additional, Nichols, D., additional, Nick, J., additional, De Boeck, K., additional, Solomon, G., additional, Elborn, J.S., additional, Mall, M.A., additional, Bolognese, J., additional, Bouisset, F., additional, den Hollander, W., additional, Lamontagne, N., additional, Tomkinson, N., additional, and Henig, N., additional

Published
2017
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34. Novel Genetic Variants for Cartilage Thickness and Hip Osteoarthritis

Author

Castano Betancourt, Martha, Evans, DS, Ramos, YFM, Boer, Cindy, Metrustry, S, Liu, YF, den Hollander, W, van Rooij, J, Kraus, V B, Yau, MS, Mitchell, BD, Muir, K, Hofman, Bert, Doherty, M, Doherty, S, Zhang, WY, Kraaij, Robert, Rivadeneira, Fernando, Barrett-Connor, E, Maciewicz, RA, Arden, N, Nelissen, RGHH, Kloppenburg, M, Jordan, JM, Nevitt, MC, Slagboom, EP, Hart, DJ, Lafeber, F, Styrkarsdottir, U, Zeggini, E, Evangelou, E, Spector, TD, Uitterlinden, André, Lane, NE, Meulenbelt, I, Valdes, AM, van Meurs, Joyce, Castano Betancourt, Martha, Evans, DS, Ramos, YFM, Boer, Cindy, Metrustry, S, Liu, YF, den Hollander, W, van Rooij, J, Kraus, V B, Yau, MS, Mitchell, BD, Muir, K, Hofman, Bert, Doherty, M, Doherty, S, Zhang, WY, Kraaij, Robert, Rivadeneira, Fernando, Barrett-Connor, E, Maciewicz, RA, Arden, N, Nelissen, RGHH, Kloppenburg, M, Jordan, JM, Nevitt, MC, Slagboom, EP, Hart, DJ, Lafeber, F, Styrkarsdottir, U, Zeggini, E, Evangelou, E, Spector, TD, Uitterlinden, André, Lane, NE, Meulenbelt, I, Valdes, AM, and van Meurs, Joyce

Published
2016

36. Novel susceptability loci for osteoarthritis of the hand: Coding variants in MGP and ENPP3

Author

den Hollander, W., primary, Boer, C.G., additional, Hart, D., additional, Yau, M.S., additional, Ramos, Y.F., additional, Metrustry, S., additional, Broer, L., additional, Deelen, J., additional, Beekman, M., additional, Cupples, L.A., additional, Rivadeneira, F., additional, Kloppenburg, M., additional, Peters, M., additional, Spector, T.D., additional, Hofman, A., additional, Slagboom, P.E., additional, Nelissen, R.G., additional, Uitterlinden, A.G., additional, Felson, D.T., additional, Valdes, A., additional, Meulenbelt, I., additional, and van Meurs, J.J., additional

Published
2016
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38. The transcriptional landscape of age in human peripheral blood

Author

Peters, MJ, Joehanes, R, Pilling, LC, Schurmann, C, Conneely, KN, Powell, J, Reinmaa, E, Sutphin, GL, Zhernakova, A, Schramm, K, Wilson, YA, Kobes, S, Tukiainen, T, Ramos, YF, Göring, HHH, Fornage, M, Liu, Y, Gharib, SA, Stranger, BE, De Jager, PL, Aviv, A, Levy, D, Murabito, JM, Munson, PJ, Huan, T, Hofman, A, Uitterlinden, AG, Rivadeneira, F, Van Rooij, J, Stolk, L, Broer, L, Verbiest, MMPJ, Jhamai, M, Arp, P, Metspalu, A, Tserel, L, Milani, L, Samani, NJ, Peterson, P, Kasela, S, Codd, V, Peters, A, Ward-Caviness, CK, Herder, C, Waldenberger, M, Roden, M, Singmann, P, Zeilinger, S, Illig, T, Homuth, G, Grabe, HJ, Völzke, H, Steil, L, Kocher, T, Murray, A, Melzer, D, Yaghootkar, H, Bandinelli, S, Moses, EK, Kent, JW, Curran, JE, Johnson, MP, Williams-Blangero, S, Westra, HJ, McRae, AF, Smith, JA, Kardia, SLR, Hovatta, I, Perola, M, Ripatti, S, Salomaa, V, Henders, AK, Martin, NG, Smith, AK, Mehta, D, Binder, EB, Nylocks, KM, Kennedy, EM, Klengel, T, Ding, J, Suchy-Dicey, AM, Enquobahrie, DA, Brody, J, Rotter, JI, Chen, YDI, Houwing-Duistermaat, J, Kloppenburg, M, Slagboom, PE, Helmer, Q, Den Hollander, W, Bean, S, Raj, T, Bakhshi, N, Wang, QP, Oyston, LJ, Psaty, BM, Tracy, RP, Montgomery, GW, Turner, ST, Blangero, J, Peters, MJ, Joehanes, R, Pilling, LC, Schurmann, C, Conneely, KN, Powell, J, Reinmaa, E, Sutphin, GL, Zhernakova, A, Schramm, K, Wilson, YA, Kobes, S, Tukiainen, T, Ramos, YF, Göring, HHH, Fornage, M, Liu, Y, Gharib, SA, Stranger, BE, De Jager, PL, Aviv, A, Levy, D, Murabito, JM, Munson, PJ, Huan, T, Hofman, A, Uitterlinden, AG, Rivadeneira, F, Van Rooij, J, Stolk, L, Broer, L, Verbiest, MMPJ, Jhamai, M, Arp, P, Metspalu, A, Tserel, L, Milani, L, Samani, NJ, Peterson, P, Kasela, S, Codd, V, Peters, A, Ward-Caviness, CK, Herder, C, Waldenberger, M, Roden, M, Singmann, P, Zeilinger, S, Illig, T, Homuth, G, Grabe, HJ, Völzke, H, Steil, L, Kocher, T, Murray, A, Melzer, D, Yaghootkar, H, Bandinelli, S, Moses, EK, Kent, JW, Curran, JE, Johnson, MP, Williams-Blangero, S, Westra, HJ, McRae, AF, Smith, JA, Kardia, SLR, Hovatta, I, Perola, M, Ripatti, S, Salomaa, V, Henders, AK, Martin, NG, Smith, AK, Mehta, D, Binder, EB, Nylocks, KM, Kennedy, EM, Klengel, T, Ding, J, Suchy-Dicey, AM, Enquobahrie, DA, Brody, J, Rotter, JI, Chen, YDI, Houwing-Duistermaat, J, Kloppenburg, M, Slagboom, PE, Helmer, Q, Den Hollander, W, Bean, S, Raj, T, Bakhshi, N, Wang, QP, Oyston, LJ, Psaty, BM, Tracy, RP, Montgomery, GW, Turner, ST, and Blangero, J

Abstract

Disease incidences increase with age, but the molecular characteristics of ageing that lead to increased disease susceptibility remain inadequately understood. Here we perform a whole-blood gene expression meta-analysis in 14,983 individuals of European ancestry (including replication) and identify 1,497 genes that are differentially expressed with chronological age. The age-associated genes do not harbor more age-associated CpG-methylation sites than other genes, but are instead enriched for the presence of potentially functional CpG-methylation sites in enhancer and insulator regions that associate with both chronological age and gene expression levels. We further used the gene expression profiles to calculate the 'transcriptomic age' of an individual, and show that differences between transcriptomic age and chronological age are associated with biological features linked to ageing, such as blood pressure, cholesterol levels, fasting glucose, and body mass index. The transcriptomic prediction model adds biological relevance and complements existing epigenetic prediction models, and can be used by others to calculate transcriptomic age in external cohorts.

Published
2015

39. The transcriptional landscape of age in human peripheral blood

Author

Peters, Marjolein, Joehanes, R, Pilling, LC, Schurmann, C, Conneely, KN, Powell, J, Reinmaa, E, Sutphin, GL, Zhernakova, A, Schramm, K, Wilson, YA, Kobes, S, Tukiainen, T, Ramos, YF, Goring, HHH, Fornage, M, Liu, YM, Gharib, SA, Stranger, BE, De Jager, PL, Aviv, A, Levy, D, Murabito, JM, Munson, PJ, Huan, T, Hofman, Bert, Uitterlinden, André, Rivadeneira, Fernando, van Rooij, J, Stolk, Lisette, Broer, Linda, Verbiest, Michael, Jhamai, M, Arp, Pascal, Metspalu, A, Tserel, L, Milani, L, Samani, NJ, Peterson, P, Kasela, S, Codd, V, Peters, A, Ward-Caviness, CK, Herder, Cindy, Waldenberger, M, Roden, M, Singmann, P, Zeilinger, S, Illig, T, Homuth, G, Grabe, HJ, Voelzke, H, Steil, L, Kocher, T, Murray, A, Melzer, D, Yaghootkar, H, Bandinelli, S, Moses, EK, Kent, JW, Curran, JE, Johnson, MP, Williams-Blangero, S, Westra, HJ, Mcrae, AF, Smith, JA, Kardia, SLR, Hovatta, I, Perola, M, Ripatti, S, Salomaa, V, Henders, AK, Martin, NG, Smith, AK, Mehta, D, Binder, EB, Nylocks, KM, Kennedy, EM, Klengel, T, Ding, J, Suchy-Dicey, AM, Enquobahrie, DA, Brody, J, Rotter, JI, Chen, YDI, Houwing-Duistermaat, J, Kloppenburg, M, Slagboom, PE (Eline), Helmer, Q, den Hollander, W, Bean, S, Raj, T, Bakhshi, N, Wang, QP, Oyston, LJ, Psaty, BM, Tracy, RP, Montgomery, GW, Turner, ST, Blangero, J, Meulenbelt, I, Ressler, KJ, Yang, Jiaqi, Franke, L, Kettunen, J, Visscher, PM, Neely, GG, Korstanje, R, Hanson, RL, Prokisch, H, Ferrucci, L, Esko, T, Teumer, A, van Meurs, Joyce, Andrew, D, Peters, Marjolein, Joehanes, R, Pilling, LC, Schurmann, C, Conneely, KN, Powell, J, Reinmaa, E, Sutphin, GL, Zhernakova, A, Schramm, K, Wilson, YA, Kobes, S, Tukiainen, T, Ramos, YF, Goring, HHH, Fornage, M, Liu, YM, Gharib, SA, Stranger, BE, De Jager, PL, Aviv, A, Levy, D, Murabito, JM, Munson, PJ, Huan, T, Hofman, Bert, Uitterlinden, André, Rivadeneira, Fernando, van Rooij, J, Stolk, Lisette, Broer, Linda, Verbiest, Michael, Jhamai, M, Arp, Pascal, Metspalu, A, Tserel, L, Milani, L, Samani, NJ, Peterson, P, Kasela, S, Codd, V, Peters, A, Ward-Caviness, CK, Herder, Cindy, Waldenberger, M, Roden, M, Singmann, P, Zeilinger, S, Illig, T, Homuth, G, Grabe, HJ, Voelzke, H, Steil, L, Kocher, T, Murray, A, Melzer, D, Yaghootkar, H, Bandinelli, S, Moses, EK, Kent, JW, Curran, JE, Johnson, MP, Williams-Blangero, S, Westra, HJ, Mcrae, AF, Smith, JA, Kardia, SLR, Hovatta, I, Perola, M, Ripatti, S, Salomaa, V, Henders, AK, Martin, NG, Smith, AK, Mehta, D, Binder, EB, Nylocks, KM, Kennedy, EM, Klengel, T, Ding, J, Suchy-Dicey, AM, Enquobahrie, DA, Brody, J, Rotter, JI, Chen, YDI, Houwing-Duistermaat, J, Kloppenburg, M, Slagboom, PE (Eline), Helmer, Q, den Hollander, W, Bean, S, Raj, T, Bakhshi, N, Wang, QP, Oyston, LJ, Psaty, BM, Tracy, RP, Montgomery, GW, Turner, ST, Blangero, J, Meulenbelt, I, Ressler, KJ, Yang, Jiaqi, Franke, L, Kettunen, J, Visscher, PM, Neely, GG, Korstanje, R, Hanson, RL, Prokisch, H, Ferrucci, L, Esko, T, Teumer, A, van Meurs, Joyce, and Andrew, D

Abstract

Disease incidences increase with age, but the molecular characteristics of ageing that lead to increased disease susceptibility remain inadequately understood. Here we perform a whole-blood gene expression meta-analysis in 14,983 individuals of European ancestry (including replication) and identify 1,497 genes that are differentially expressed with chronological age. The age-associated genes do not harbor more age-associated CpG-methylation sites than other genes, but are instead enriched for the presence of potentially functional CpG-methylation sites in enhancer and insulator regions that associate with both chronological age and gene expression levels. We further used the gene expression profiles to calculate the 'transcriptomic age' of an individual, and show that differences between transcriptomic age and chronological age are associated with biological features linked to ageing, such as blood pressure, cholesterol levels, fasting glucose, and body mass index. The transcriptomic prediction model adds biological relevance and complements existing epigenetic prediction models, and can be used by others to calculate transcriptomic age in external cohorts.

Published
2015

40. Underlying molecular mechanisms of DIO2 susceptibility in symptomatic osteoarthritis

Author

Bomer, N, den Hollander, W, Ramos, YFM, Bos, SD (Steffan Daniel), van der Breggen, R, Lakenberg, N, Pepers, BA, van Eeden, AE, Darvishan, A, Tobi, EW, Duijnisveld, BJ, van den Akker, EB, Heijmans, BT, van Roon-Mom, WMC, Verbeek, FJ, van Osch, Gerjo, Nelissen, RGHH, Slagboom, PE (Eline), Meulenbelt, I, Bomer, N, den Hollander, W, Ramos, YFM, Bos, SD (Steffan Daniel), van der Breggen, R, Lakenberg, N, Pepers, BA, van Eeden, AE, Darvishan, A, Tobi, EW, Duijnisveld, BJ, van den Akker, EB, Heijmans, BT, van Roon-Mom, WMC, Verbeek, FJ, van Osch, Gerjo, Nelissen, RGHH, Slagboom, PE (Eline), and Meulenbelt, I

Abstract

Objectives To investigate how the genetic susceptibility gene DIO2 confers risk to osteoarthritis (OA) onset in humans and to explore whether counteracting the deleterious effect could contribute to novel therapeutic approaches. Methods Epigenetically regulated expression of DIO2 was explored by assessing methylation of positional CpG-dinucleotides and the respective DIO2 expression in OA-affected and macroscopically preserved articular cartilage from end-stage OA patients. In a human in vitro chondrogenesis model, we measured the effects when thyroid signalling during culturing was either enhanced (excess T3 or lentiviral induced DIO2 overexpression) or decreased (iopanoic acid). Results OA-related changes in methylation at a specific CpG dinucleotide upstream of DIO2 caused significant upregulation of its expression (beta=4.96; p=0.0016). This effect was enhanced and appeared driven specifically by DIO2 rs225014 risk allele carriers (beta=5.58, p=0.0006). During in vitro chondrogenesis, DIO2 overexpression resulted in a significant reduced capacity of chondrocytes to deposit extracellular matrix (ECM) components, concurrent with significant induction of ECM degrading enzymes (ADAMTS5, MMP13) and markers of mineralisation (ALPL, COL1A1). Given their concurrent and significant upregulation of expression, this process is likely mediated via HIF-2 alpha/RUNX2 signalling. In contrast, we showed that inhibiting deiodinases during in vitro chondrogenesis contributed to prolonged cartilage homeostasis as reflected by significant increased deposition of ECM components and attenuated upregulation of matrix degrading enzymes. Conclusions Our findings show how genetic variation at DIO2 could confer risk to OA and raised the possibility that counteracting thyroid signalling may be a novel therapeutic approach.

Published
2015

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