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53 results on '"Reinders, Marcel J T"'

1. SIRV: Spatial inference of RNA velocity at the single-cell resolution

Author: TN groep Pasterkamp, Brain, Translational Neuroscience, Regenerative Medicine and Stem Cells, Abdelaal, Tamim, Grossouw, Laurens M, Pasterkamp, R Jeroen, Lelieveldt, Boudewijn P F, Reinders, Marcel J T, Mahfouz, Ahmed, TN groep Pasterkamp, Brain, Translational Neuroscience, Regenerative Medicine and Stem Cells, Abdelaal, Tamim, Grossouw, Laurens M, Pasterkamp, R Jeroen, Lelieveldt, Boudewijn P F, Reinders, Marcel J T, and Mahfouz, Ahmed
Published: 2024

2. PATE: Proximity-Aware Time series anomaly Evaluation

Author: Ghorbani, Ramin, Reinders, Marcel J. T., Tax, David M. J., Ghorbani, Ramin, Reinders, Marcel J. T., and Tax, David M. J.
Abstract: Evaluating anomaly detection algorithms in time series data is critical as inaccuracies can lead to flawed decision-making in various domains where real-time analytics and data-driven strategies are essential. Traditional performance metrics assume iid data and fail to capture the complex temporal dynamics and specific characteristics of time series anomalies, such as early and delayed detections. We introduce Proximity-Aware Time series anomaly Evaluation (PATE), a novel evaluation metric that incorporates the temporal relationship between prediction and anomaly intervals. PATE uses proximity-based weighting considering buffer zones around anomaly intervals, enabling a more detailed and informed assessment of a detection. Using these weights, PATE computes a weighted version of the area under the Precision and Recall curve. Our experiments with synthetic and real-world datasets show the superiority of PATE in providing more sensible and accurate evaluations than other evaluation metrics. We also tested several state-of-the-art anomaly detectors across various benchmark datasets using the PATE evaluation scheme. The results show that a common metric like Point-Adjusted F1 Score fails to characterize the detection performances well, and that PATE is able to provide a more fair model comparison. By introducing PATE, we redefine the understanding of model efficacy that steers future studies toward developing more effective and accurate detection models., Comment: Accepted by ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2024), Research Track. (Preprint version)
Published: 2024

3. RESTAD: REconstruction and Similarity based Transformer for time series Anomaly Detection

Author: Ghorbani, Ramin, Reinders, Marcel J. T., Tax, David M. J., Ghorbani, Ramin, Reinders, Marcel J. T., and Tax, David M. J.
Abstract: Anomaly detection in time series data is crucial across various domains. The scarcity of labeled data for such tasks has increased the attention towards unsupervised learning methods. These approaches, often relying solely on reconstruction error, typically fail to detect subtle anomalies in complex datasets. To address this, we introduce RESTAD, an adaptation of the Transformer model by incorporating a layer of Radial Basis Function (RBF) neurons within its architecture. This layer fits a non-parametric density in the latent representation, such that a high RBF output indicates similarity with predominantly normal training data. RESTAD integrates the RBF similarity scores with the reconstruction errors to increase sensitivity to anomalies. Our empirical evaluations demonstrate that RESTAD outperforms various established baselines across multiple benchmark datasets., Comment: Manuscript under review
Published: 2024

4. The correlation between neuropathology levels and cognitive performance in centenarians

Author: Zhang, Meng, Ganz, Andrea B, Rohde, Susan, Lorenz, Linda, Rozemuller, Annemieke J M, van Vliet, Kimberley, Graat, Marieke, Sikkes, Sietske A M, Reinders, Marcel J T, Scheltens, Philip, Hulsman, Marc, Hoozemans, Jeroen J M, Holstege, Henne, Zhang, Meng, Ganz, Andrea B, Rohde, Susan, Lorenz, Linda, Rozemuller, Annemieke J M, van Vliet, Kimberley, Graat, Marieke, Sikkes, Sietske A M, Reinders, Marcel J T, Scheltens, Philip, Hulsman, Marc, Hoozemans, Jeroen J M, and Holstege, Henne
Abstract: INTRODUCTION: Neuropathological substrates associated with neurodegeneration occur in brains of the oldest old. How does this affect cognitive performance?METHODS: The 100-plus Study is an ongoing longitudinal cohort study of centenarians who self-report to be cognitively healthy; post mortem brain donation is optional. In 85 centenarian brains, we explored the correlations between the levels of 11 neuropathological substrates with ante mortem performance on 12 neuropsychological tests.RESULTS: Levels of neuropathological substrates varied: we observed levels up to Thal-amyloid beta phase 5, Braak-neurofibrillary tangle (NFT) stage V, Consortium to Establish a Registry for Alzheimer's Disease (CERAD)-neuritic plaque score 3, Thal-cerebral amyloid angiopathy stage 3, Tar-DNA binding protein 43 (TDP-43) stage 3, hippocampal sclerosis stage 1, Braak-Lewy bodies stage 6, atherosclerosis stage 3, cerebral infarcts stage 1, and cerebral atrophy stage 2. Granulovacuolar degeneration occurred in all centenarians. Some high performers had the highest neuropathology scores.DISCUSSION: Only Braak-NFT stage and limbic-predominant age-related TDP-43 encephalopathy (LATE) pathology associated significantly with performance across multiple cognitive domains. Of all cognitive tests, the clock-drawing test was particularly sensitive to levels of multiple neuropathologies.
Published: 2023

5. Resilience and resistance to the accumulation of amyloid plaques and neurofibrillary tangles in centenarians: An age-continuous perspective

Author: Zhang, Meng, Ganz, Andrea B, Rohde, Susan, Rozemuller, Annemieke J M, Netherlands Brain Bank, null, Reinders, Marcel J T, Scheltens, Philip, Hulsman, Marc, Hoozemans, Jeroen J M, Holstege, Henne, Zhang, Meng, Ganz, Andrea B, Rohde, Susan, Rozemuller, Annemieke J M, Netherlands Brain Bank, null, Reinders, Marcel J T, Scheltens, Philip, Hulsman, Marc, Hoozemans, Jeroen J M, and Holstege, Henne
Abstract: INTRODUCTION: With increasing age, neuropathological substrates associated with Alzheimer's disease (AD) accumulate in brains of cognitively healthy individuals-are they resilient, or resistant to AD-associated neuropathologies?METHODS: In 85 centenarian brains, we correlated NIA (amyloid) stages, Braak (neurofibrillary tangle) stages, and CERAD (neuritic plaque) scores with cognitive performance close to death as determined by Mini-Mental State Examination (MMSE) scores. We assessed centenarian brains against 2131 brains from AD patients, non-AD demented, and non-demented individuals in an age continuum ranging from 16 to 100+ years.RESULTS: With age, brains from non-demented individuals reached the NIA and Braak stages observed in AD patients, while CERAD scores remained lower. In centenarians, NIA stages varied (22.4% were the highest stage 3), Braak stages rarely exceeded stage IV (5.9% were V), and CERAD scores rarely exceeded 2 (4.7% were 3); within these distributions, we observed no correlation with the MMSE (NIA: P = 0.60; Braak: P = 0.08; CERAD: P = 0.16).DISCUSSION: Cognitive health can be maintained despite the accumulation of high levels of AD-related neuropathological substrates.HIGHLIGHTS: Cognitively healthy elderly have AD neuropathology levels similar to AD patients. AD neuropathology loads do not correlate with cognitive performance in centenarians. Some centenarians are resilient to the highest levels of AD neuropathology.
Published: 2023

6. Epigenetic and Metabolomic Biomarkers for Biological Age: A Comparative Analysis of Mortality and Frailty Risk

Author: Cardiometabolic Health, Circulatory Health, JC onderzoeksprogramma Cardiovasculaire Epidemiologie, Kuiper, Lieke M, Polinder-Bos, Harmke A, Bizzarri, Daniele, Vojinovic, Dina, Vallerga, Costanza L, Beekman, Marian, Dollé, E T, Ghanbari, Mohsen, Voortman, Trudy, Reinders, Marcel J T, Verschuren, W M Monique, Slagboom, P Eline, van den Akker, Erik B, van Meurs, Joyce B J, Cardiometabolic Health, Circulatory Health, JC onderzoeksprogramma Cardiovasculaire Epidemiologie, Kuiper, Lieke M, Polinder-Bos, Harmke A, Bizzarri, Daniele, Vojinovic, Dina, Vallerga, Costanza L, Beekman, Marian, Dollé, E T, Ghanbari, Mohsen, Voortman, Trudy, Reinders, Marcel J T, Verschuren, W M Monique, Slagboom, P Eline, van den Akker, Erik B, and van Meurs, Joyce B J
Published: 2023

7. Personalized Anomaly Detection in PPG Data using Representation Learning and Biometric Identification

Author: Ghorbani, Ramin, Reinders, Marcel J. T., Tax, David M. J., Ghorbani, Ramin, Reinders, Marcel J. T., and Tax, David M. J.
Abstract: Photoplethysmography (PPG) signals, typically acquired from wearable devices, hold significant potential for continuous fitness-health monitoring. In particular, heart conditions that manifest in rare and subtle deviating heart patterns may be interesting. However, robust and reliable anomaly detection within these data remains a challenge due to the scarcity of labeled data and high inter-subject variability. This paper introduces a two-stage framework leveraging representation learning and personalization to improve anomaly detection performance in PPG data. The proposed framework first employs representation learning to transform the original PPG signals into a more discriminative and compact representation. We then apply three different unsupervised anomaly detection methods for movement detection and biometric identification. We validate our approach using two different datasets in both generalized and personalized scenarios. The results show that representation learning significantly improves anomaly detection performance while reducing the high inter-subject variability. Personalized models further enhance anomaly detection performance, underscoring the role of personalization in PPG-based fitness-health monitoring systems. The results from biometric identification show that it's easier to distinguish a new user from one intended authorized user than from a group of users. Overall, this study provides evidence of the effectiveness of representation learning and personalization for anomaly detection in PPG data.
Published: 2023

8. New insights into the genetic etiology of Alzheimer's disease and related dementias

Author: Bellenguez, Celine, Kucukali, Fahri, Jansen, Iris E., Kleineidam, Luca, Moreno-Grau, Sonia, Amin, Najaf, Naj, Adam C., Campos-Martin, Rafael, Grenier-Boley, Benjamin, Andrade, Victor, Holmans, Peter A., Boland, Anne, Damotte, Vincent, van der Lee, Sven J., Costa, Marcos R., Kuulasmaa, Teemu, Yang, Qiong, De Rojas, Itziar, Bis, Joshua C., Yaqub, Amber, Prokic, Ivana, Chapuis, Julien, Ahmad, Shahzad, Giedraitis, Vilmantas, Aarsland, Dag, Garcia-Gonzalez, Pablo, Abdelnour, Carla, Alarcon-Martin, Emilio, Alcolea, Daniel, Alegret, Montserrat, Alvarez, Ignacio, Alvarez, Victoria, Armstrong, Nicola J., Tsolaki, Anthoula, Antunez, Carmen, Appollonio, Ildebrando, Arcaro, Marina, Archetti, Silvana, Arias Pastor, Alfonso, Arosio, Beatrice, Athanasiu, Lavinia, Bailly, Henri, Banaj, Nerisa, Baquero, Miquel, Barral, Sandra, Beiser, Alexa, Pastor, Ana Belen, Below, Jennifer E., Benchek, Penelope, Benussi, Luisa, Berr, Claudine, Besse, Celine, Bessi, Valentina, Binetti, Giuliano, Bizarro, Alessandra, Blesa, Rafael, Boada, Merce, Boerwinkle, Eric, Borroni, Barbara, Boschi, Silvia, Bossu, Paola, Brathen, Geir, Bressler, Jan, Bresner, Catherine, Brodaty, Henry, Brookes, Keeley J., Ignacio Brusco, Luis, Buiza-Rueda, Dolores, Burger, Katharina, Burholt, Vanessa, Bush, William S., Calero, Miguel, Cantwell, Laura B., Chene, Genevieve, Chung, Jaeyoon, Cuccaro, Michael L., Cecchetti, Roberta, Cervera-Carles, Laura, Charbonnier, Camille, Chen, Hung-Hsin, Chillotti, Caterina, Ciccone, Simona, Claassen, Jurgen A. H. R., Clark, Christopher, Conti, Elisa, Corma-Gomez, Anais, Costantini, Emanuele, Custodero, Carlo, Daian, Delphine, Dalmasso, Maria Carolina, Daniele, Antonio, Dardiotis, Efthimios, Dartigues, Jean-Francois, de Deyn, Peter Paul, Lopes, Katia de Paiva, De Witte, Lot D., Debette, Stephanie, Deckert, Jurgen, del Ser, Teodoro, Denning, Nicola, Destefano, Anita, Dichgans, Martin, Diehl-Schmid, Janine, Diez-Fairen, Monica, Rossi, Paolo Dionigi, Djurovic, Srdjan, Duron, Emmanuelle, Duzel, Emrah, Dufouil, Carole, Eiriksdottir, Gudny, Engelborghs, Sebastiaan, Escott-Price, Valentina, Espinosa, Ana, Ewers, Michael, Faber, Kelley M., Fabrizio, Tagliavini, Nielsen, Sune Fallgaard, Fardo, David W., Farotti, Lucia, Fenoglio, Chiara, Fernandez-Fuertes, Marta, Ferrari, Raffaele, Ferreira, Catarina B., Ferri, Evelyn, Fin, Bertrand, Fischer, Peter, Fladby, Tormod, Fliessbach, Klaus, Fongang, Bernard, Fornage, Myriam, Fortea, Juan, Foroud, Tatiana M., Fostinelli, Silvia, Fox, Nick C., Franco-Macias, Emlio, Bullido, Maria J., Frank-Garcia, Ana, Froelich, Lutz, Fulton-Howard, Brian, Galimberti, Daniela, Maria Garcia-Alberca, Jose, Garcia-Madrona, Sebastian, Garcia-Ribas, Guillermo, Ghidoni, Roberta, Giegling, Ina, Giorgio, Giaccone, Goate, Alison M., Goldhardt, Oliver, Gomez-Fonseca, Duber, Gonzalez-Perez, Antonio, Graff, Caroline, Grande, Giulia, Green, Emma, Grimmer, Timo, Grunblatt, Edna, Grunin, Michelle, Gudnason, Vilmundur, Guetta-Baranes, Tamar, Haapasalo, Annakaisa, Hadjigeorgiou, Georgios, Haines, Jonathan L., Hamilton-Nelson, Kara L., Hampel, Harald, Hanon, Olivier, Hardy, John, Hartmann, Annette M., Hausner, Lucrezia, Harwood, Janet, Heilmann-Heimbach, Stefanie, Helisalmi, Seppo, Heneka, Michael T., Hernandez, Isabel, Herrmann, Martin J., Hoffmann, Per, Holmes, Clive, Holstege, Henne, Huerto Vilas, Raquel, Hulsman, Marc, Humphrey, Jack, Biessels, Geert Jan, Jian, Xueqiu, Johansson, Charlotte, Jun, Gyungah R., Kastumata, Yuriko, Kauwe, John, Kehoe, Patrick G., Kilander, Lena, Stahlbom, Anne Kinhult, Kivipelto, Miia, Koivisto, Anne, Kornhuber, Johannes, Kosmidis, Mary H., Kukull, Walter A., Kuksa, Pavel P., Kunkle, Brian W., Kuzma, Amanda B., Lage, Carmen, Laukka, Erika J., Launer, Lenore, Lauria, Alessandra, Lee, Chien-Yueh, Lehtisalo, Jenni, Lerch, Ondrej, Lleo, Alberto, Longstreth, William, Jr., Lopez, Oscar, Lopez de Munain, Adolfo, Love, Seth, Lowemark, Malin, Luckcuck, Lauren, Lunetta, Kathryn L., Ma, Yiyi, Macias, Juan, Macleod, Catherine A., Maier, Wolfgang, Mangialasche, Francesca, Spallazzi, Marco, Marquie, Marta, Marshall, Rachel, Martin, Eden R., Martin Montes, Angel, Martinez Rodriguez, Carmen, Masullo, Carlo, Mayeux, Richard, Mead, Simon, Mecocci, Patrizia, Medina, Miguel, Meggy, Alun, Mehrabian, Shima, Mendoza, Silvia, Menendez-Gonzalez, Manuel, Mir, Pablo, Moebus, Susanne, Mol, Merel, Molina-Porcel, Laura, Montrreal, Laura, Morelli, Laura, Moreno, Fermin, Morgan, Kevin, Mosley, Thomas, Nothen, Markus M., Muchnik, Carolina, Mukherjee, Shubhabrata, Nacmias, Benedetta, Ngandu, Tiia, Nicolas, Gael, Nordestgaard, Borge G., Olaso, Robert, Orellana, Adelina, Orsini, Michela, Ortega, Gemma, Padovani, Alessandro, Paolo, Caffarra, Papenberg, Goran, Parnetti, Lucilla, Pasquier, Florence, Pastor, Pau, Peloso, Gina, Perez-Cordon, Alba, Perez-Tur, Jordi, Pericard, Pierre, Peters, Oliver, Pijnenburg, Yolande A. L., Pineda, Juan A., Pinol-Ripoll, Gerard, Pisanu, Laudia, Polak, Thomas, Popp, Julius, Posthuma, Danielle, Priller, Josef, Puerta, Raquel, Quenez, Olivier, Quintela, Ines, Thomassen, Jesper Qvist, Rabano, Alberto, Rainero, Innocenzo, Rajabli, Farid, Ramakers, Inez, Real, Luis M., Reinders, Marcel J. T., Reitz, Christiane, Reyes-Dumeyer, Dolly, Ridge, Perry, Riedel-Heller, Steffi, Riederer, Peter, Roberto, Natalia, Rodriguez-Rodriguez, Eloy, Rongve, Arvid, Rosas Allende, Irene, Rosende-Roca, Maitee, Luis Royo, Jose, Rubino, Elisa, Rujescu, Dan, Eugenia Saez, Maria, Sakka, Paraskevi, Saltvedt, Ingvild, Bernal Sanchez-Arjona, Maria, Sanchez-Garcia, Florentino, Sanchez Juan, Pascual, Sanchez-Valle, Raquel, Sando, Sigrid B., Sarnowski, Chloe, Satizabal, Claudia L., Scamosci, Michela, Scarmeas, Nikolaos, Scarpini, Elio, Scheltens, Philip, Scherbaum, Norbert, Scherer, Martin, Schmid, Matthias, Schneider, Anja, Schott, Jonathan M., Selbaek, Geir, Seripa, Davide, Serrano, Manuel, Sha, Jin, Shadrin, Alexey A., Skrobot, Olivia, Slifer, Susan, Snijders, Gijsje J. L., Soininen, Hilkka, Solfrizzi, Vincenzo, Solomon, Alina, Song, Yeunjoo, Sorbi, Sandro, Sotolongo-Grau, Oscar, Spalletta, Gianfranco, Spottke, Annika, Squassina, Alessio, Stordal, Eystein, Pablo Tartan, Juan, Tarraga, Lluis, Tesi, Niccolo, Thalamuthu, Anbupalam, Thomas, Tegos, Tosto, Giuseppe, Traykov, Latchezar, Tremolizzo, Lucio, Tybjaerg-Hansen, Anne, Uitterlinden, Andre, Ullgren, Abbe, Ulstein, Ingun, Valero, Sergi, Valladares, Otto, Van Broeckhoven, Christine, Vance, Jeffery, Vardarajan, Badri N., van der Lugt, Aad, Van Dongen, Jasper, van Rooij, Jeroen, van Swieten, John, Vandenberghe, Rik, Verhey, Frans, Vidal, Jean-Sebastien, Vogelgsang, Jonathan, Vyhnalek, Martin, Wagner, Michael, Wallon, David, Wang, Li-San, Wang, Ruiqi, Weinhold, Leonie, Wiltfang, Jens, Windle, Gill, Woods, Bob, Yannakoulia, Mary, Zare, Habil, Zhao, Yi, Zhang, Xiaoling, Zhu, Congcong, Zulaica, Miren, Farrer, Lindsay A., Psaty, Bruce M., Ghanbari, Mohsen, Raj, Towfique, Sachdev, Perminder, Mather, Karen, Jessen, Frank, Ikram, M. Arfan, de Mendonca, Alexandre, Hort, Jakub, Tsolaki, Magda, Pericak-Vance, Margaret A., Amouyel, Philippe, Williams, Julie, Frikke-Schmidt, Ruth, Clarimon, Jordi, Deleuze, Jean-Francois, Rossi, Giacomina, Seshadri, Sudha, Andreassen, Ole A., Ingelsson, Martin, Hiltunen, Mikko, Sleegers, Kristel, Schellenberg, Gerard D., van Duijn, Cornelia M., Sims, Rebecca, van der Flier, Wiesje M., Ruiz, Agustin, Ramirez, Alfredo, Lambert, Jean-Charles, Bellenguez, Celine, Kucukali, Fahri, Jansen, Iris E., Kleineidam, Luca, Moreno-Grau, Sonia, Amin, Najaf, Naj, Adam C., Campos-Martin, Rafael, Grenier-Boley, Benjamin, Andrade, Victor, Holmans, Peter A., Boland, Anne, Damotte, Vincent, van der Lee, Sven J., Costa, Marcos R., Kuulasmaa, Teemu, Yang, Qiong, De Rojas, Itziar, Bis, Joshua C., Yaqub, Amber, Prokic, Ivana, Chapuis, Julien, Ahmad, Shahzad, Giedraitis, Vilmantas, Aarsland, Dag, Garcia-Gonzalez, Pablo, Abdelnour, Carla, Alarcon-Martin, Emilio, Alcolea, Daniel, Alegret, Montserrat, Alvarez, Ignacio, Alvarez, Victoria, Armstrong, Nicola J., Tsolaki, Anthoula, Antunez, Carmen, Appollonio, Ildebrando, Arcaro, Marina, Archetti, Silvana, Arias Pastor, Alfonso, Arosio, Beatrice, Athanasiu, Lavinia, Bailly, Henri, Banaj, Nerisa, Baquero, Miquel, Barral, Sandra, Beiser, Alexa, Pastor, Ana Belen, Below, Jennifer E., Benchek, Penelope, Benussi, Luisa, Berr, Claudine, Besse, Celine, Bessi, Valentina, Binetti, Giuliano, Bizarro, Alessandra, Blesa, Rafael, Boada, Merce, Boerwinkle, Eric, Borroni, Barbara, Boschi, Silvia, Bossu, Paola, Brathen, Geir, Bressler, Jan, Bresner, Catherine, Brodaty, Henry, Brookes, Keeley J., Ignacio Brusco, Luis, Buiza-Rueda, Dolores, Burger, Katharina, Burholt, Vanessa, Bush, William S., Calero, Miguel, Cantwell, Laura B., Chene, Genevieve, Chung, Jaeyoon, Cuccaro, Michael L., Cecchetti, Roberta, Cervera-Carles, Laura, Charbonnier, Camille, Chen, Hung-Hsin, Chillotti, Caterina, Ciccone, Simona, Claassen, Jurgen A. H. R., Clark, Christopher, Conti, Elisa, Corma-Gomez, Anais, Costantini, Emanuele, Custodero, Carlo, Daian, Delphine, Dalmasso, Maria Carolina, Daniele, Antonio, Dardiotis, Efthimios, Dartigues, Jean-Francois, de Deyn, Peter Paul, Lopes, Katia de Paiva, De Witte, Lot D., Debette, Stephanie, Deckert, Jurgen, del Ser, Teodoro, Denning, Nicola, Destefano, Anita, Dichgans, Martin, Diehl-Schmid, Janine, Diez-Fairen, Monica, Rossi, Paolo Dionigi, Djurovic, Srdjan, Duron, Emmanuelle, Duzel, Emrah, Dufouil, Carole, Eiriksdottir, Gudny, Engelborghs, Sebastiaan, Escott-Price, Valentina, Espinosa, Ana, Ewers, Michael, Faber, Kelley M., Fabrizio, Tagliavini, Nielsen, Sune Fallgaard, Fardo, David W., Farotti, Lucia, Fenoglio, Chiara, Fernandez-Fuertes, Marta, Ferrari, Raffaele, Ferreira, Catarina B., Ferri, Evelyn, Fin, Bertrand, Fischer, Peter, Fladby, Tormod, Fliessbach, Klaus, Fongang, Bernard, Fornage, Myriam, Fortea, Juan, Foroud, Tatiana M., Fostinelli, Silvia, Fox, Nick C., Franco-Macias, Emlio, Bullido, Maria J., Frank-Garcia, Ana, Froelich, Lutz, Fulton-Howard, Brian, Galimberti, Daniela, Maria Garcia-Alberca, Jose, Garcia-Madrona, Sebastian, Garcia-Ribas, Guillermo, Ghidoni, Roberta, Giegling, Ina, Giorgio, Giaccone, Goate, Alison M., Goldhardt, Oliver, Gomez-Fonseca, Duber, Gonzalez-Perez, Antonio, Graff, Caroline, Grande, Giulia, Green, Emma, Grimmer, Timo, Grunblatt, Edna, Grunin, Michelle, Gudnason, Vilmundur, Guetta-Baranes, Tamar, Haapasalo, Annakaisa, Hadjigeorgiou, Georgios, Haines, Jonathan L., Hamilton-Nelson, Kara L., Hampel, Harald, Hanon, Olivier, Hardy, John, Hartmann, Annette M., Hausner, Lucrezia, Harwood, Janet, Heilmann-Heimbach, Stefanie, Helisalmi, Seppo, Heneka, Michael T., Hernandez, Isabel, Herrmann, Martin J., Hoffmann, Per, Holmes, Clive, Holstege, Henne, Huerto Vilas, Raquel, Hulsman, Marc, Humphrey, Jack, Biessels, Geert Jan, Jian, Xueqiu, Johansson, Charlotte, Jun, Gyungah R., Kastumata, Yuriko, Kauwe, John, Kehoe, Patrick G., Kilander, Lena, Stahlbom, Anne Kinhult, Kivipelto, Miia, Koivisto, Anne, Kornhuber, Johannes, Kosmidis, Mary H., Kukull, Walter A., Kuksa, Pavel P., Kunkle, Brian W., Kuzma, Amanda B., Lage, Carmen, Laukka, Erika J., Launer, Lenore, Lauria, Alessandra, Lee, Chien-Yueh, Lehtisalo, Jenni, Lerch, Ondrej, Lleo, Alberto, Longstreth, William, Jr., Lopez, Oscar, Lopez de Munain, Adolfo, Love, Seth, Lowemark, Malin, Luckcuck, Lauren, Lunetta, Kathryn L., Ma, Yiyi, Macias, Juan, Macleod, Catherine A., Maier, Wolfgang, Mangialasche, Francesca, Spallazzi, Marco, Marquie, Marta, Marshall, Rachel, Martin, Eden R., Martin Montes, Angel, Martinez Rodriguez, Carmen, Masullo, Carlo, Mayeux, Richard, Mead, Simon, Mecocci, Patrizia, Medina, Miguel, Meggy, Alun, Mehrabian, Shima, Mendoza, Silvia, Menendez-Gonzalez, Manuel, Mir, Pablo, Moebus, Susanne, Mol, Merel, Molina-Porcel, Laura, Montrreal, Laura, Morelli, Laura, Moreno, Fermin, Morgan, Kevin, Mosley, Thomas, Nothen, Markus M., Muchnik, Carolina, Mukherjee, Shubhabrata, Nacmias, Benedetta, Ngandu, Tiia, Nicolas, Gael, Nordestgaard, Borge G., Olaso, Robert, Orellana, Adelina, Orsini, Michela, Ortega, Gemma, Padovani, Alessandro, Paolo, Caffarra, Papenberg, Goran, Parnetti, Lucilla, Pasquier, Florence, Pastor, Pau, Peloso, Gina, Perez-Cordon, Alba, Perez-Tur, Jordi, Pericard, Pierre, Peters, Oliver, Pijnenburg, Yolande A. L., Pineda, Juan A., Pinol-Ripoll, Gerard, Pisanu, Laudia, Polak, Thomas, Popp, Julius, Posthuma, Danielle, Priller, Josef, Puerta, Raquel, Quenez, Olivier, Quintela, Ines, Thomassen, Jesper Qvist, Rabano, Alberto, Rainero, Innocenzo, Rajabli, Farid, Ramakers, Inez, Real, Luis M., Reinders, Marcel J. T., Reitz, Christiane, Reyes-Dumeyer, Dolly, Ridge, Perry, Riedel-Heller, Steffi, Riederer, Peter, Roberto, Natalia, Rodriguez-Rodriguez, Eloy, Rongve, Arvid, Rosas Allende, Irene, Rosende-Roca, Maitee, Luis Royo, Jose, Rubino, Elisa, Rujescu, Dan, Eugenia Saez, Maria, Sakka, Paraskevi, Saltvedt, Ingvild, Bernal Sanchez-Arjona, Maria, Sanchez-Garcia, Florentino, Sanchez Juan, Pascual, Sanchez-Valle, Raquel, Sando, Sigrid B., Sarnowski, Chloe, Satizabal, Claudia L., Scamosci, Michela, Scarmeas, Nikolaos, Scarpini, Elio, Scheltens, Philip, Scherbaum, Norbert, Scherer, Martin, Schmid, Matthias, Schneider, Anja, Schott, Jonathan M., Selbaek, Geir, Seripa, Davide, Serrano, Manuel, Sha, Jin, Shadrin, Alexey A., Skrobot, Olivia, Slifer, Susan, Snijders, Gijsje J. L., Soininen, Hilkka, Solfrizzi, Vincenzo, Solomon, Alina, Song, Yeunjoo, Sorbi, Sandro, Sotolongo-Grau, Oscar, Spalletta, Gianfranco, Spottke, Annika, Squassina, Alessio, Stordal, Eystein, Pablo Tartan, Juan, Tarraga, Lluis, Tesi, Niccolo, Thalamuthu, Anbupalam, Thomas, Tegos, Tosto, Giuseppe, Traykov, Latchezar, Tremolizzo, Lucio, Tybjaerg-Hansen, Anne, Uitterlinden, Andre, Ullgren, Abbe, Ulstein, Ingun, Valero, Sergi, Valladares, Otto, Van Broeckhoven, Christine, Vance, Jeffery, Vardarajan, Badri N., van der Lugt, Aad, Van Dongen, Jasper, van Rooij, Jeroen, van Swieten, John, Vandenberghe, Rik, Verhey, Frans, Vidal, Jean-Sebastien, Vogelgsang, Jonathan, Vyhnalek, Martin, Wagner, Michael, Wallon, David, Wang, Li-San, Wang, Ruiqi, Weinhold, Leonie, Wiltfang, Jens, Windle, Gill, Woods, Bob, Yannakoulia, Mary, Zare, Habil, Zhao, Yi, Zhang, Xiaoling, Zhu, Congcong, Zulaica, Miren, Farrer, Lindsay A., Psaty, Bruce M., Ghanbari, Mohsen, Raj, Towfique, Sachdev, Perminder, Mather, Karen, Jessen, Frank, Ikram, M. Arfan, de Mendonca, Alexandre, Hort, Jakub, Tsolaki, Magda, Pericak-Vance, Margaret A., Amouyel, Philippe, Williams, Julie, Frikke-Schmidt, Ruth, Clarimon, Jordi, Deleuze, Jean-Francois, Rossi, Giacomina, Seshadri, Sudha, Andreassen, Ole A., Ingelsson, Martin, Hiltunen, Mikko, Sleegers, Kristel, Schellenberg, Gerard D., van Duijn, Cornelia M., Sims, Rebecca, van der Flier, Wiesje M., Ruiz, Agustin, Ramirez, Alfredo, and Lambert, Jean-Charles
Abstract: Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE epsilon 4 allele. Meta-analysis of genome-wide association studies on Alzheimer's disease and related dementias identifies new loci and enables generation of a new genetic risk score associated with the risk of future Alzheimer's disease and dementia.
Published: 2022

9. Self-Supervised PPG Representation Learning Shows High Inter-Subject Variability

Author: Ghorbani, Ramin, Reinders, Marcel J. T., Tax, David M. J., Ghorbani, Ramin, Reinders, Marcel J. T., and Tax, David M. J.
Abstract: With the progress of sensor technology in wearables, the collection and analysis of PPG signals are gaining more interest. Using Machine Learning, the cardiac rhythm corresponding to PPG signals can be used to predict different tasks such as activity recognition, sleep stage detection, or more general health status. However, supervised learning is often limited by the amount of available labeled data, which is typically expensive to obtain. To address this problem, we propose a Self-Supervised Learning (SSL) method with a pretext task of signal reconstruction to learn an informative generalized PPG representation. The performance of the proposed SSL framework is compared with two fully supervised baselines. The results show that in a very limited label data setting (10 samples per class or less), using SSL is beneficial, and a simple classifier trained on SSL-learned representations outperforms fully supervised deep neural networks. However, the results reveal that the SSL-learned representations are too focused on encoding the subjects. Unfortunately, there is high inter-subject variability in the SSL-learned representations, which makes working with this data more challenging when labeled data is scarce. The high inter-subject variability suggests that there is still room for improvements in learning representations. In general, the results suggest that SSL may pave the way for the broader use of machine learning models on PPG data in label-scarce regimes., Comment: The current version has been accepted to be presented at ICMLT 2023; Typo corrected in the second author's name
Published: 2022

10. Single-cell immune profiling reveals thymus-seeding populations, T cell commitment, and multilineage development in the human thymus

Author: Cordes, Martijn, Akker, Erik B. van den, Morett, Federico A., Kiełbasa, Szymon M., Vloemans, Sandra A., García-Perez, Laura, Teodosio, Cristina, Dongen, J. J. M. van, Pike-Overzet, Karin, Reinders, Marcel J. T., Staal, Frank J. T., Cordes, Martijn, Akker, Erik B. van den, Morett, Federico A., Kiełbasa, Szymon M., Vloemans, Sandra A., García-Perez, Laura, Teodosio, Cristina, Dongen, J. J. M. van, Pike-Overzet, Karin, Reinders, Marcel J. T., and Staal, Frank J. T.
Abstract: T cell development in the mouse thymus has been studied extensively, but less is known regarding T cell development in the human thymus. We used a combination of single-cell techniques and functional assays to perform deep immune profiling of human T cell development, focusing on the initial stages of prelineage commitment. We identified three thymus-seeding progenitor populations that also have counterparts in the bone marrow. In addition, we found that the human thymus physiologically supports the development of monocytes, dendritic cells, and NK cells, as well as limited development of B cells. These results are an important step toward monitoring and guiding regenerative therapies in patients after hematopoietic stem cell transplantation.
Published: 2022

11. Single-cell immune profiling reveals thymus-seeding populations, T cell commitment, and multilineage development in the human thymus

Author: Cordes, Martijn, Akker, Erik B. van den, Morett, Federico A., Kiełbasa, Szymon M., Vloemans, Sandra A., García-Perez, Laura, Teodosio, Cristina, Dongen, J. J. M. van, Pike-Overzet, Karin, Reinders, Marcel J. T., Staal, Frank J. T., Cordes, Martijn, Akker, Erik B. van den, Morett, Federico A., Kiełbasa, Szymon M., Vloemans, Sandra A., García-Perez, Laura, Teodosio, Cristina, Dongen, J. J. M. van, Pike-Overzet, Karin, Reinders, Marcel J. T., and Staal, Frank J. T.
Abstract: T cell development in the mouse thymus has been studied extensively, but less is known regarding T cell development in the human thymus. We used a combination of single-cell techniques and functional assays to perform deep immune profiling of human T cell development, focusing on the initial stages of prelineage commitment. We identified three thymus-seeding progenitor populations that also have counterparts in the bone marrow. In addition, we found that the human thymus physiologically supports the development of monocytes, dendritic cells, and NK cells, as well as limited development of B cells. These results are an important step toward monitoring and guiding regenerative therapies in patients after hematopoietic stem cell transplantation.
Published: 2022

12. Development and validation of an early warning model for hospitalized COVID-19 patients:a multi-center retrospective cohort study

Author: Smit, Jim M., Krijthe, Jesse H., Tintu, Andrei N., Endeman, Henrik, Ludikhuize, Jeroen, van Genderen, Michel E., Hassan, Shermarke, El Moussaoui, Rachida, Westerweel, Peter E., Goekoop, Robbert J., Waverijn, Geeke, Verheijen, Tim, den Hollander, Jan G., de Boer, Mark G. J., Gommers, Diederik A. M. P. J., van der Vlies, Robin, Schellings, Mark, Carels, Regina A., van Nieuwkoop, Cees, Arbous, Sesmu M., van Bommel, Jasper, Knevel, Rachel, de Rijke, Yolanda B., Reinders, Marcel J. T., Smit, Jim M., Krijthe, Jesse H., Tintu, Andrei N., Endeman, Henrik, Ludikhuize, Jeroen, van Genderen, Michel E., Hassan, Shermarke, El Moussaoui, Rachida, Westerweel, Peter E., Goekoop, Robbert J., Waverijn, Geeke, Verheijen, Tim, den Hollander, Jan G., de Boer, Mark G. J., Gommers, Diederik A. M. P. J., van der Vlies, Robin, Schellings, Mark, Carels, Regina A., van Nieuwkoop, Cees, Arbous, Sesmu M., van Bommel, Jasper, Knevel, Rachel, de Rijke, Yolanda B., and Reinders, Marcel J. T.
Abstract: Background: Timely identification of deteriorating COVID-19 patients is needed to guide changes in clinical management and admission to intensive care units (ICUs). There is significant concern that widely used Early warning scores (EWSs) underestimate illness severity in COVID-19 patients and therefore, we developed an early warning model specifically for COVID-19 patients.Methods: We retrospectively collected electronic medical record data to extract predictors and used these to fit a random forest model. To simulate the situation in which the model would have been developed after the first and implemented during the second COVID-19 `wave' in the Netherlands, we performed a temporal validation by splitting all included patients into groups admitted before and after August 1, 2020. Furthermore, we propose a method for dynamic model updating to retain model performance over time. We evaluated model discrimination and calibration, performed a decision curve analysis, and quantified the importance of predictors using SHapley Additive exPlanations values.Results: We included 3514 COVID-19 patient admissions from six Dutch hospitals between February 2020 and May 2021, and included a total of 18 predictors for model fitting. The model showed a higher discriminative performance in terms of partial area under the receiver operating characteristic curve (0.82 [0.80-0.84]) compared to the National early warning score (0.72 [0.69-0.74]) and the Modified early warning score (0.67 [0.65-0.69]), a greater net benefit over a range of clinically relevant model thresholds, and relatively good calibration (intercept = 0.03 [- 0.09 to 0.14], slope = 0.79 [0.73-0.86]).Conclusions: This study shows the potential benefit of moving from early warning models for the general inpatient population to models for specific patient groups. Further (independent) validation of the model is needed.
Published: 2022

13. Genome-wide association study of frontotemporal dementia identifies a C9ORF72 haplotype with a median of 12-G4C2 repeats that predisposes to pathological repeat expansions

Author: Neurologen, Brain, Circulatory Health, Reus, Lianne M, Jansen, Iris E, Mol, Merel O, van Ruissen, Fred, van Rooij, Jeroen, van Schoor, Natasja M, Tesi, Niccolò, Reinders, Marcel J T, Huisman, Martijn A, Holstege, Henne, Visser, Pieter Jelle, de Boer, Sterre C M, Hulsman, Marc, Ahmad, Shahzad, Amin, Najaf, Uitterlinden, Andre G, Ikram, Arfan, van Duijn, Cornelia M, Seelaar, Harro, Ramakers, Inez H G B, Verhey, Frans R J, van der Lugt, Aad, Claassen, Jurgen A H R, Jan Biessels, Geert, De Deyn, Peter Paul, Scheltens, Philip, van der Flier, Wiesje M, van Swieten, John C, Pijnenburg, Yolande A L, van der Lee, Sven J, Neurologen, Brain, Circulatory Health, Reus, Lianne M, Jansen, Iris E, Mol, Merel O, van Ruissen, Fred, van Rooij, Jeroen, van Schoor, Natasja M, Tesi, Niccolò, Reinders, Marcel J T, Huisman, Martijn A, Holstege, Henne, Visser, Pieter Jelle, de Boer, Sterre C M, Hulsman, Marc, Ahmad, Shahzad, Amin, Najaf, Uitterlinden, Andre G, Ikram, Arfan, van Duijn, Cornelia M, Seelaar, Harro, Ramakers, Inez H G B, Verhey, Frans R J, van der Lugt, Aad, Claassen, Jurgen A H R, Jan Biessels, Geert, De Deyn, Peter Paul, Scheltens, Philip, van der Flier, Wiesje M, van Swieten, John C, Pijnenburg, Yolande A L, and van der Lee, Sven J
Published: 2021

14. Metabolic Age Based on the BBMRI-NL 1 H-NMR Metabolomics Repository as Biomarker of Age-related Disease

Author: van den Akker, Erik B., van den Akker, Erik B., Trompet, Stella, Barkey Wolf, Jurriaan J. H., Beekman, Marian, Suchiman, H. Eka D., Deelen, Joris, Asselbergs, Folkert W., Boersma, Eric, Cats, Davy, Elders, Petra M., Geleijnse, J. Marianne, Ikram, M. Arfan, Kloppenburg, Margreet, Mei, Haillang, Meulenbelt, Ingrid, Mooijaart, Simon P., Nelissen, Rob G. H. H., Netea, Mihai G., Penninx, Brenda W. J. H., Slofstra, Mariska, Stehouwer, Coen D. A., Swertz, Morris A., Teunissen, Charlotte E., Terwindt, Gisela M., 't Hart, Leen M., van den Maagdenberg, Arn M. J. M., van der Harst, Pim, van der Horst, Iwan C. C., van der Kallen, Carla J. H., van Greevenbroek, Marleen M. J., van Spil, W. Erwin, Wijmenga, Cisca, Zhernakova, Alexandra, Zwinderman, Aeilko H., Sattar, Naveed, Jukema, J. Wouter, van Duijn, Cornelia M., Boomsma, Dorret I., Reinders, Marcel J. T., Slagboom, P. Eline, van den Akker, Erik B., van den Akker, Erik B., Trompet, Stella, Barkey Wolf, Jurriaan J. H., Beekman, Marian, Suchiman, H. Eka D., Deelen, Joris, Asselbergs, Folkert W., Boersma, Eric, Cats, Davy, Elders, Petra M., Geleijnse, J. Marianne, Ikram, M. Arfan, Kloppenburg, Margreet, Mei, Haillang, Meulenbelt, Ingrid, Mooijaart, Simon P., Nelissen, Rob G. H. H., Netea, Mihai G., Penninx, Brenda W. J. H., Slofstra, Mariska, Stehouwer, Coen D. A., Swertz, Morris A., Teunissen, Charlotte E., Terwindt, Gisela M., 't Hart, Leen M., van den Maagdenberg, Arn M. J. M., van der Harst, Pim, van der Horst, Iwan C. C., van der Kallen, Carla J. H., van Greevenbroek, Marleen M. J., van Spil, W. Erwin, Wijmenga, Cisca, Zhernakova, Alexandra, Zwinderman, Aeilko H., Sattar, Naveed, Jukema, J. Wouter, van Duijn, Cornelia M., Boomsma, Dorret I., Reinders, Marcel J. T., and Slagboom, P. Eline
Abstract: BACKGROUND: The blood metabolome incorporates cues from the environment and the host's genetic background, potentially offering a holistic view of an individual's health status.METHODS: We have compiled a vast resource of proton nuclear magnetic resonance metabolomics and phenotypic data encompassing over 25 000 samples derived from 26 community and hospital-based cohorts.RESULTS: Using this resource, we constructed a metabolomics-based age predictor (metaboAge) to calculate an individual's biological age. Exploration in independent cohorts demonstrates that being judged older by one's metabolome, as compared with one's chronological age, confers an increased risk on future cardiovascular disease, mortality, and functionality in older individuals. A web-based tool for calculating metaboAge (metaboage.researchlumc.nl) allows easy incorporation in other epidemiological studies. Access to data can be requested at bmri.nl/samples-images-data.CONCLUSIONS: In summary, we present a vast resource of metabolomics data and illustrate its merit by constructing a metabolomics-based score for biological age that captures aspects of current and future cardiometabolic health.
Published: 2020

15. A nonsynonymous mutation in PLCG2 reduces the risk of Alzheimer's disease, dementia with Lewy bodies and frontotemporal dementia, and increases the likelihood of longevity (vol 138, pg 237, 2019)

Author: van der Lee, Sven J., Conway, Olivia J., Jansen, Iris, Carrasquillo, Minerva M., Kleineidam, Luca, van den Akker, Erik, Hernandez, Isabel, van Eijk, Kristel R., Stringa, Najada, Chen, Jason A., Zettergren, Anna, Andlauer, Till F. M., Diez-Fairen, Monica, Simon-Sanchez, Javier, Lleo, Alberto, Zetterberg, Henrik, Nygaard, Marianne, Blauwendraat, Cornelis, Savage, Jeanne E., Mengel-From, Jonas, Moreno-Grau, Sonia, Wagner, Michael, Fortea, Juan, Keogh, Michael J., Blennow, Kaj, Skoog, Ingmar, Friese, Manuel A., Pletnikova, Olga, Zulaica, Miren, Lage, Carmen, de Rojas, Itziar, Riedel-Heller, Steffi, Illan-Gala, Ignacio, Wei, Wei, Jeune, Bernard, Orellana, Adelina, Then Bergh, Florian, Wang, Xue, Hulsman, Marc, Beker, Nina, Tesi, Niccolo, Morris, Christopher M., Indakoetxea, Begona, Collij, Lyduine E., Scherer, Martin, Morenas-Rodriguez, Estrella, Ironside, James W., van Berckel, Bart N. M., Alcolea, Daniel, Wiendl, Heinz, Strickland, Samantha L., Pastor, Pau, Rodriguez Rodriguez, Eloy, Boeve, Bradley F., Petersen, Ronald C., Ferman, Tanis J., van Gerpen, Jay A., Reinders, Marcel J. T., Uitti, Ryan J., Tarraga, Lluis, Maier, Wolfgang, Dols-Icardo, Oriol, Kawalia, Amit, Dalmasso, Maria Carolina, Boada, Merce, Zettl, Uwe K., van Schoor, Natasja M., Beekman, Marian, Allen, Mariet, Masliah, Eliezer, de Munain, Adolfo Lopez, Pantelyat, Alexander, Wszolek, Zbigniew K., Ross, Owen A., Dickson, Dennis W., Graff-Radford, Neill R., Knopman, David, Rademakers, Rosa, Lemstra, Afina W., Pijnenburg, Yolande A. L., Scheltens, Philip, Gasser, Thomas, Chinnery, Patrick F., Hemmer, Bernhard, Huisman, Martijn A., Troncoso, Juan, Moreno, Fermin., Nohr, Ellen A., Sorensen, Thorkild I. A., Heutink, Peter, Sanchez-Juan, Pascual, Posthuma, Danielle, Clarimon, Jordi, Christensen, Kaare, Ertekin-Taner, Nilufer, Scholz, Sonja W., Ramirez, Alfredo, Ruiz, Agustin, Slagboom, Eline, van der Flier, Wiesje M., Holstege, Henne, van der Lee, Sven J., Conway, Olivia J., Jansen, Iris, Carrasquillo, Minerva M., Kleineidam, Luca, van den Akker, Erik, Hernandez, Isabel, van Eijk, Kristel R., Stringa, Najada, Chen, Jason A., Zettergren, Anna, Andlauer, Till F. M., Diez-Fairen, Monica, Simon-Sanchez, Javier, Lleo, Alberto, Zetterberg, Henrik, Nygaard, Marianne, Blauwendraat, Cornelis, Savage, Jeanne E., Mengel-From, Jonas, Moreno-Grau, Sonia, Wagner, Michael, Fortea, Juan, Keogh, Michael J., Blennow, Kaj, Skoog, Ingmar, Friese, Manuel A., Pletnikova, Olga, Zulaica, Miren, Lage, Carmen, de Rojas, Itziar, Riedel-Heller, Steffi, Illan-Gala, Ignacio, Wei, Wei, Jeune, Bernard, Orellana, Adelina, Then Bergh, Florian, Wang, Xue, Hulsman, Marc, Beker, Nina, Tesi, Niccolo, Morris, Christopher M., Indakoetxea, Begona, Collij, Lyduine E., Scherer, Martin, Morenas-Rodriguez, Estrella, Ironside, James W., van Berckel, Bart N. M., Alcolea, Daniel, Wiendl, Heinz, Strickland, Samantha L., Pastor, Pau, Rodriguez Rodriguez, Eloy, Boeve, Bradley F., Petersen, Ronald C., Ferman, Tanis J., van Gerpen, Jay A., Reinders, Marcel J. T., Uitti, Ryan J., Tarraga, Lluis, Maier, Wolfgang, Dols-Icardo, Oriol, Kawalia, Amit, Dalmasso, Maria Carolina, Boada, Merce, Zettl, Uwe K., van Schoor, Natasja M., Beekman, Marian, Allen, Mariet, Masliah, Eliezer, de Munain, Adolfo Lopez, Pantelyat, Alexander, Wszolek, Zbigniew K., Ross, Owen A., Dickson, Dennis W., Graff-Radford, Neill R., Knopman, David, Rademakers, Rosa, Lemstra, Afina W., Pijnenburg, Yolande A. L., Scheltens, Philip, Gasser, Thomas, Chinnery, Patrick F., Hemmer, Bernhard, Huisman, Martijn A., Troncoso, Juan, Moreno, Fermin., Nohr, Ellen A., Sorensen, Thorkild I. A., Heutink, Peter, Sanchez-Juan, Pascual, Posthuma, Danielle, Clarimon, Jordi, Christensen, Kaare, Ertekin-Taner, Nilufer, Scholz, Sonja W., Ramirez, Alfredo, Ruiz, Agustin, Slagboom, Eline, van der Flier, Wiesje M., and Holstege, Henne
Abstract: The IPDGC (The International Parkinson Disease Genomics Consortium) and EADB (Alzheimer Disease European DNA biobank) are listed correctly as an author to the article, however, they were incorrectly listed more than once.
Published: 2020

16. A nonsynonymous mutation in PLCG2 reduces the risk of Alzheimer's disease, dementia with Lewy bodies and frontotemporal dementia, and increases the likelihood of longevity (vol 138, pg 237, 2019)

Author: van der Lee, Sven J., Conway, Olivia J., Jansen, Iris, Carrasquillo, Minerva M., Kleineidam, Luca, van den Akker, Erik, Hernandez, Isabel, van Eijk, Kristel R., Stringa, Najada, Chen, Jason A., Zettergren, Anna, Andlauer, Till F. M., Diez-Fairen, Monica, Simon-Sanchez, Javier, Lleo, Alberto, Zetterberg, Henrik, Nygaard, Marianne, Blauwendraat, Cornelis, Savage, Jeanne E., Mengel-From, Jonas, Moreno-Grau, Sonia, Wagner, Michael, Fortea, Juan, Keogh, Michael J., Blennow, Kaj, Skoog, Ingmar, Friese, Manuel A., Pletnikova, Olga, Zulaica, Miren, Lage, Carmen, de Rojas, Itziar, Riedel-Heller, Steffi, Illan-Gala, Ignacio, Wei, Wei, Jeune, Bernard, Orellana, Adelina, Then Bergh, Florian, Wang, Xue, Hulsman, Marc, Beker, Nina, Tesi, Niccolo, Morris, Christopher M., Indakoetxea, Begona, Collij, Lyduine E., Scherer, Martin, Morenas-Rodriguez, Estrella, Ironside, James W., van Berckel, Bart N. M., Alcolea, Daniel, Wiendl, Heinz, Strickland, Samantha L., Pastor, Pau, Rodriguez Rodriguez, Eloy, Boeve, Bradley F., Petersen, Ronald C., Ferman, Tanis J., van Gerpen, Jay A., Reinders, Marcel J. T., Uitti, Ryan J., Tarraga, Lluis, Maier, Wolfgang, Dols-Icardo, Oriol, Kawalia, Amit, Dalmasso, Maria Carolina, Boada, Merce, Zettl, Uwe K., van Schoor, Natasja M., Beekman, Marian, Allen, Mariet, Masliah, Eliezer, de Munain, Adolfo Lopez, Pantelyat, Alexander, Wszolek, Zbigniew K., Ross, Owen A., Dickson, Dennis W., Graff-Radford, Neill R., Knopman, David, Rademakers, Rosa, Lemstra, Afina W., Pijnenburg, Yolande A. L., Scheltens, Philip, Gasser, Thomas, Chinnery, Patrick F., Hemmer, Bernhard, Huisman, Martijn A., Troncoso, Juan, Moreno, Fermin., Nohr, Ellen A., Sorensen, Thorkild I. A., Heutink, Peter, Sanchez-Juan, Pascual, Posthuma, Danielle, Clarimon, Jordi, Christensen, Kaare, Ertekin-Taner, Nilufer, Scholz, Sonja W., Ramirez, Alfredo, Ruiz, Agustin, Slagboom, Eline, van der Flier, Wiesje M., Holstege, Henne, van der Lee, Sven J., Conway, Olivia J., Jansen, Iris, Carrasquillo, Minerva M., Kleineidam, Luca, van den Akker, Erik, Hernandez, Isabel, van Eijk, Kristel R., Stringa, Najada, Chen, Jason A., Zettergren, Anna, Andlauer, Till F. M., Diez-Fairen, Monica, Simon-Sanchez, Javier, Lleo, Alberto, Zetterberg, Henrik, Nygaard, Marianne, Blauwendraat, Cornelis, Savage, Jeanne E., Mengel-From, Jonas, Moreno-Grau, Sonia, Wagner, Michael, Fortea, Juan, Keogh, Michael J., Blennow, Kaj, Skoog, Ingmar, Friese, Manuel A., Pletnikova, Olga, Zulaica, Miren, Lage, Carmen, de Rojas, Itziar, Riedel-Heller, Steffi, Illan-Gala, Ignacio, Wei, Wei, Jeune, Bernard, Orellana, Adelina, Then Bergh, Florian, Wang, Xue, Hulsman, Marc, Beker, Nina, Tesi, Niccolo, Morris, Christopher M., Indakoetxea, Begona, Collij, Lyduine E., Scherer, Martin, Morenas-Rodriguez, Estrella, Ironside, James W., van Berckel, Bart N. M., Alcolea, Daniel, Wiendl, Heinz, Strickland, Samantha L., Pastor, Pau, Rodriguez Rodriguez, Eloy, Boeve, Bradley F., Petersen, Ronald C., Ferman, Tanis J., van Gerpen, Jay A., Reinders, Marcel J. T., Uitti, Ryan J., Tarraga, Lluis, Maier, Wolfgang, Dols-Icardo, Oriol, Kawalia, Amit, Dalmasso, Maria Carolina, Boada, Merce, Zettl, Uwe K., van Schoor, Natasja M., Beekman, Marian, Allen, Mariet, Masliah, Eliezer, de Munain, Adolfo Lopez, Pantelyat, Alexander, Wszolek, Zbigniew K., Ross, Owen A., Dickson, Dennis W., Graff-Radford, Neill R., Knopman, David, Rademakers, Rosa, Lemstra, Afina W., Pijnenburg, Yolande A. L., Scheltens, Philip, Gasser, Thomas, Chinnery, Patrick F., Hemmer, Bernhard, Huisman, Martijn A., Troncoso, Juan, Moreno, Fermin., Nohr, Ellen A., Sorensen, Thorkild I. A., Heutink, Peter, Sanchez-Juan, Pascual, Posthuma, Danielle, Clarimon, Jordi, Christensen, Kaare, Ertekin-Taner, Nilufer, Scholz, Sonja W., Ramirez, Alfredo, Ruiz, Agustin, Slagboom, Eline, van der Flier, Wiesje M., and Holstege, Henne
Abstract: The IPDGC (The International Parkinson Disease Genomics Consortium) and EADB (Alzheimer Disease European DNA biobank) are listed correctly as an author to the article, however, they were incorrectly listed more than once.
Published: 2020

17. Metabolic Age Based on the BBMRI-NL 1 H-NMR Metabolomics Repository as Biomarker of Age-related Disease

Author: van den Akker, Erik B., Trompet, Stella, Barkey Wolf, Jurriaan J. H., Beekman, Marian, Suchiman, H. Eka D., Deelen, Joris, Asselbergs, Folkert W., Boersma, Eric, Cats, Davy, Elders, Petra M., Geleijnse, J. Marianne, Ikram, M. Arfan, Kloppenburg, Margreet, Mei, Haillang, Meulenbelt, Ingrid, Mooijaart, Simon P., Nelissen, Rob G. H. H., Netea, Mihai G., Penninx, Brenda W. J. H., Slofstra, Mariska, Stehouwer, Coen D. A., Swertz, Morris A., Teunissen, Charlotte E., Terwindt, Gisela M., 't Hart, Leen M., van den Maagdenberg, Arn M. J. M., van der Harst, Pim, van der Horst, Iwan C. C., van der Kallen, Carla J. H., van Greevenbroek, Marleen M. J., van Spil, W. Erwin, Wijmenga, Cisca, Zhernakova, Alexandra, Zwinderman, Aeilko H., Sattar, Naveed, Jukema, J. Wouter, van Duijn, Cornelia M., Boomsma, Dorret I., Reinders, Marcel J. T., Slagboom, P. Eline, van den Akker, Erik B., Trompet, Stella, Barkey Wolf, Jurriaan J. H., Beekman, Marian, Suchiman, H. Eka D., Deelen, Joris, Asselbergs, Folkert W., Boersma, Eric, Cats, Davy, Elders, Petra M., Geleijnse, J. Marianne, Ikram, M. Arfan, Kloppenburg, Margreet, Mei, Haillang, Meulenbelt, Ingrid, Mooijaart, Simon P., Nelissen, Rob G. H. H., Netea, Mihai G., Penninx, Brenda W. J. H., Slofstra, Mariska, Stehouwer, Coen D. A., Swertz, Morris A., Teunissen, Charlotte E., Terwindt, Gisela M., 't Hart, Leen M., van den Maagdenberg, Arn M. J. M., van der Harst, Pim, van der Horst, Iwan C. C., van der Kallen, Carla J. H., van Greevenbroek, Marleen M. J., van Spil, W. Erwin, Wijmenga, Cisca, Zhernakova, Alexandra, Zwinderman, Aeilko H., Sattar, Naveed, Jukema, J. Wouter, van Duijn, Cornelia M., Boomsma, Dorret I., Reinders, Marcel J. T., and Slagboom, P. Eline
Abstract: BACKGROUND: The blood metabolome incorporates cues from the environment and the host's genetic background, potentially offering a holistic view of an individual's health status.METHODS: We have compiled a vast resource of proton nuclear magnetic resonance metabolomics and phenotypic data encompassing over 25 000 samples derived from 26 community and hospital-based cohorts.RESULTS: Using this resource, we constructed a metabolomics-based age predictor (metaboAge) to calculate an individual's biological age. Exploration in independent cohorts demonstrates that being judged older by one's metabolome, as compared with one's chronological age, confers an increased risk on future cardiovascular disease, mortality, and functionality in older individuals. A web-based tool for calculating metaboAge (metaboage.researchlumc.nl) allows easy incorporation in other epidemiological studies. Access to data can be requested at bmri.nl/samples-images-data.CONCLUSIONS: In summary, we present a vast resource of metabolomics data and illustrate its merit by constructing a metabolomics-based score for biological age that captures aspects of current and future cardiometabolic health.
Published: 2020

18. Metabolic Age Based on the BBMRI-NL 1H-NMR Metabolomics Repository as Biomarker of Age-related Disease

Author: Team Medisch, Circulatory Health, Lab Reumatologie/Klinische Immunologie, Infection & Immunity, van den Akker, Erik B, Trompet, Stella, Barkey Wolf, Jurriaan J H, Beekman, Marian, Suchiman, H Eka D, Deelen, Joris, Asselbergs, Folkert W, Boersma, Eric, Cats, Davy, Elders, Petra M, Geleijnse, J Marianne, Ikram, M Arfan, Kloppenburg, Margreet, Mei, Haillang, Meulenbelt, Ingrid, Mooijaart, Simon P, Nelissen, Rob G H H, Netea, Mihai G, Penninx, Brenda W J H, Slofstra, Mariska, Stehouwer, Coen D A, Swertz, Morris A, Teunissen, Charlotte E, Terwindt, Gisela M, 't Hart, Leen M, van den Maagdenberg, Arn M J M, van der Harst, Pim, van der Horst, Iwan C C, van der Kallen, Carla J H, van Greevenbroek, Marleen M J, van Spil, W Erwin, Wijmenga, Cisca, Zhernakova, Alexandra, Zwinderman, Aeilko H, Sattar, Naveed, Jukema, J Wouter, van Duijn, Cornelia M, Boomsma, Dorret I, Reinders, Marcel J T, Slagboom, P Eline, Team Medisch, Circulatory Health, Lab Reumatologie/Klinische Immunologie, Infection & Immunity, van den Akker, Erik B, Trompet, Stella, Barkey Wolf, Jurriaan J H, Beekman, Marian, Suchiman, H Eka D, Deelen, Joris, Asselbergs, Folkert W, Boersma, Eric, Cats, Davy, Elders, Petra M, Geleijnse, J Marianne, Ikram, M Arfan, Kloppenburg, Margreet, Mei, Haillang, Meulenbelt, Ingrid, Mooijaart, Simon P, Nelissen, Rob G H H, Netea, Mihai G, Penninx, Brenda W J H, Slofstra, Mariska, Stehouwer, Coen D A, Swertz, Morris A, Teunissen, Charlotte E, Terwindt, Gisela M, 't Hart, Leen M, van den Maagdenberg, Arn M J M, van der Harst, Pim, van der Horst, Iwan C C, van der Kallen, Carla J H, van Greevenbroek, Marleen M J, van Spil, W Erwin, Wijmenga, Cisca, Zhernakova, Alexandra, Zwinderman, Aeilko H, Sattar, Naveed, Jukema, J Wouter, van Duijn, Cornelia M, Boomsma, Dorret I, Reinders, Marcel J T, and Slagboom, P Eline
Published: 2020

19. A nonsynonymous mutation in PLCG2 reduces the risk of Alzheimer's disease, dementia with Lewy bodies and frontotemporal dementia, and increases the likelihood of longevity

Author: van der Lee, Sven J., Conway, Olivia J., Jansen, Iris, Carrasquillo, Minerva M., Kleineidam, Luca, van den Akker, Erik, Hernandez, Isabel, van Eijk, Kristel R., Stringa, Najada, Chen, Jason A., Zettergren, Anna, Andlauer, Till F. M., Diez-Fairen, Monica, Simon-Sanchez, Javier, Lleo, Alberto, Zetterberg, Henrik, Nygaard, Marianne, Blauwendraat, Cornelis, Savage, Jeanne E., Mengel-From, Jonas, Moreno-Grau, Sonia, Wagner, Michael, Fortea, Juan, Keogh, Michael J., Blennow, Kaj, Skoog, Ingmar, Friese, Manuel A., Pletnikova, Olga, Zulaica, Miren, Lage, Carmen, de Rojas, Itziar, Riedel-Heller, Steffi, Illan-Gala, Ignacio, Wei, Wei, Jeune, Bernard, Orellana, Adelina, Bergh, Florian Then, Wang, Xue, Hulsman, Marc, Beker, Nina, Tesi, Niccolo, Morris, Christopher M., Indakoetxea, Begona, Collij, Lyduine E., Scherer, Martin, Morenas-Rodriguez, Estrella, Ironside, James W., van Berckel, Bart N. M., Alcolea, Daniel, Wiendl, Heinz, Strickland, Samantha L., Pastor, Pau, Rodriguez Rodriguez, Eloy, Boeve, Bradley F., Petersen, Ronald C., Ferman, Tanis J., van Gerpen, Jay A., Reinders, Marcel J. T., Uitti, Ryan J., Tarraga, Lluis, Maier, Wolfgang, Dols-Icardo, Oriol, Kawalia, Amit, Dalmasso, Maria Carolina, Boada, Merce, Zettl, Uwe K., van Schoor, Natasja M., Beekman, Marian, Allen, Mariet, Masliah, Eliezer, Lopez de Munain, Adolfo, Pantelyat, Alexander, Wszolek, Zbigniew K., Ross, Owen A., Dickson, Dennis W., Graff-Radford, Neill R., Knopman, David, Rademakers, Rosa, Lemstra, Afina W., Pijnenburg, Yolande A. L., Scheltens, Philip, Gasser, Thomas, Chinnery, Patrick F., Hemmer, Bernhard, Huisman, Martijn A., Troncoso, Juan, Moreno, Fermin, Nohr, Ellen A., Sorensen, Thorkild I. A., Heutink, Peter, Sanchez-Juan, Pascual, Posthuma, Danielle, Clarimon, Jordi, Christensen, Kaare, Ertekin-Taner, Nilufer, Scholz, Sonja W., Ramirez, Alfredo, Ruiz, Agustin, Slagboom, Eline, van der Flier, Wiesje M., Holstege, Henne, van der Lee, Sven J., Conway, Olivia J., Jansen, Iris, Carrasquillo, Minerva M., Kleineidam, Luca, van den Akker, Erik, Hernandez, Isabel, van Eijk, Kristel R., Stringa, Najada, Chen, Jason A., Zettergren, Anna, Andlauer, Till F. M., Diez-Fairen, Monica, Simon-Sanchez, Javier, Lleo, Alberto, Zetterberg, Henrik, Nygaard, Marianne, Blauwendraat, Cornelis, Savage, Jeanne E., Mengel-From, Jonas, Moreno-Grau, Sonia, Wagner, Michael, Fortea, Juan, Keogh, Michael J., Blennow, Kaj, Skoog, Ingmar, Friese, Manuel A., Pletnikova, Olga, Zulaica, Miren, Lage, Carmen, de Rojas, Itziar, Riedel-Heller, Steffi, Illan-Gala, Ignacio, Wei, Wei, Jeune, Bernard, Orellana, Adelina, Bergh, Florian Then, Wang, Xue, Hulsman, Marc, Beker, Nina, Tesi, Niccolo, Morris, Christopher M., Indakoetxea, Begona, Collij, Lyduine E., Scherer, Martin, Morenas-Rodriguez, Estrella, Ironside, James W., van Berckel, Bart N. M., Alcolea, Daniel, Wiendl, Heinz, Strickland, Samantha L., Pastor, Pau, Rodriguez Rodriguez, Eloy, Boeve, Bradley F., Petersen, Ronald C., Ferman, Tanis J., van Gerpen, Jay A., Reinders, Marcel J. T., Uitti, Ryan J., Tarraga, Lluis, Maier, Wolfgang, Dols-Icardo, Oriol, Kawalia, Amit, Dalmasso, Maria Carolina, Boada, Merce, Zettl, Uwe K., van Schoor, Natasja M., Beekman, Marian, Allen, Mariet, Masliah, Eliezer, Lopez de Munain, Adolfo, Pantelyat, Alexander, Wszolek, Zbigniew K., Ross, Owen A., Dickson, Dennis W., Graff-Radford, Neill R., Knopman, David, Rademakers, Rosa, Lemstra, Afina W., Pijnenburg, Yolande A. L., Scheltens, Philip, Gasser, Thomas, Chinnery, Patrick F., Hemmer, Bernhard, Huisman, Martijn A., Troncoso, Juan, Moreno, Fermin, Nohr, Ellen A., Sorensen, Thorkild I. A., Heutink, Peter, Sanchez-Juan, Pascual, Posthuma, Danielle, Clarimon, Jordi, Christensen, Kaare, Ertekin-Taner, Nilufer, Scholz, Sonja W., Ramirez, Alfredo, Ruiz, Agustin, Slagboom, Eline, van der Flier, Wiesje M., and Holstege, Henne
Abstract: The genetic variant rs72824905-G (minor allele) in the PLCG2 gene was previously associated with a reduced Alzheimer's disease risk (AD). The role of PLCG2 in immune system signaling suggests it may also protect against other neurodegenerative diseases and possibly associates with longevity. We studied the effect of the rs72824905-G on seven neurodegenerative diseases and longevity, using 53,627 patients, 3,516 long-lived individuals and 149,290 study-matched controls. We replicated the association of rs72824905-G with reduced AD risk and we found an association with reduced risk of dementia with Lewy bodies (DLB) and frontotemporal dementia (FTD). We did not find evidence for an effect on Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS) and multiple sclerosis (MS) risks, despite adequate sample sizes. Conversely, the rs72824905-G allele was associated with increased likelihood of longevity. By-proxy analyses in the UK Biobank supported the associations with both dementia and longevity. Concluding, rs72824905-G has a protective effect against multiple neurodegenerative diseases indicating shared aspects of disease etiology. Our findings merit studying the PLC gamma 2 pathway as drug-target.
Published: 2019

20. A nonsynonymous mutation in PLCG2 reduces the risk of Alzheimer's disease, dementia with Lewy bodies and frontotemporal dementia, and increases the likelihood of longevity

Author: van der Lee, Sven J., Conway, Olivia J., Jansen, Iris, Carrasquillo, Minerva M., Kleineidam, Luca, van den Akker, Erik, Hernandez, Isabel, van Eijk, Kristel R., Stringa, Najada, Chen, Jason A., Zettergren, Anna, Andlauer, Till F. M., Diez-Fairen, Monica, Simon-Sanchez, Javier, Lleo, Alberto, Zetterberg, Henrik, Nygaard, Marianne, Blauwendraat, Cornelis, Savage, Jeanne E., Mengel-From, Jonas, Moreno-Grau, Sonia, Wagner, Michael, Fortea, Juan, Keogh, Michael J., Blennow, Kaj, Skoog, Ingmar, Friese, Manuel A., Pletnikova, Olga, Zulaica, Miren, Lage, Carmen, de Rojas, Itziar, Riedel-Heller, Steffi, Illan-Gala, Ignacio, Wei, Wei, Jeune, Bernard, Orellana, Adelina, Bergh, Florian Then, Wang, Xue, Hulsman, Marc, Beker, Nina, Tesi, Niccolo, Morris, Christopher M., Indakoetxea, Begona, Collij, Lyduine E., Scherer, Martin, Morenas-Rodriguez, Estrella, Ironside, James W., van Berckel, Bart N. M., Alcolea, Daniel, Wiendl, Heinz, Strickland, Samantha L., Pastor, Pau, Rodriguez Rodriguez, Eloy, Boeve, Bradley F., Petersen, Ronald C., Ferman, Tanis J., van Gerpen, Jay A., Reinders, Marcel J. T., Uitti, Ryan J., Tarraga, Lluis, Maier, Wolfgang, Dols-Icardo, Oriol, Kawalia, Amit, Dalmasso, Maria Carolina, Boada, Merce, Zettl, Uwe K., van Schoor, Natasja M., Beekman, Marian, Allen, Mariet, Masliah, Eliezer, Lopez de Munain, Adolfo, Pantelyat, Alexander, Wszolek, Zbigniew K., Ross, Owen A., Dickson, Dennis W., Graff-Radford, Neill R., Knopman, David, Rademakers, Rosa, Lemstra, Afina W., Pijnenburg, Yolande A. L., Scheltens, Philip, Gasser, Thomas, Chinnery, Patrick F., Hemmer, Bernhard, Huisman, Martijn A., Troncoso, Juan, Moreno, Fermin, Nohr, Ellen A., Sorensen, Thorkild I. A., Heutink, Peter, Sanchez-Juan, Pascual, Posthuma, Danielle, Clarimon, Jordi, Christensen, Kaare, Ertekin-Taner, Nilufer, Scholz, Sonja W., Ramirez, Alfredo, Ruiz, Agustin, Slagboom, Eline, van der Flier, Wiesje M., Holstege, Henne, van der Lee, Sven J., Conway, Olivia J., Jansen, Iris, Carrasquillo, Minerva M., Kleineidam, Luca, van den Akker, Erik, Hernandez, Isabel, van Eijk, Kristel R., Stringa, Najada, Chen, Jason A., Zettergren, Anna, Andlauer, Till F. M., Diez-Fairen, Monica, Simon-Sanchez, Javier, Lleo, Alberto, Zetterberg, Henrik, Nygaard, Marianne, Blauwendraat, Cornelis, Savage, Jeanne E., Mengel-From, Jonas, Moreno-Grau, Sonia, Wagner, Michael, Fortea, Juan, Keogh, Michael J., Blennow, Kaj, Skoog, Ingmar, Friese, Manuel A., Pletnikova, Olga, Zulaica, Miren, Lage, Carmen, de Rojas, Itziar, Riedel-Heller, Steffi, Illan-Gala, Ignacio, Wei, Wei, Jeune, Bernard, Orellana, Adelina, Bergh, Florian Then, Wang, Xue, Hulsman, Marc, Beker, Nina, Tesi, Niccolo, Morris, Christopher M., Indakoetxea, Begona, Collij, Lyduine E., Scherer, Martin, Morenas-Rodriguez, Estrella, Ironside, James W., van Berckel, Bart N. M., Alcolea, Daniel, Wiendl, Heinz, Strickland, Samantha L., Pastor, Pau, Rodriguez Rodriguez, Eloy, Boeve, Bradley F., Petersen, Ronald C., Ferman, Tanis J., van Gerpen, Jay A., Reinders, Marcel J. T., Uitti, Ryan J., Tarraga, Lluis, Maier, Wolfgang, Dols-Icardo, Oriol, Kawalia, Amit, Dalmasso, Maria Carolina, Boada, Merce, Zettl, Uwe K., van Schoor, Natasja M., Beekman, Marian, Allen, Mariet, Masliah, Eliezer, Lopez de Munain, Adolfo, Pantelyat, Alexander, Wszolek, Zbigniew K., Ross, Owen A., Dickson, Dennis W., Graff-Radford, Neill R., Knopman, David, Rademakers, Rosa, Lemstra, Afina W., Pijnenburg, Yolande A. L., Scheltens, Philip, Gasser, Thomas, Chinnery, Patrick F., Hemmer, Bernhard, Huisman, Martijn A., Troncoso, Juan, Moreno, Fermin, Nohr, Ellen A., Sorensen, Thorkild I. A., Heutink, Peter, Sanchez-Juan, Pascual, Posthuma, Danielle, Clarimon, Jordi, Christensen, Kaare, Ertekin-Taner, Nilufer, Scholz, Sonja W., Ramirez, Alfredo, Ruiz, Agustin, Slagboom, Eline, van der Flier, Wiesje M., and Holstege, Henne
Abstract: The genetic variant rs72824905-G (minor allele) in the PLCG2 gene was previously associated with a reduced Alzheimer's disease risk (AD). The role of PLCG2 in immune system signaling suggests it may also protect against other neurodegenerative diseases and possibly associates with longevity. We studied the effect of the rs72824905-G on seven neurodegenerative diseases and longevity, using 53,627 patients, 3,516 long-lived individuals and 149,290 study-matched controls. We replicated the association of rs72824905-G with reduced AD risk and we found an association with reduced risk of dementia with Lewy bodies (DLB) and frontotemporal dementia (FTD). We did not find evidence for an effect on Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS) and multiple sclerosis (MS) risks, despite adequate sample sizes. Conversely, the rs72824905-G allele was associated with increased likelihood of longevity. By-proxy analyses in the UK Biobank supported the associations with both dementia and longevity. Concluding, rs72824905-G has a protective effect against multiple neurodegenerative diseases indicating shared aspects of disease etiology. Our findings merit studying the PLC gamma 2 pathway as drug-target.
Published: 2019

21. A meta-analysis of genome-wide association studies identifies multiple longevity genes

Author: Deelen, Joris, Evans, Daniel S., Arking, Dan E., Tesi, Niccola, Nygaard, Marianne, Liu, Xiaomin, Wojczynski, Mary K., Biggs, Mary L., van Der Spek, Ashley, Atzmon, Gil, Ware, Erin B., Sarnowski, Chloe, Smith, Albert, V, Seppala, Ilkka, Cordell, Heather J., Dose, Janina, Amin, Najaf, Arnold, Alice M., Ayers, Kristin L., Barzilai, Nir, Becker, Elizabeth J., Beekman, Marian, Blanche, Helene, Christensen, Kaare, Christiansen, Lene, Collerton, Joanna C., Cubaynes, Sarah, Cummings, Steven R., Davies, Karen, Debrabant, Birgit, Deleuze, Jean-Francois, Duncan, Rachel, Faul, Jessica D., Franceschi, Claudio, Galan, Pilar, Gudnaso, Vilmundur, Harris, Tamara B., Huisman, Martijn, Hurme, Mikko A., Jagger, Carol, Jansen, Iris, Jylha, Marja, Kahonen, Mika, Karasik, David, Kardia, Sharon L. R., Kingston, Andrew, Kirkwood, Thomas B. L., Launer, Lenore J., Lehtimaki, Terho, Lieb, Wolfgang, Lyytikainen, Leo-Pekka, Martin-Ruiz, Carmen, Min, Junxia, Nebe, Almut, Newman, Anne B., Nie, Chao, Nohr, Ellen A., Orwoll, Eric S., Perls, Thomas T., Province, Michael A., Psat, Bruce M., Raitakari, Olli T., Reinders, Marcel J. T., Robine, Jean-Marie, Rotter, Jerome, I, Sebastiani, Paola, Smith, Jennifer, Sørensen, Thorkild I. A., D Taylor, Kent, Uitterlinden, Andre G., van Der Flier, Wiesje, van Der Lee, Sven J., van Duijn, Cornelia M., van Heemst, Diana, Vaupel, James W., Weir, David, Ye, Kenny, Zeng, Yi, Zheng, Wanlin, Holstege, Henne, Kiel, Douglas P., Lunetta, Kathryn L., Slagboom, P. Eline, Murabito, Joanne M., Deelen, Joris, Evans, Daniel S., Arking, Dan E., Tesi, Niccola, Nygaard, Marianne, Liu, Xiaomin, Wojczynski, Mary K., Biggs, Mary L., van Der Spek, Ashley, Atzmon, Gil, Ware, Erin B., Sarnowski, Chloe, Smith, Albert, V, Seppala, Ilkka, Cordell, Heather J., Dose, Janina, Amin, Najaf, Arnold, Alice M., Ayers, Kristin L., Barzilai, Nir, Becker, Elizabeth J., Beekman, Marian, Blanche, Helene, Christensen, Kaare, Christiansen, Lene, Collerton, Joanna C., Cubaynes, Sarah, Cummings, Steven R., Davies, Karen, Debrabant, Birgit, Deleuze, Jean-Francois, Duncan, Rachel, Faul, Jessica D., Franceschi, Claudio, Galan, Pilar, Gudnaso, Vilmundur, Harris, Tamara B., Huisman, Martijn, Hurme, Mikko A., Jagger, Carol, Jansen, Iris, Jylha, Marja, Kahonen, Mika, Karasik, David, Kardia, Sharon L. R., Kingston, Andrew, Kirkwood, Thomas B. L., Launer, Lenore J., Lehtimaki, Terho, Lieb, Wolfgang, Lyytikainen, Leo-Pekka, Martin-Ruiz, Carmen, Min, Junxia, Nebe, Almut, Newman, Anne B., Nie, Chao, Nohr, Ellen A., Orwoll, Eric S., Perls, Thomas T., Province, Michael A., Psat, Bruce M., Raitakari, Olli T., Reinders, Marcel J. T., Robine, Jean-Marie, Rotter, Jerome, I, Sebastiani, Paola, Smith, Jennifer, Sørensen, Thorkild I. A., D Taylor, Kent, Uitterlinden, Andre G., van Der Flier, Wiesje, van Der Lee, Sven J., van Duijn, Cornelia M., van Heemst, Diana, Vaupel, James W., Weir, David, Ye, Kenny, Zeng, Yi, Zheng, Wanlin, Holstege, Henne, Kiel, Douglas P., Lunetta, Kathryn L., Slagboom, P. Eline, and Murabito, Joanne M.
Published: 2019

22. A nonsynonymous mutation in PLCG2 reduces the risk of Alzheimer's disease, dementia with Lewy bodies and frontotemporal dementia, and increases the likelihood of longevity

Author: van der Lee, Sven J., Conway, Olivia J., Jansen, Iris, Carrasquillo, Minerva M., Kleineidam, Luca, van den Akker, Erik, Hernandez, Isabel, van Eijk, Kristel R., Stringa, Najada, Chen, Jason A., Zettergren, Anna, Andlauer, Till F. M., Diez-Fairen, Monica, Simon-Sanchez, Javier, Lleo, Alberto, Zetterberg, Henrik, Nygaard, Marianne, Blauwendraat, Cornelis, Savage, Jeanne E., Mengel-From, Jonas, Moreno-Grau, Sonia, Wagner, Michael, Fortea, Juan, Keogh, Michael J., Blennow, Kaj, Skoog, Ingmar, Friese, Manuel A., Pletnikova, Olga, Zulaica, Miren, Lage, Carmen, de Rojas, Itziar, Riedel-Heller, Steffi, Illan-Gala, Ignacio, Wei, Wei, Jeune, Bernard, Orellana, Adelina, Bergh, Florian Then, Wang, Xue, Hulsman, Marc, Beker, Nina, Tesi, Niccolo, Morris, Christopher M., Indakoetxea, Begona, Collij, Lyduine E., Scherer, Martin, Morenas-Rodriguez, Estrella, Ironside, James W., van Berckel, Bart N. M., Alcolea, Daniel, Wiendl, Heinz, Strickland, Samantha L., Pastor, Pau, Rodriguez Rodriguez, Eloy, Boeve, Bradley F., Petersen, Ronald C., Ferman, Tanis J., van Gerpen, Jay A., Reinders, Marcel J. T., Uitti, Ryan J., Tarraga, Lluis, Maier, Wolfgang, Dols-Icardo, Oriol, Kawalia, Amit, Dalmasso, Maria Carolina, Boada, Merce, Zettl, Uwe K., van Schoor, Natasja M., Beekman, Marian, Allen, Mariet, Masliah, Eliezer, Lopez de Munain, Adolfo, Pantelyat, Alexander, Wszolek, Zbigniew K., Ross, Owen A., Dickson, Dennis W., Graff-Radford, Neill R., Knopman, David, Rademakers, Rosa, Lemstra, Afina W., Pijnenburg, Yolande A. L., Scheltens, Philip, Gasser, Thomas, Chinnery, Patrick F., Hemmer, Bernhard, Huisman, Martijn A., Troncoso, Juan, Moreno, Fermin, Nohr, Ellen A., Sørensen, Thorkild I. A., Heutink, Peter, Sanchez-Juan, Pascual, Posthuma, Danielle, Clarimon, Jordi, Christensen, Kaare, Ertekin-Taner, Nilufer, Scholz, Sonja W., Ramirez, Alfredo, Ruiz, Agustin, Slagboom, Eline, van der Flier, Wiesje M., Holstege, Henne, van der Lee, Sven J., Conway, Olivia J., Jansen, Iris, Carrasquillo, Minerva M., Kleineidam, Luca, van den Akker, Erik, Hernandez, Isabel, van Eijk, Kristel R., Stringa, Najada, Chen, Jason A., Zettergren, Anna, Andlauer, Till F. M., Diez-Fairen, Monica, Simon-Sanchez, Javier, Lleo, Alberto, Zetterberg, Henrik, Nygaard, Marianne, Blauwendraat, Cornelis, Savage, Jeanne E., Mengel-From, Jonas, Moreno-Grau, Sonia, Wagner, Michael, Fortea, Juan, Keogh, Michael J., Blennow, Kaj, Skoog, Ingmar, Friese, Manuel A., Pletnikova, Olga, Zulaica, Miren, Lage, Carmen, de Rojas, Itziar, Riedel-Heller, Steffi, Illan-Gala, Ignacio, Wei, Wei, Jeune, Bernard, Orellana, Adelina, Bergh, Florian Then, Wang, Xue, Hulsman, Marc, Beker, Nina, Tesi, Niccolo, Morris, Christopher M., Indakoetxea, Begona, Collij, Lyduine E., Scherer, Martin, Morenas-Rodriguez, Estrella, Ironside, James W., van Berckel, Bart N. M., Alcolea, Daniel, Wiendl, Heinz, Strickland, Samantha L., Pastor, Pau, Rodriguez Rodriguez, Eloy, Boeve, Bradley F., Petersen, Ronald C., Ferman, Tanis J., van Gerpen, Jay A., Reinders, Marcel J. T., Uitti, Ryan J., Tarraga, Lluis, Maier, Wolfgang, Dols-Icardo, Oriol, Kawalia, Amit, Dalmasso, Maria Carolina, Boada, Merce, Zettl, Uwe K., van Schoor, Natasja M., Beekman, Marian, Allen, Mariet, Masliah, Eliezer, Lopez de Munain, Adolfo, Pantelyat, Alexander, Wszolek, Zbigniew K., Ross, Owen A., Dickson, Dennis W., Graff-Radford, Neill R., Knopman, David, Rademakers, Rosa, Lemstra, Afina W., Pijnenburg, Yolande A. L., Scheltens, Philip, Gasser, Thomas, Chinnery, Patrick F., Hemmer, Bernhard, Huisman, Martijn A., Troncoso, Juan, Moreno, Fermin, Nohr, Ellen A., Sørensen, Thorkild I. A., Heutink, Peter, Sanchez-Juan, Pascual, Posthuma, Danielle, Clarimon, Jordi, Christensen, Kaare, Ertekin-Taner, Nilufer, Scholz, Sonja W., Ramirez, Alfredo, Ruiz, Agustin, Slagboom, Eline, van der Flier, Wiesje M., and Holstege, Henne
Published: 2019

23. A meta-analysis of genome-wide association studies identifies multiple longevity genes

Author: Deelen, Joris, Evans, Daniel S., Arking, Dan E., Tesi, Niccola, Nygaard, Marianne, Liu, Xiaomin, Wojczynski, Mary K., Biggs, Mary L., van Der Spek, Ashley, Atzmon, Gil, Ware, Erin B., Sarnowski, Chloe, Smith, Albert, V, Seppala, Ilkka, Cordell, Heather J., Dose, Janina, Amin, Najaf, Arnold, Alice M., Ayers, Kristin L., Barzilai, Nir, Becker, Elizabeth J., Beekman, Marian, Blanche, Helene, Christensen, Kaare, Christiansen, Lene, Collerton, Joanna C., Cubaynes, Sarah, Cummings, Steven R., Davies, Karen, Debrabant, Birgit, Deleuze, Jean-Francois, Duncan, Rachel, Faul, Jessica D., Franceschi, Claudio, Galan, Pilar, Gudnaso, Vilmundur, Harris, Tamara B., Huisman, Martijn, Hurme, Mikko A., Jagger, Carol, Jansen, Iris, Jylha, Marja, Kahonen, Mika, Karasik, David, Kardia, Sharon L. R., Kingston, Andrew, Kirkwood, Thomas B. L., Launer, Lenore J., Lehtimaki, Terho, Lieb, Wolfgang, Lyytikainen, Leo-Pekka, Martin-Ruiz, Carmen, Min, Junxia, Nebe, Almut, Newman, Anne B., Nie, Chao, Nohr, Ellen A., Orwoll, Eric S., Perls, Thomas T., Province, Michael A., Psat, Bruce M., Raitakari, Olli T., Reinders, Marcel J. T., Robine, Jean-Marie, Rotter, Jerome, I, Sebastiani, Paola, Smith, Jennifer, Sørensen, Thorkild I. A., D Taylor, Kent, Uitterlinden, Andre G., van Der Flier, Wiesje, van Der Lee, Sven J., van Duijn, Cornelia M., van Heemst, Diana, Vaupel, James W., Weir, David, Ye, Kenny, Zeng, Yi, Zheng, Wanlin, Holstege, Henne, Kiel, Douglas P., Lunetta, Kathryn L., Slagboom, P. Eline, Murabito, Joanne M., Deelen, Joris, Evans, Daniel S., Arking, Dan E., Tesi, Niccola, Nygaard, Marianne, Liu, Xiaomin, Wojczynski, Mary K., Biggs, Mary L., van Der Spek, Ashley, Atzmon, Gil, Ware, Erin B., Sarnowski, Chloe, Smith, Albert, V, Seppala, Ilkka, Cordell, Heather J., Dose, Janina, Amin, Najaf, Arnold, Alice M., Ayers, Kristin L., Barzilai, Nir, Becker, Elizabeth J., Beekman, Marian, Blanche, Helene, Christensen, Kaare, Christiansen, Lene, Collerton, Joanna C., Cubaynes, Sarah, Cummings, Steven R., Davies, Karen, Debrabant, Birgit, Deleuze, Jean-Francois, Duncan, Rachel, Faul, Jessica D., Franceschi, Claudio, Galan, Pilar, Gudnaso, Vilmundur, Harris, Tamara B., Huisman, Martijn, Hurme, Mikko A., Jagger, Carol, Jansen, Iris, Jylha, Marja, Kahonen, Mika, Karasik, David, Kardia, Sharon L. R., Kingston, Andrew, Kirkwood, Thomas B. L., Launer, Lenore J., Lehtimaki, Terho, Lieb, Wolfgang, Lyytikainen, Leo-Pekka, Martin-Ruiz, Carmen, Min, Junxia, Nebe, Almut, Newman, Anne B., Nie, Chao, Nohr, Ellen A., Orwoll, Eric S., Perls, Thomas T., Province, Michael A., Psat, Bruce M., Raitakari, Olli T., Reinders, Marcel J. T., Robine, Jean-Marie, Rotter, Jerome, I, Sebastiani, Paola, Smith, Jennifer, Sørensen, Thorkild I. A., D Taylor, Kent, Uitterlinden, Andre G., van Der Flier, Wiesje, van Der Lee, Sven J., van Duijn, Cornelia M., van Heemst, Diana, Vaupel, James W., Weir, David, Ye, Kenny, Zeng, Yi, Zheng, Wanlin, Holstege, Henne, Kiel, Douglas P., Lunetta, Kathryn L., Slagboom, P. Eline, and Murabito, Joanne M.
Published: 2019

24. A nonsynonymous mutation in PLCG2 reduces the risk of Alzheimer's disease, dementia with Lewy bodies and frontotemporal dementia, and increases the likelihood of longevity

Author: van der Lee, Sven J., Conway, Olivia J., Jansen, Iris, Carrasquillo, Minerva M., Kleineidam, Luca, van den Akker, Erik, Hernandez, Isabel, van Eijk, Kristel R., Stringa, Najada, Chen, Jason A., Zettergren, Anna, Andlauer, Till F. M., Diez-Fairen, Monica, Simon-Sanchez, Javier, Lleo, Alberto, Zetterberg, Henrik, Nygaard, Marianne, Blauwendraat, Cornelis, Savage, Jeanne E., Mengel-From, Jonas, Moreno-Grau, Sonia, Wagner, Michael, Fortea, Juan, Keogh, Michael J., Blennow, Kaj, Skoog, Ingmar, Friese, Manuel A., Pletnikova, Olga, Zulaica, Miren, Lage, Carmen, de Rojas, Itziar, Riedel-Heller, Steffi, Illan-Gala, Ignacio, Wei, Wei, Jeune, Bernard, Orellana, Adelina, Bergh, Florian Then, Wang, Xue, Hulsman, Marc, Beker, Nina, Tesi, Niccolo, Morris, Christopher M., Indakoetxea, Begona, Collij, Lyduine E., Scherer, Martin, Morenas-Rodriguez, Estrella, Ironside, James W., van Berckel, Bart N. M., Alcolea, Daniel, Wiendl, Heinz, Strickland, Samantha L., Pastor, Pau, Rodriguez Rodriguez, Eloy, Boeve, Bradley F., Petersen, Ronald C., Ferman, Tanis J., van Gerpen, Jay A., Reinders, Marcel J. T., Uitti, Ryan J., Tarraga, Lluis, Maier, Wolfgang, Dols-Icardo, Oriol, Kawalia, Amit, Dalmasso, Maria Carolina, Boada, Merce, Zettl, Uwe K., van Schoor, Natasja M., Beekman, Marian, Allen, Mariet, Masliah, Eliezer, Lopez de Munain, Adolfo, Pantelyat, Alexander, Wszolek, Zbigniew K., Ross, Owen A., Dickson, Dennis W., Graff-Radford, Neill R., Knopman, David, Rademakers, Rosa, Lemstra, Afina W., Pijnenburg, Yolande A. L., Scheltens, Philip, Gasser, Thomas, Chinnery, Patrick F., Hemmer, Bernhard, Huisman, Martijn A., Troncoso, Juan, Moreno, Fermin, Nohr, Ellen A., Sørensen, Thorkild I. A., Heutink, Peter, Sanchez-Juan, Pascual, Posthuma, Danielle, Clarimon, Jordi, Christensen, Kaare, Ertekin-Taner, Nilufer, Scholz, Sonja W., Ramirez, Alfredo, Ruiz, Agustin, Slagboom, Eline, van der Flier, Wiesje M., Holstege, Henne, van der Lee, Sven J., Conway, Olivia J., Jansen, Iris, Carrasquillo, Minerva M., Kleineidam, Luca, van den Akker, Erik, Hernandez, Isabel, van Eijk, Kristel R., Stringa, Najada, Chen, Jason A., Zettergren, Anna, Andlauer, Till F. M., Diez-Fairen, Monica, Simon-Sanchez, Javier, Lleo, Alberto, Zetterberg, Henrik, Nygaard, Marianne, Blauwendraat, Cornelis, Savage, Jeanne E., Mengel-From, Jonas, Moreno-Grau, Sonia, Wagner, Michael, Fortea, Juan, Keogh, Michael J., Blennow, Kaj, Skoog, Ingmar, Friese, Manuel A., Pletnikova, Olga, Zulaica, Miren, Lage, Carmen, de Rojas, Itziar, Riedel-Heller, Steffi, Illan-Gala, Ignacio, Wei, Wei, Jeune, Bernard, Orellana, Adelina, Bergh, Florian Then, Wang, Xue, Hulsman, Marc, Beker, Nina, Tesi, Niccolo, Morris, Christopher M., Indakoetxea, Begona, Collij, Lyduine E., Scherer, Martin, Morenas-Rodriguez, Estrella, Ironside, James W., van Berckel, Bart N. M., Alcolea, Daniel, Wiendl, Heinz, Strickland, Samantha L., Pastor, Pau, Rodriguez Rodriguez, Eloy, Boeve, Bradley F., Petersen, Ronald C., Ferman, Tanis J., van Gerpen, Jay A., Reinders, Marcel J. T., Uitti, Ryan J., Tarraga, Lluis, Maier, Wolfgang, Dols-Icardo, Oriol, Kawalia, Amit, Dalmasso, Maria Carolina, Boada, Merce, Zettl, Uwe K., van Schoor, Natasja M., Beekman, Marian, Allen, Mariet, Masliah, Eliezer, Lopez de Munain, Adolfo, Pantelyat, Alexander, Wszolek, Zbigniew K., Ross, Owen A., Dickson, Dennis W., Graff-Radford, Neill R., Knopman, David, Rademakers, Rosa, Lemstra, Afina W., Pijnenburg, Yolande A. L., Scheltens, Philip, Gasser, Thomas, Chinnery, Patrick F., Hemmer, Bernhard, Huisman, Martijn A., Troncoso, Juan, Moreno, Fermin, Nohr, Ellen A., Sørensen, Thorkild I. A., Heutink, Peter, Sanchez-Juan, Pascual, Posthuma, Danielle, Clarimon, Jordi, Christensen, Kaare, Ertekin-Taner, Nilufer, Scholz, Sonja W., Ramirez, Alfredo, Ruiz, Agustin, Slagboom, Eline, van der Flier, Wiesje M., and Holstege, Henne
Published: 2019

25. Nucleus-specific expression in the multinuclear mushroom-forming fungus reveals different nuclear regulatory programs

Author: Gehrmann, Thies, Pelkmans, Jordi F, Ohm, Robin A, Vos, Aurin M, Sonnenberg, Anton S.M., Baars, Johan J.P., Wösten, Han A B, Reinders, Marcel J T, Abeel, Thomas, Gehrmann, Thies, Pelkmans, Jordi F, Ohm, Robin A, Vos, Aurin M, Sonnenberg, Anton S.M., Baars, Johan J.P., Wösten, Han A B, Reinders, Marcel J T, and Abeel, Thomas
Abstract: Many fungi are polykaryotic, containing multiple nuclei per cell. In the case of heterokaryons, there are different nuclear types within a single cell. It is unknown what the different nuclear types contribute in terms of mRNA expression levels in fungal heterokaryons. Each cell of the mushroom Agaricus bisporus contains two to 25 nuclei of two nuclear types originating from two parental strains. Using RNA-sequencing data, we assess the differential mRNA contribution of individual nuclear types and its functional impact. We studied differential expression between genes of the two nuclear types, P1 and P2, throughout mushroom development in various tissue types. P1 and P2 produced specific mRNA profiles that changed through mushroom development. Differential regulation occurred at the gene level, rather than at the locus, chromosomal, or nuclear level. P1 dominated mRNA production throughout development, and P2 showed more differentially up-regulated genes in important functional groups. In the vegetative mycelium, P2 up-regulated almost threefold more metabolism genes and carbohydrate active enzymes (cazymes) than P1, suggesting phenotypic differences in growth. We identified widespread transcriptomic variation between the nuclear types of A. bisporus Our method enables studying nucleus-specific expression, which likely influences the phenotype of a fungus in a polykaryotic stage. Our findings have a wider impact to better understand gene regulation in fungi in a heterokaryotic state. This work provides insight into the transcriptomic variation introduced by genomic nuclear separation.
Published: 2018

26. Nucleus-specific expression in the multinuclear mushroom-forming fungus reveals different nuclear regulatory programs

Author: Molecular Microbiology, Sub Molecular Microbiology, Gehrmann, Thies, Pelkmans, Jordi F, Ohm, Robin A, Vos, Aurin M, Sonnenberg, Anton S.M., Baars, Johan J.P., Wösten, Han A B, Reinders, Marcel J T, Abeel, Thomas, Molecular Microbiology, Sub Molecular Microbiology, Gehrmann, Thies, Pelkmans, Jordi F, Ohm, Robin A, Vos, Aurin M, Sonnenberg, Anton S.M., Baars, Johan J.P., Wösten, Han A B, Reinders, Marcel J T, and Abeel, Thomas
Published: 2018

27. Nucleus-specific expression in the multinuclear mushroom-forming fungus reveals different nuclear regulatory programs

Author: Molecular Microbiology, Sub Molecular Microbiology, Gehrmann, Thies, Pelkmans, Jordi F, Ohm, Robin A, Vos, Aurin M, Sonnenberg, Anton S.M., Baars, Johan J.P., Wösten, Han A B, Reinders, Marcel J T, Abeel, Thomas, Molecular Microbiology, Sub Molecular Microbiology, Gehrmann, Thies, Pelkmans, Jordi F, Ohm, Robin A, Vos, Aurin M, Sonnenberg, Anton S.M., Baars, Johan J.P., Wösten, Han A B, Reinders, Marcel J T, and Abeel, Thomas
Published: 2018

28. Nucleus-specific expression in the multinuclear mushroom-forming fungus reveals different nuclear regulatory programs

Author: Molecular Microbiology, Sub Molecular Microbiology, Gehrmann, Thies, Pelkmans, Jordi F, Ohm, Robin A, Vos, Aurin M, Sonnenberg, Anton S.M., Baars, Johan J.P., Wösten, Han A B, Reinders, Marcel J T, Abeel, Thomas, Molecular Microbiology, Sub Molecular Microbiology, Gehrmann, Thies, Pelkmans, Jordi F, Ohm, Robin A, Vos, Aurin M, Sonnenberg, Anton S.M., Baars, Johan J.P., Wösten, Han A B, Reinders, Marcel J T, and Abeel, Thomas
Published: 2018

29. Transcription factors of Schizophyllum commune involved in mushroom formation and modulation of vegetative growth

Author: Sub Molecular Microbiology, Molecular Microbiology, Pelkmans, Jordi F, Patil, Mohini B, Gehrmann, Thies, Reinders, Marcel J T, Wösten, Han A B, Lugones, Luis G, Sub Molecular Microbiology, Molecular Microbiology, Pelkmans, Jordi F, Patil, Mohini B, Gehrmann, Thies, Reinders, Marcel J T, Wösten, Han A B, and Lugones, Luis G
Published: 2017

30. Transcription factors of Schizophyllum commune involved in mushroom formation and modulation of vegetative growth

Author: Sub Molecular Microbiology, Molecular Microbiology, Pelkmans, Jordi F, Patil, Mohini B, Gehrmann, Thies, Reinders, Marcel J T, Wösten, Han A B, Lugones, Luis G, Sub Molecular Microbiology, Molecular Microbiology, Pelkmans, Jordi F, Patil, Mohini B, Gehrmann, Thies, Reinders, Marcel J T, Wösten, Han A B, and Lugones, Luis G
Published: 2017

31. Transcription factors of Schizophyllum commune involved in mushroom formation and modulation of vegetative growth

Author: Sub Molecular Microbiology, Molecular Microbiology, Pelkmans, Jordi F, Patil, Mohini B, Gehrmann, Thies, Reinders, Marcel J T, Wösten, Han A B, Lugones, Luis G, Sub Molecular Microbiology, Molecular Microbiology, Pelkmans, Jordi F, Patil, Mohini B, Gehrmann, Thies, Reinders, Marcel J T, Wösten, Han A B, and Lugones, Luis G
Published: 2017

32. ECCB 2016 : The 15th European Conference on Computational Biology

Author: Heringa, Jaap, Reinders, Marcel J T, Abeln, Sanne, De Ridder, Jeroen, Heringa, Jaap, Reinders, Marcel J T, Abeln, Sanne, and De Ridder, Jeroen
Published: 2016

33. Gene co-expression analysis identifies brain regions and cell types involved in migraine pathophysiology

Author: University of Helsinki, Clinicum, University of Helsinki, Institute for Molecular Medicine Finland (FIMM), Eising, Else, Huisman, Sjoerd M. H., Mahfouz, Ahmed, Vijfhuizen, Lisanne S., Anttila, Verneri, Winsvold, Bendik S., Kurth, Tobias, Ikram, M. Arfan, Freilinger, Tobias, Kaprio, Jaakko, Boomsma, Dorret I., van Duijn, Cornelia M., Jarvelin, Marjo-Riitta R., Zwart, John-Anker, Quaye, Lydia, Strachan, David P., Kubisch, Christian, Dichgans, Martin, Smith, George Davey, Stefansson, Kari, Palotie, Aarno, Chasman, Daniel I., Ferrari, Michel D., Terwindt, Gisela M., de Vries, Boukje, Nyholt, Dale R., Lelieveldt, Boudewijn P. F., van den Maagdenberg, Arn M. J. M., Reinders, Marcel J. T., University of Helsinki, Clinicum, University of Helsinki, Institute for Molecular Medicine Finland (FIMM), Eising, Else, Huisman, Sjoerd M. H., Mahfouz, Ahmed, Vijfhuizen, Lisanne S., Anttila, Verneri, Winsvold, Bendik S., Kurth, Tobias, Ikram, M. Arfan, Freilinger, Tobias, Kaprio, Jaakko, Boomsma, Dorret I., van Duijn, Cornelia M., Jarvelin, Marjo-Riitta R., Zwart, John-Anker, Quaye, Lydia, Strachan, David P., Kubisch, Christian, Dichgans, Martin, Smith, George Davey, Stefansson, Kari, Palotie, Aarno, Chasman, Daniel I., Ferrari, Michel D., Terwindt, Gisela M., de Vries, Boukje, Nyholt, Dale R., Lelieveldt, Boudewijn P. F., van den Maagdenberg, Arn M. J. M., and Reinders, Marcel J. T.
Abstract: Migraine is a common disabling neurovascular brain disorder typically characterised by attacks of severe headache and associated with autonomic and neurological symptoms. Migraine is caused by an interplay of genetic and environmental factors. Genome-wide association studies (GWAS) have identified over a dozen genetic loci associated with migraine. Here, we integrated migraine GWAS data with high-resolution spatial gene expression data of normal adult brains from the Allen Human Brain Atlas to identify specific brain regions and molecular pathways that are possibly involved in migraine pathophysiology. To this end, we used two complementary methods. In GWAS data from 23,285 migraine cases and 95,425 controls, we first studied modules of co-expressed genes that were calculated based on human brain expression data for enrichment of genes that showed association with migraine. Enrichment of a migraine GWAS signal was found for five modules that suggest involvement in migraine pathophysiology of: (i) neurotransmission, protein catabolism and mitochondria in the cortex; (ii) transcription regulation in the cortex and cerebellum; and (iii) oligodendrocytes and mitochondria in subcortical areas. Second, we used the high-confidence genes from the migraine GWAS as a basis to construct local migraine-related co-expression gene networks. Signatures of all brain regions and pathways that were prominent in the first method also surfaced in the second method, thus providing support that these brain regions and pathways are indeed involved in migraine pathophysiology.
Published: 2016

34. ECCB 2016 : The 15th European Conference on Computational Biology

Author: Heringa, Jaap, Reinders, Marcel J T, Abeln, Sanne, De Ridder, Jeroen, Heringa, Jaap, Reinders, Marcel J T, Abeln, Sanne, and De Ridder, Jeroen
Published: 2016

35. ECCB 2016 : The 15th European Conference on Computational Biology

Author: Heringa, Jaap, Reinders, Marcel J T, Abeln, Sanne, De Ridder, Jeroen, Heringa, Jaap, Reinders, Marcel J T, Abeln, Sanne, and De Ridder, Jeroen
Published: 2016

36. ECCB 2016: The 15th European Conference on Computational Biology

Author: CMM Groep De Ridder, Heringa, Jaap, Reinders, Marcel J T, Abeln, Sanne, De Ridder, Jeroen, CMM Groep De Ridder, Heringa, Jaap, Reinders, Marcel J T, Abeln, Sanne, and De Ridder, Jeroen
Published: 2016

37. Switching from a unicellular to multicellular organization in an Aspergillus niger hypha

Author: Bleichrodt, Robert-Jan, Hulsman, Marc, Wosten, H.A.B., Reinders, Marcel J T, Bleichrodt, Robert-Jan, Hulsman, Marc, Wosten, H.A.B., and Reinders, Marcel J T
Abstract: UNLABELLED: Pores in fungal septa enable cytoplasmic streaming between hyphae and their compartments. Consequently, the mycelium can be considered unicellular. However, we show here that Woronin bodies close ~50% of the three most apical septa of growing hyphae of Aspergillus niger. The incidence of closure of the 9th and 10th septa was even ≥94%. Intercompartmental streaming of photoactivatable green fluorescent protein (PA-GFP) was not observed when the septa were closed, but open septa acted as a barrier, reducing the mobility rate of PA-GFP ~500 times. This mobility rate decreased with increasing septal age and under stress conditions, likely reflecting a regulatory mechanism affecting septal pore diameter. Modeling revealed that such regulation offers effective control of compound concentration between compartments. Modeling also showed that the incidence of septal closure in A. niger had an even stronger impact on cytoplasmic continuity. Cytoplasm of hyphal compartments was shown not to be in physical contact when separated by more than 4 septa. Together, data show that apical compartments of growing hyphae behave unicellularly, while older compartments have a multicellular organization.IMPORTANCE: The hyphae of higher fungi are compartmentalized by porous septa that enable cytosolic streaming. Therefore, it is believed that the mycelium shares cytoplasm. However, it is shown here that the septa of Aspergillus niger are always closed in the oldest part of the hyphae, and therefore, these compartments are physically isolated from each other. In contrast, only part of the septa is closed in the youngest part of the hyphae. Still, compartments in this hyphal part are physically isolated when separated by more than 4 septa. Even open septa act as a barrier for cytoplasmic mixing. The mobility rate through such septa reduces with increasing septal age and under stress conditions. Modeling shows that the septal pore width is set such that its regulation of
Published: 2015

38. Switching from a unicellular to multicellular organization in an Aspergillus niger hypha

Author: Sub Molecular Microbiology, Dep Biologie, Molecular Microbiology, Bleichrodt, Robert-Jan, Hulsman, Marc, Wosten, H.A.B., Reinders, Marcel J T, Sub Molecular Microbiology, Dep Biologie, Molecular Microbiology, Bleichrodt, Robert-Jan, Hulsman, Marc, Wosten, H.A.B., and Reinders, Marcel J T
Published: 2015

39. Analysis of high-throughput screening reveals the effect of surface topographies on cellular morphology

Author: Hulsman, Marc, Hulsman, Marc, Hulshof, Frits, Unadkat, Hemant, Papenburg, Bernke J., Stamatialis, Dimitrios F., Truckenmuller, Roman, van Blitterswijk, Clemens, de Boer, Jan, Reinders, Marcel J. T., Hulsman, Marc, Hulsman, Marc, Hulshof, Frits, Unadkat, Hemant, Papenburg, Bernke J., Stamatialis, Dimitrios F., Truckenmuller, Roman, van Blitterswijk, Clemens, de Boer, Jan, and Reinders, Marcel J. T.
Abstract: Surface topographies of materials considerably impact cellular behavior as they have been shown to affect cell growth, provide cell guidance, and even induce cell differentiation. Consequently, for successful application in tissue engineering, the contact interface of biomaterials needs to be optimized to induce the required cell behavior. However, a rational design of biomaterial surfaces is severely hampered because knowledge is lacking on the underlying biological mechanisms. Therefore, we previously developed a high-throughput screening device (TopoChip) that measures cell responses to large libraries of parameterized topographical material surfaces. Here, we introduce a computational analysis of high-throughput materiome data to capture the relationship between the surface topographies of materials and cellular morphology. We apply robust statistical techniques to find surface topographies that best promote a certain specified cellular response. By augmenting surface screening with data-driven modeling, we determine which properties of the surface topographies influence the morphological properties of the cells. With this information, we build models that predict the cellular response to surface topographies that have not yet been measured. We analyze cellular morphology on 2176 surfaces, and find that the surface topography significantly affects various cellular properties, including the roundness and size of the nucleus, as well as the perimeter and orientation of the cells. Our learned models capture and accurately predict these relationships and reveal a spectrum of topographies that induce various levels of cellular morphologies. Taken together, this novel approach of high-throughput screening of materials and subsequent analysis opens up possibilities for a rational design of biomaterial surfaces.
Published: 2015

40. Switching from a unicellular to multicellular organization in an Aspergillus niger hypha

Author: Sub Molecular Microbiology, Dep Biologie, Molecular Microbiology, Bleichrodt, Robert-Jan, Hulsman, Marc, Wosten, H.A.B., Reinders, Marcel J T, Sub Molecular Microbiology, Dep Biologie, Molecular Microbiology, Bleichrodt, Robert-Jan, Hulsman, Marc, Wosten, H.A.B., and Reinders, Marcel J T
Published: 2015

41. Switching from a unicellular to multicellular organization in an Aspergillus niger hypha

Author: Sub Molecular Microbiology, Dep Biologie, Molecular Microbiology, Bleichrodt, Robert-Jan, Hulsman, Marc, Wosten, H.A.B., Reinders, Marcel J T, Sub Molecular Microbiology, Dep Biologie, Molecular Microbiology, Bleichrodt, Robert-Jan, Hulsman, Marc, Wosten, H.A.B., and Reinders, Marcel J T
Published: 2015

42. Analysis of high-throughput screening reveals the effect of surface topographies on cellular morphology

Author: Hulsman, Marc, Hulshof, Frits, Unadkat, Hemant, Papenburg, Bernke J., Stamatialis, Dimitrios F., Truckenmuller, Roman, van Blitterswijk, Clemens, de Boer, Jan, Reinders, Marcel J. T., Hulsman, Marc, Hulshof, Frits, Unadkat, Hemant, Papenburg, Bernke J., Stamatialis, Dimitrios F., Truckenmuller, Roman, van Blitterswijk, Clemens, de Boer, Jan, and Reinders, Marcel J. T.
Abstract: Surface topographies of materials considerably impact cellular behavior as they have been shown to affect cell growth, provide cell guidance, and even induce cell differentiation. Consequently, for successful application in tissue engineering, the contact interface of biomaterials needs to be optimized to induce the required cell behavior. However, a rational design of biomaterial surfaces is severely hampered because knowledge is lacking on the underlying biological mechanisms. Therefore, we previously developed a high-throughput screening device (TopoChip) that measures cell responses to large libraries of parameterized topographical material surfaces. Here, we introduce a computational analysis of high-throughput materiome data to capture the relationship between the surface topographies of materials and cellular morphology. We apply robust statistical techniques to find surface topographies that best promote a certain specified cellular response. By augmenting surface screening with data-driven modeling, we determine which properties of the surface topographies influence the morphological properties of the cells. With this information, we build models that predict the cellular response to surface topographies that have not yet been measured. We analyze cellular morphology on 2176 surfaces, and find that the surface topography significantly affects various cellular properties, including the roundness and size of the nucleus, as well as the perimeter and orientation of the cells. Our learned models capture and accurately predict these relationships and reveal a spectrum of topographies that induce various levels of cellular morphologies. Taken together, this novel approach of high-throughput screening of materials and subsequent analysis opens up possibilities for a rational design of biomaterial surfaces.
Published: 2015

43. Predicting the therapeutic efficacy of MSC in bone tissue engineering using the molecular marker CADM1

Author: Faculteit Diergeneeskunde, LS Equine Muscoskeletal Biology, Onderzoek, Mentink, Anouk, Hulsman, Marc, Groen, Nathalie, Licht, Ruud, Dechering, Koen J, van der Stok, Johan, Alves, Hugo A, Dhert, Wouter JA, van Someren, Eugene P, Reinders, Marcel J T, van Blitterswijk, Clemens A, de Boer, Jan, Faculteit Diergeneeskunde, LS Equine Muscoskeletal Biology, Onderzoek, Mentink, Anouk, Hulsman, Marc, Groen, Nathalie, Licht, Ruud, Dechering, Koen J, van der Stok, Johan, Alves, Hugo A, Dhert, Wouter JA, van Someren, Eugene P, Reinders, Marcel J T, van Blitterswijk, Clemens A, and de Boer, Jan
Published: 2013

44. Predicting the therapeutic efficacy of MSC in bone tissue engineering using the molecular marker CADM1

Author: Faculteit Diergeneeskunde, LS Equine Muscoskeletal Biology, Onderzoek, Mentink, Anouk, Hulsman, Marc, Groen, Nathalie, Licht, Ruud, Dechering, Koen J, van der Stok, Johan, Alves, Hugo A, Dhert, Wouter JA, van Someren, Eugene P, Reinders, Marcel J T, van Blitterswijk, Clemens A, de Boer, Jan, Faculteit Diergeneeskunde, LS Equine Muscoskeletal Biology, Onderzoek, Mentink, Anouk, Hulsman, Marc, Groen, Nathalie, Licht, Ruud, Dechering, Koen J, van der Stok, Johan, Alves, Hugo A, Dhert, Wouter JA, van Someren, Eugene P, Reinders, Marcel J T, van Blitterswijk, Clemens A, and de Boer, Jan
Published: 2013

45. Predicting the therapeutic efficacy of MSC in bone tissue engineering using the molecular marker CADM1

Author: Faculteit Diergeneeskunde, LS Equine Muscoskeletal Biology, Onderzoek, Mentink, Anouk, Hulsman, Marc, Groen, Nathalie, Licht, Ruud, Dechering, Koen J, van der Stok, Johan, Alves, Hugo A, Dhert, Wouter JA, van Someren, Eugene P, Reinders, Marcel J T, van Blitterswijk, Clemens A, de Boer, Jan, Faculteit Diergeneeskunde, LS Equine Muscoskeletal Biology, Onderzoek, Mentink, Anouk, Hulsman, Marc, Groen, Nathalie, Licht, Ruud, Dechering, Koen J, van der Stok, Johan, Alves, Hugo A, Dhert, Wouter JA, van Someren, Eugene P, Reinders, Marcel J T, van Blitterswijk, Clemens A, and de Boer, Jan
Published: 2013

46. Prior Biological Knowledge And Epigenetic Information Enhances Prediction Accuracy Of Bayesian Wnt Pathway

Author: Sinha, Shriprakash, Reinders, Marcel J. T., Verhaegh, Wim, Sinha, Shriprakash, Reinders, Marcel J. T., and Verhaegh, Wim
Abstract: Computational modeling of Wnt signaling pathway has gained prominence for its use as computer aided diagnostic tool to develop therapeutic cancer target drugs and predict of test samples as cancerous and non cancerous. This manuscript focuses on development of simple static bayesian network models of varying complexity that encompasses prior partially available biological knowledge about intra and extra cellular factors affecting the Wnt pathway and incorporates epigenetic information like methylation and histone modification of a few genes known to have inhibitory affect on Wnt pathway. It might be expected that such models not only increase cancer prediction accuracies and also form basis for understanding Wnt signaling activity in different states of tumorigenesis. Initial results in human colorectal cancer cases indicate that incorporation of epigenetic information increases prediction accuracy of test samples as being tumorous or normal. Receiver Operator Curves (ROC) and their respective area under the curve (AUC) measurements, obtained from predictions of state of test sample and corresponding predictions of the state of activation of transcription complex of the Wnt pathway for the test sample, indicate that there is significant difference between the Wnt pathway being on (off) and its association with the sample being tumorous (normal). Two sample Kolmogorov-Smirnov test confirm the statistical deviation between the distributions of these predictions. At a preliminary stage, use of these models may help in understanding the yet unknown effect of certain factors like DKK2, DKK3-1 and SFRP-2/3/5 on {\beta}-catenin transcription complex., Comment: This paper has been withdrawn by the owner because it was submitted without consent of the co-authors
Published: 2013

47. De novo sequencing, assembly and analysis of the genome of the laboratory strain Saccharomyces cerevisiae CEN.PK113-7D, a model for modern industrial biotechnology

Author: Nijkamp, Jurgen F., Broek, Marcel van den, Datema, Erwin, Kok, Stefan de, Bosman, Lizanne, Luttik, M. Louise, Daran-Lapujade, Pascale, Vongsangnak, Wanwipa, Nielsen, Jens, Heijne, Wilbert H. M., Klaassen, Paul, Paddon, Chris J., Platt, Darren, Kötter, Peter, Ham, Roeland C. van, Reinders, Marcel J. T., Pronk, Jack T., Ridder, Dick de, Daran, Jean-Marc, Nijkamp, Jurgen F., Broek, Marcel van den, Datema, Erwin, Kok, Stefan de, Bosman, Lizanne, Luttik, M. Louise, Daran-Lapujade, Pascale, Vongsangnak, Wanwipa, Nielsen, Jens, Heijne, Wilbert H. M., Klaassen, Paul, Paddon, Chris J., Platt, Darren, Kötter, Peter, Ham, Roeland C. van, Reinders, Marcel J. T., Pronk, Jack T., Ridder, Dick de, and Daran, Jean-Marc
Abstract: Saccharomyces cerevisiae CEN.PK 113-7D is widely used for metabolic engineering and systems biology research in industry and academia. We sequenced, assembled, annotated and analyzed its genome. Single-nucleotide variations (SNV), insertions/deletions (indels) and differences in genome organization compared to the reference strain S. cerevisiae S288C were analyzed. In addition to a few large deletions and duplications, nearly 3000 indels were identified in the CEN.PK113-7D genome relative to S288C. These differences were overrepresented in genes whose functions are related to transcriptional regulation and chromatin remodelling. Some of these variations were caused by unstable tandem repeats, suggesting an innate evolvability of the corresponding genes. Besides a previously characterized mutation in adenylate cyclase, the CEN.PK113-7D genome sequence revealed a significant enrichment of non-synonymous mutations in genes encoding for components of the cAMP signalling pathway. Some phenotypic characteristics of the CEN.PK113-7D strains were explained by the presence of additional specific metabolic genes relative to S288C. In particular, the presence of the BIO1 and BIO6 genes correlated with a biotin prototrophy of CEN.PK113-7D. Furthermore, the copy number, chromosomal location and sequences of the MAL loci were resolved. The assembled sequence reveals that CEN.PK113-7D has a mosaic genome that combines characteristics of laboratory strains and wild-industrial strains.
Published: 2012

48. A Bilinear Interpolation Based Approach for Optimizing Hematoxylin and Eosin Stained Microscopical Images, Pattern Recognition in Bioinformatics

Author: Loog, Marco, Wessels, Lodewyk, Reinders, Marcel J. T., Ridder, Dick de, Kuru, Kaya, Girgin, Sertan, Loog, Marco, Wessels, Lodewyk, Reinders, Marcel J. T., Ridder, Dick de, Kuru, Kaya, and Girgin, Sertan
Abstract: Hematoxylin & Eosin (H&E) is a widely used staining technique in medical pathology for distinguishing nuclei and cytoplasm in tissues by dying them in different colors; this helps to ease the diagnosis process. However, usually the microscopic digital images obtained using this technique suffer from uneven lighting, i.e. poor Koehler illumination. The existing ad-hoc methods for correcting this problem generally work in RGB color model, and may result in both an unwanted color shift and loosing essential details in terms of the diagnosis. The aim of this study is to present an alternative method that remedies these deficiencies. We first identify the characteristics of uneven lighting in pathological images produced by using the H&E technique, and then show how the quality of these images can be improved by applying an interpolation based approach in the Lab color model without losing any important detail. The effectiveness of the proposed method is demonstrated on sample microscopic images
Published: 2011

49. A Bilinear Interpolation Based Approach for Optimizing Hematoxylin and Eosin Stained Microscopical Images, Pattern Recognition in Bioinformatics

Author: Loog, Marco, Wessels, Lodewyk, Reinders, Marcel J. T., Ridder, Dick de, Kuru, Kaya, Girgin, Sertan, Loog, Marco, Wessels, Lodewyk, Reinders, Marcel J. T., Ridder, Dick de, Kuru, Kaya, and Girgin, Sertan
Abstract: Hematoxylin & Eosin (H&E) is a widely used staining technique in medical pathology for distinguishing nuclei and cytoplasm in tissues by dying them in different colors; this helps to ease the diagnosis process. However, usually the microscopic digital images obtained using this technique suffer from uneven lighting, i.e. poor Koehler illumination. The existing ad-hoc methods for correcting this problem generally work in RGB color model, and may result in both an unwanted color shift and loosing essential details in terms of the diagnosis. The aim of this study is to present an alternative method that remedies these deficiencies. We first identify the characteristics of uneven lighting in pathological images produced by using the H&E technique, and then show how the quality of these images can be improved by applying an interpolation based approach in the Lab color model without losing any important detail. The effectiveness of the proposed method is demonstrated on sample microscopic images
Published: 2011

50. A Bilinear Interpolation Based Approach for Optimizing Hematoxylin and Eosin Stained Microscopical Images, Pattern Recognition in Bioinformatics

Author: Loog, Marco, Wessels, Lodewyk, Reinders, Marcel J. T., Ridder, Dick de, Kuru, Kaya, Girgin, Sertan, Loog, Marco, Wessels, Lodewyk, Reinders, Marcel J. T., Ridder, Dick de, Kuru, Kaya, and Girgin, Sertan
Abstract: Hematoxylin & Eosin (H&E) is a widely used staining technique in medical pathology for distinguishing nuclei and cytoplasm in tissues by dying them in different colors; this helps to ease the diagnosis process. However, usually the microscopic digital images obtained using this technique suffer from uneven lighting, i.e. poor Koehler illumination. The existing ad-hoc methods for correcting this problem generally work in RGB color model, and may result in both an unwanted color shift and loosing essential details in terms of the diagnosis. The aim of this study is to present an alternative method that remedies these deficiencies. We first identify the characteristics of uneven lighting in pathological images produced by using the H&E technique, and then show how the quality of these images can be improved by applying an interpolation based approach in the Lab color model without losing any important detail. The effectiveness of the proposed method is demonstrated on sample microscopic images
Published: 2011

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