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

1. PATE: Proximity-Aware Time series anomaly Evaluation

Author

Ghorbani, Ramin, Reinders, Marcel J. T., and Tax, David M. J.

Subjects
Computer Science - Machine Learning
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

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

Author

Ghorbani, Ramin, Reinders, Marcel J. T., and Tax, David M. J.

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence
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. Personalized Anomaly Detection in PPG Data using Representation Learning and Biometric Identification

Author

Ghorbani, Ramin, Reinders, Marcel J. T., and Tax, David M. J.

Subjects
Computer Science - Machine Learning, Electrical Engineering and Systems Science - Signal Processing
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

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

Author

Ghorbani, Ramin, Reinders, Marcel J. T., and Tax, David M. J.

Subjects
Electrical Engineering and Systems Science - Signal Processing, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
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

9. Percolate: An Exponential Family JIVE Model to Design DNA-Based Predictors of Drug Response

Author

Mourragui, Soufiane M. C., Loog, Marco, van Nee, Mirrelijn, de Wiel, Mark A van, Reinders, Marcel J. T., Wessels, Lodewyk F. A., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, and Tang, Haixu, editor

Published
2023
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10. Exome sequencing identifies rare damaging variants in ATP8B4 and ABCA1 as risk factors for Alzheimer’s disease

Author

Holstege, Henne, Hulsman, Marc, Charbonnier, Camille, Grenier-Boley, Benjamin, Quenez, Olivier, Grozeva, Detelina, van Rooij, Jeroen G. J., Sims, Rebecca, Ahmad, Shahzad, Amin, Najaf, Norsworthy, Penny J., Dols-Icardo, Oriol, Hummerich, Holger, Kawalia, Amit, Amouyel, Philippe, Beecham, Gary W., Berr, Claudine, Bis, Joshua C., Boland, Anne, Bossù, Paola, Bouwman, Femke, Bras, Jose, Campion, Dominique, Cochran, J. Nicholas, Daniele, Antonio, Dartigues, Jean-François, Debette, Stéphanie, Deleuze, Jean-François, Denning, Nicola, DeStefano, Anita L., Farrer, Lindsay A., Fernández, Maria Victoria, Fox, Nick C., Galimberti, Daniela, Genin, Emmanuelle, Gille, Johan J. P., Le Guen, Yann, Guerreiro, Rita, Haines, Jonathan L., Holmes, Clive, Ikram, M. Arfan, Ikram, M. Kamran, Jansen, Iris E., Kraaij, Robert, Lathrop, Marc, Lemstra, Afina W., Lleó, Alberto, Luckcuck, Lauren, Mannens, Marcel M. A. M., Marshall, Rachel, Martin, Eden R., Masullo, Carlo, Mayeux, Richard, Mecocci, Patrizia, Meggy, Alun, Mol, Merel O., Morgan, Kevin, Myers, Richard M., Nacmias, Benedetta, Naj, Adam C., Napolioni, Valerio, Pasquier, Florence, Pastor, Pau, Pericak-Vance, Margaret A., Raybould, Rachel, Redon, Richard, Reinders, Marcel J. T., Richard, Anne-Claire, Riedel-Heller, Steffi G., Rivadeneira, Fernando, Rousseau, Stéphane, Ryan, Natalie S., Saad, Salha, Sanchez-Juan, Pascual, Schellenberg, Gerard D., Scheltens, Philip, Schott, Jonathan M., Seripa, Davide, Seshadri, Sudha, Sie, Daoud, Sistermans, Erik A., Sorbi, Sandro, van Spaendonk, Resie, Spalletta, Gianfranco, Tesi, Niccolo’, Tijms, Betty, Uitterlinden, André G., van der Lee, Sven J., Visser, Pieter Jelle, Wagner, Michael, Wallon, David, Wang, Li-San, Zarea, Aline, Clarimon, Jordi, van Swieten, John C., Greicius, Michael D., Yokoyama, Jennifer S., Cruchaga, Carlos, Hardy, John, Ramirez, Alfredo, Mead, Simon, van der Flier, Wiesje M., van Duijn, Cornelia M., Williams, Julie, Nicolas, Gaël, Bellenguez, Céline, and Lambert, Jean-Charles

Published
2022
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12. New insights into the genetic etiology of Alzheimer’s disease and related dementias

Author

Bellenguez, Céline, Küçükali, 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, Alarcón-Martín, Emilio, Alcolea, Daniel, Alegret, Montserrat, Alvarez, Ignacio, Álvarez, Victoria, Armstrong, Nicola J., Tsolaki, Anthoula, Antúnez, Carmen, Appollonio, Ildebrando, Arcaro, Marina, Archetti, Silvana, Pastor, Alfonso Arias, Arosio, Beatrice, Athanasiu, Lavinia, Bailly, Henri, Banaj, Nerisa, Baquero, Miquel, Barral, Sandra, Beiser, Alexa, Pastor, Ana Belén, Below, Jennifer E., Benchek, Penelope, Benussi, Luisa, Berr, Claudine, Besse, Céline, Bessi, Valentina, Binetti, Giuliano, Bizarro, Alessandra, Blesa, Rafael, Boada, Mercè, Boerwinkle, Eric, Borroni, Barbara, Boschi, Silvia, Bossù, Paola, Bråthen, Geir, Bressler, Jan, Bresner, Catherine, Brodaty, Henry, Brookes, Keeley J., Brusco, Luis Ignacio, Buiza-Rueda, Dolores, Bûrger, Katharina, Burholt, Vanessa, Bush, William S., Calero, Miguel, Cantwell, Laura B., Chene, Geneviève, Chung, Jaeyoon, Cuccaro, Michael L., Carracedo, Ángel, Cecchetti, Roberta, Cervera-Carles, Laura, Charbonnier, Camille, Chen, Hung-Hsin, Chillotti, Caterina, Ciccone, Simona, Claassen, Jurgen A. H. R., Clark, Christopher, Conti, Elisa, Corma-Gómez, Anaïs, Costantini, Emanuele, Custodero, Carlo, Daian, Delphine, Dalmasso, Maria Carolina, Daniele, Antonio, Dardiotis, Efthimios, Dartigues, Jean-François, de Deyn, Peter Paul, de Paiva Lopes, Katia, de Witte, Lot D., Debette, Stéphanie, Deckert, Jürgen, del Ser, Teodoro, Denning, Nicola, DeStefano, Anita, Dichgans, Martin, Diehl-Schmid, Janine, Diez-Fairen, Mónica, Rossi, Paolo Dionigi, Djurovic, Srdjan, Duron, Emmanuelle, Düzel, 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, Fernández-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-Macías, Emlio, Bullido, María J., Frank-García, Ana, Froelich, Lutz, Fulton-Howard, Brian, Galimberti, Daniela, García-Alberca, Jose Maria, García-González, Pablo, Garcia-Madrona, Sebastian, Garcia-Ribas, Guillermo, Ghidoni, Roberta, Giegling, Ina, Giorgio, Giaccone, Goate, Alison M., Goldhardt, Oliver, Gomez-Fonseca, Duber, González-Pérez, Antonio, Graff, Caroline, Grande, Giulia, Green, Emma, Grimmer, Timo, Grünblatt, 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., Hernández, Isabel, Herrmann, Martin J., Hoffmann, Per, Holmes, Clive, Holstege, Henne, Vilas, Raquel Huerto, Hulsman, Marc, Humphrey, Jack, Biessels, Geert Jan, Jian, Xueqiu, Johansson, Charlotte, Jun, Gyungah R., Kastumata, Yuriko, Kauwe, John, Kehoe, Patrick G., Kilander, Lena, Ståhlbom, 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, Lleó, Alberto, Longstreth, Jr, William, Lopez, Oscar, de Munain, Adolfo Lopez, Love, Seth, Löwemark, Malin, Luckcuck, Lauren, Lunetta, Kathryn L., Ma, Yiyi, Macías, Juan, MacLeod, Catherine A., Maier, Wolfgang, Mangialasche, Francesca, Spallazzi, Marco, Marquié, Marta, Marshall, Rachel, Martin, Eden R., Montes, Angel Martín, Rodríguez, Carmen Martínez, Masullo, Carlo, Mayeux, Richard, Mead, Simon, Mecocci, Patrizia, Medina, Miguel, Meggy, Alun, Mehrabian, Shima, Mendoza, Silvia, Menéndez-González, Manuel, Mir, Pablo, Moebus, Susanne, Mol, Merel, Molina-Porcel, Laura, Montrreal, Laura, Morelli, Laura, Moreno, Fermin, Morgan, Kevin, Mosley, Thomas, Nöthen, Markus M., Muchnik, Carolina, Mukherjee, Shubhabrata, Nacmias, Benedetta, Ngandu, Tiia, Nicolas, Gael, Nordestgaard, Børge G., Olaso, Robert, Orellana, Adelina, Orsini, Michela, Ortega, Gemma, Padovani, Alessandro, Paolo, Caffarra, Papenberg, Goran, Parnetti, Lucilla, Pasquier, Florence, Pastor, Pau, Peloso, Gina, Pérez-Cordón, Alba, Pérez-Tur, Jordi, Pericard, Pierre, Peters, Oliver, Pijnenburg, Yolande A. L., Pineda, Juan A., Piñol-Ripoll, Gerard, Pisanu, Claudia, Polak, Thomas, Popp, Julius, Posthuma, Danielle, Priller, Josef, Puerta, Raquel, Quenez, Olivier, Quintela, Inés, Thomassen, Jesper Qvist, Rábano, 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, Allende, Irene Rosas, Rosende-Roca, Maitée, Royo, Jose Luis, Rubino, Elisa, Rujescu, Dan, Sáez, María Eugenia, Sakka, Paraskevi, Saltvedt, Ingvild, Sanabria, Ángela, Sánchez-Arjona, María Bernal, Sanchez-Garcia, Florentino, Juan, Pascual Sánchez, Sánchez-Valle, Raquel, Sando, Sigrid B., Sarnowski, Chloé, Satizabal, Claudia L., Scamosci, Michela, Scarmeas, Nikolaos, Scarpini, Elio, Scheltens, Philip, Scherbaum, Norbert, Scherer, Martin, Schmid, Matthias, Schneider, Anja, Schott, Jonathan M., Selbæk, 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, Tartan, Juan Pablo, Tárraga, Lluís, Tesí, Niccolo, Thalamuthu, Anbupalam, Thomas, Tegos, Tosto, Giuseppe, Traykov, Latchezar, Tremolizzo, Lucio, Tybjærg-Hansen, Anne, Uitterlinden, Andre, Ullgren, Abbe, Ulstein, Ingun, Valero, Sergi, Valladares, Otto, Broeckhoven, Christine Van, Vance, Jeffery, Vardarajan, Badri N., van der Lugt, Aad, Dongen, Jasper Van, van Rooij, Jeroen, van Swieten, John, Vandenberghe, Rik, Verhey, Frans, Vidal, Jean-Sébastien, 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 Mendonça, Alexandre, Hort, Jakub, Tsolaki, Magda, Pericak-Vance, Margaret A., Amouyel, Philippe, Williams, Julie, Frikke-Schmidt, Ruth, Clarimon, Jordi, Deleuze, Jean-François, 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, Agustín, Ramirez, Alfredo, and Lambert, Jean-Charles

Published
2022
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13. 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., and Reinders, Marcel J. T.

Published
2022
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16. 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

18. TREM2 Burden associates solely with Alzheimer’s Disease, and decreases the Chance to become a Centenarian

Author

Dijkstra, Janna I.R., primary, Vermunt, Lisa, additional, Biessels, Geert Jan, additional, Braber, Anouk, additional, Claassen, Jurgen A.H.R., additional, De Deyn, Peter Paul, additional, Ghanbari, Mohsen, additional, Huisman, Martijn, additional, Hulsman, Marc, additional, Ramakers, Inez H.G.B., additional, Reinders, Marcel J. T., additional, Seelaar, Harro, additional, Tesi, Niccoló, additional, Visser, Pieter Jelle, additional, van der Flier, Wiesje M., additional, Teunissen, Charlotte E., additional, Holstege, Henne, additional, and Van Der Lee, Sven J, additional

Published
2023
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22. Machine learning–based biomarker profile derived from 4210 serially measured proteins predicts clinical outcome of patients with heart failure

Author

de Bakker, Marie, primary, Petersen, Teun B, additional, Rueten-Budde, Anja J, additional, Akkerhuis, K Martijn, additional, Umans, Victor A, additional, Brugts, Jasper J, additional, Germans, Tjeerd, additional, Reinders, Marcel J T, additional, Katsikis, Peter D, additional, van der Spek, Peter J, additional, Ostroff, Rachel, additional, She, Ruicong, additional, Lanfear, David, additional, Asselbergs, Folkert W, additional, Boersma, Eric, additional, Rizopoulos, Dimitris, additional, and Kardys, Isabella, additional

Published
2023
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23. Epigenetic and Metabolomic Biomarkers for Biological Age: A Comparative Analysis of Mortality and Frailty Risk

Author

Kuiper, Lieke M, primary, Polinder-Bos, Harmke A, additional, Bizzarri, Daniele, additional, Vojinovic, Dina, additional, Vallerga, Costanza L, additional, Beekman, Marian, additional, Dollé, Martijn E T, additional, Ghanbari, Mohsen, additional, Voortman, Trudy, additional, Reinders, Marcel J T, additional, Verschuren, W M Monique, additional, Slagboom, P Eline, additional, van den Akker, Erik B, additional, and van Meurs, Joyce B J, additional

Published
2023
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26. 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

27. 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

28. 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

29. Technical Report: A Comprehensive Comparison between Different Quantification Versions of Nightingale Health's 1 H-NMR Metabolomics Platform.

Author

Bizzarri, Daniele, Reinders, Marcel J. T., Beekman, Marian, Slagboom, P. Eline, and van den Akker, Erik B.

Subjects
TECHNICAL reports, METABOLOMICS, NIGHTINGALE, RANK correlation (Statistics), FATTY acids
Abstract

1H-NMR metabolomics data is increasingly used to track health and disease. Nightingale Health, a major supplier of 1H-NMR metabolomics, has recently updated the quantification strategy to further align with clinical standards. Such updates, however, might influence backward replicability, particularly affecting studies with repeated measures. Using data from BBMRI-NL consortium (~28,000 samples from 28 cohorts), we compared Nightingale data, originally released in 2014 and 2016, with a re-quantified version released in 2020, of which both versions were based on the same NMR spectra. Apart from two discontinued and twenty-three new analytes, we generally observe a high concordance between quantification versions with 73 out of 222 (33%) analytes showing a mean ρ > 0.9 across all cohorts. Conversely, five analytes consistently showed lower Spearman's correlations ( ρ < 0.7) between versions, namely acetoacetate, LDL-L, saturated fatty acids, S-HDL-C, and sphingomyelins. Furthermore, previously trained multi-analyte scores, such as MetaboAge or MetaboHealth, might be particularly sensitive to platform changes. Whereas MetaboHealth replicated well, the MetaboAge score had to be retrained due to use of discontinued analytes. Notably, both scores in the re-quantified data recapitulated mortality associations observed previously. Concluding, we urge caution in utilizing different platform versions to avoid mixing analytes, having different units, or simply being discontinued. [ABSTRACT FROM AUTHOR]

Published
2023
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30. The correlation between neuropathology levels and cognitive performance in centenarians

Author

Zhang, Meng, primary, Ganz, Andrea B., additional, Rohde, Susan, additional, Lorenz, Linda, additional, Rozemuller, Annemieke J. M., additional, van Vliet, Kimberley, additional, Graat, Marieke, additional, Sikkes, Sietske A. M., additional, Reinders, Marcel J. T., additional, Scheltens, Philip, additional, Hulsman, Marc, additional, Hoozemans, Jeroen J. M., additional, and Holstege, Henne, additional

Published
2023
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31. Machine learning-based somatic variant calling in cell-free DNA of metastatic breast cancer patients using large NGS panels

Author

Jongbloed, Elisabeth M., primary, Jansen, Maurice P.H.M., additional, de Weerd, Vanja, additional, Helmijr, Jean A., additional, Beaufort, Corine M., additional, Reinders, Marcel J. T., additional, Marion, Ronald van, additional, IJcken, Wilfred F. J. van, additional, Sonke, Gabe S., additional, Konings, Inge R. H. M., additional, Jager, Agnes, additional, Martens, John W.M., additional, Wilting, Saskia M., additional, and Makrodimitris, Stavros, additional

Published
2023
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33. PLIS: A metabolomic response monitor to a lifestyle intervention study in older adults

Author

Bogaards, Fatih A., Gehrmann, Thies, Beekman, Marian, van den Akker, Erik Ben, van de Rest, Ondine, Hangelbroek, Roland W. J., Noordam, Raymond, Mooijaart, Simon P., de Groot, Lisette C. P. G. M., Reinders, Marcel J. T., and Slagboom, P. Eline

Subjects
Male, Nutrition and Disease, Biochemistry, Voeding, Metabolisme en Genomica, Voeding, Voeding en Ziekte, OT BVG/MNH/MDS, Genetics, Humans, Insulin, Life Science, Obesity, Life Style, Molecular Biology, Aged, Nutrition, VLAG, Cholesterol, HDL, lifestyle intervention, bioinformatics, response monitor, metabolomics, Metabolism and Genomics, Nutritional Biology, machine learning, Metabolisme en Genomica, Female, Nutrition, Metabolism and Genomics, healthy ageing, Biomarkers, Biotechnology
Abstract

The response to lifestyle intervention studies is often heterogeneous, especially in older adults. Subtle responses that may represent a health gain for individuals are not always detected by classical health variables, stressing the need for novel biomarkers that detect intermediate changes in metabolic, inflammatory, and immunity-related health. Here, our aim was to develop and validate a molecular multivariate biomarker maximally sensitive to the individual effect of a lifestyle intervention; the Personalized Lifestyle Intervention Status (PLIS). We used 1 H-NMR fasting blood metabolite measurements from before and after the 13-week combined physical and nutritional Growing Old TOgether (GOTO) lifestyle intervention study in combination with a fivefold cross-validation and a bootstrapping method to train a separate PLIS score for men and women. The PLIS scores consisted of 14 and four metabolites for females and males, respectively. Performance of the PLIS score in tracking health gain was illustrated by association of the sex-specific PLIS scores with several classical metabolic health markers, such as BMI, trunk fat%, fasting HDL cholesterol, and fasting insulin, the primary outcome of the GOTO study. We also showed that the baseline PLIS score indicated which participants respond positively to the intervention. Finally, we explored PLIS in an independent physical activity lifestyle intervention study, showing similar, albeit remarkably weaker, associations of PLIS with classical metabolic health markers. To conclude, we found that the sex-specific PLIS score was able to track the individual short-term metabolic health gain of the GOTO lifestyle intervention study. The methodology used to train the PLIS score potentially provides a useful instrument to track personal responses and predict the participant's health benefit in lifestyle interventions similar to the GOTO study.

Published
2022

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

Author

Cordes, Martijn, primary, Canté-Barrett, Kirsten, additional, van den Akker, Erik B., additional, Moretti, Federico A., additional, Kiełbasa, Szymon M., additional, Vloemans, Sandra A., additional, Garcia-Perez, Laura, additional, Teodosio, Cristina, additional, van Dongen, Jacques J. M., additional, Pike-Overzet, Karin, additional, Reinders, Marcel J. T., additional, and Staal, Frank J. T., additional

Published
2022
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37. 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

38. 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

39. A framework for employing longitudinally collected multicenter electronic health records to stratify heterogeneous patient populations on disease history

Author

Maurits, Marc P, primary, Korsunsky, Ilya, additional, Raychaudhuri, Soumya, additional, Murphy, Shawn N, additional, Smoller, Jordan W, additional, Weiss, Scott T, additional, Petukhova, Lynn M, additional, Weng, Chunhua, additional, Wei, Wei-Qi, additional, Huizinga, Thomas W J, additional, Reinders, Marcel J T, additional, Karlson, Elizabeth W, additional, van den Akker, Erik B, additional, and Knevel, Rachel, additional

Published
2022
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40. Additional file 1 of 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., and Reinders, Marcel J. T.

Abstract

Additional file 1. Appendices.

Published
2022
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42. Effect of Phenotype and Genotype on the Plasma Proteome in Patients with Inflammatory Bowel Disease.

Author

Bourgonje, Arno R, Hu, Shixian, Spekhorst, Lieke M, Zhernakova, Daria V, Vila, Arnau Vich, Li, Yanni, Voskuil, Michiel D, Berkel, Lisette A van, Folly, Brenda Bley, Charrout, Mohammed, Mahfouz, Ahmed, Reinders, Marcel J T, Heck, Julia I P van, Joosten, Leo A B, Visschedijk, Marijn C, Dullemen, Hendrik M van, Faber, Klaas Nico, Samsom, Janneke N, Festen, Eleonora A M, and Dijkstra, Gerard

Abstract

Background and Aims Protein profiling in patients with inflammatory bowel diseases [IBD] for diagnostic and therapeutic purposes is underexplored. This study analysed the association between phenotype, genotype, and the plasma proteome in IBD. Methods A total of 92 inflammation-related proteins were quantified in plasma of 1028 patients with IBD (567 Crohn's disease [CD]; 461 ulcerative colitis [UC]) and 148 healthy individuals to assess protein-phenotype associations. Corresponding whole-exome sequencing and global screening array data of 919 patients with IBD were included to analyse the effect of genetics on protein levels (protein quantitative trait loci [pQTL] analysis). Intestinal mucosal RNA sequencing and faecal metagenomic data were used for complementary analyses. Results Thirty-two proteins were differentially abundant between IBD and healthy individuals, of which 22 proteins were independent of active inflammation; 69 proteins were associated with 15 demographic and clinical factors. Fibroblast growth factor-19 levels were decreased in CD patients with ileal disease or a history of ileocecal resection. Thirteen novel cis -pQTLs were identified and 10 replicated from previous studies. One trans -pQTL of the fucosyltransferase 2 [ FUT2 ] gene [rs602662] and two independent cis -pQTLs of C-C motif chemokine 25 [ CCL25 ] affected plasma CCL25 levels. Intestinal gene expression data revealed an overlapping cis -expression [e]QTL-variant [rs3745387] of the CCL25 gene. The FUT2 rs602662 trans -pQTL was associated with reduced abundances of faecal butyrate-producing bacteria. Conclusions This study shows that genotype and multiple disease phenotypes strongly associate with the plasma inflammatory proteome in IBD, and identifies disease-associated pathways that may help to improve disease management in the future. [ABSTRACT FROM AUTHOR]

Published
2022
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43. Exome sequencing identifies rare damaging variants in ATP8B4and ABCA1as risk factors for Alzheimer’s disease

Author

Holstege, Henne, Hulsman, Marc, Charbonnier, Camille, Grenier-Boley, Benjamin, Quenez, Olivier, Grozeva, Detelina, van Rooij, Jeroen G. J., Sims, Rebecca, Ahmad, Shahzad, Amin, Najaf, Norsworthy, Penny J., Dols-Icardo, Oriol, Hummerich, Holger, Kawalia, Amit, Amouyel, Philippe, Beecham, Gary W., Berr, Claudine, Bis, Joshua C., Boland, Anne, Bossù, Paola, Bouwman, Femke, Bras, Jose, Campion, Dominique, Cochran, J. Nicholas, Daniele, Antonio, Dartigues, Jean-François, Debette, Stéphanie, Deleuze, Jean-François, Denning, Nicola, DeStefano, Anita L., Farrer, Lindsay A., Fernández, Maria Victoria, Fox, Nick C., Galimberti, Daniela, Genin, Emmanuelle, Gille, Johan J. P., Le Guen, Yann, Guerreiro, Rita, Haines, Jonathan L., Holmes, Clive, Ikram, M. Arfan, Ikram, M. Kamran, Jansen, Iris E., Kraaij, Robert, Lathrop, Marc, Lemstra, Afina W., Lleó, Alberto, Luckcuck, Lauren, Mannens, Marcel M. A. M., Marshall, Rachel, Martin, Eden R., Masullo, Carlo, Mayeux, Richard, Mecocci, Patrizia, Meggy, Alun, Mol, Merel O., Morgan, Kevin, Myers, Richard M., Nacmias, Benedetta, Naj, Adam C., Napolioni, Valerio, Pasquier, Florence, Pastor, Pau, Pericak-Vance, Margaret A., Raybould, Rachel, Redon, Richard, Reinders, Marcel J. T., Richard, Anne-Claire, Riedel-Heller, Steffi G., Rivadeneira, Fernando, Rousseau, Stéphane, Ryan, Natalie S., Saad, Salha, Sanchez-Juan, Pascual, Schellenberg, Gerard D., Scheltens, Philip, Schott, Jonathan M., Seripa, Davide, Seshadri, Sudha, Sie, Daoud, Sistermans, Erik A., Sorbi, Sandro, van Spaendonk, Resie, Spalletta, Gianfranco, Tesi, Niccolo’, Tijms, Betty, Uitterlinden, André G., van der Lee, Sven J., Visser, Pieter Jelle, Wagner, Michael, Wallon, David, Wang, Li-San, Zarea, Aline, Clarimon, Jordi, van Swieten, John C., Greicius, Michael D., Yokoyama, Jennifer S., Cruchaga, Carlos, Hardy, John, Ramirez, Alfredo, Mead, Simon, van der Flier, Wiesje M., van Duijn, Cornelia M., Williams, Julie, Nicolas, Gaël, Bellenguez, Céline, and Lambert, Jean-Charles

Abstract

Alzheimer’s disease (AD), the leading cause of dementia, has an estimated heritability of approximately 70%1. The genetic component of AD has been mainly assessed using genome-wide association studies, which do not capture the risk contributed by rare variants2. Here, we compared the gene-based burden of rare damaging variants in exome sequencing data from 32,558 individuals—16,036 AD cases and 16,522 controls. Next to variants in TREM2, SORL1and ABCA7, we observed a significant association of rare, predicted damaging variants in ATP8B4and ABCA1with AD risk, and a suggestive signal in ADAM10. Additionally, the rare-variant burden in RIN3, CLU, ZCWPW1and ACEhighlighted these genes as potential drivers of respective AD-genome-wide association study loci. Variants associated with the strongest effect on AD risk, in particular loss-of-function variants, are enriched in early-onset AD cases. Our results provide additional evidence for a major role for amyloid-β precursor protein processing, amyloid-β aggregation, lipid metabolism and microglial function in AD.

Published
2022
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44. Combined plasma protein and memory T cell profiling discern IBD-patient-immunotypes related to intestinal disease and treatment outcomes.

Author

Heredia M, Charrout M, Klomberg RCW, Aardoom MA, Jongsma MME, Kemos P, Hulleman-van Haaften DH, Tuk B, van Berkel LA, Bley Folly B, Calado B, Nugteren S, Simons-Oosterhuis Y, Doukas M, Sanders MA, van Beek G, Ruemmele FM, Croft NM, Mahfouz A, Reinders MJT, Escher JC, de Ridder L, and Samsom JN

Abstract

Inflammatory bowel disease (IBD) chronicity results from memory T helper cell (Tmem) reactivation. Identifying patient-specific immunotypes is crucial for tailored treatment. We conducted a comprehensive study integrating circulating immune proteins and circulating Tmem, with intestinal tissue histology and mRNA analysis, in therapy-naïve pediatric IBD (Crohn's disease, CD: n = 62; ulcerative colitis, UC: n = 20; age-matched controls n = 43), and after 10-12 weeks' induction therapy. At diagnosis, plasma protein profiles unveiled two UC and three CD clusters with distinct disease courses. UC patients displayed unchanged circulating Tmem, while CD exhibited increased frequencies of gut-homing ex-Th17, known for high IFN-γ production. UC#2 had elevated Th17/neutrophil-pathway-related proteins and severe disease, with higher endoscopic and histological damage and Th17/neutrophil infiltration. Although both UC#1 and UC#2 responded to therapy, UC#2 required earlier immunomodulation. CD#3 had lower plasma protein concentrations, especially IFN-γ pathway proteins, fewer gut-homing ex-Th17 and clinically milder disease, confirmed by intestinal gene expression. CD#1 and CD#2 had comparably high Th1-related immune profiles, but CD#1 exhibited higher concentrations of proteins previously associated with poorer prognosis. Both CD clusters responded to induction therapy, with similar one-year outcomes. This study highlights feasibility of discriminating patient-specific immunotypes in IBD, advancing our understanding of immune pathogenesis, needed for tailored treatment strategies., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Published
2024
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45. gsQTL: Associating genetic risk variants with gene sets by exploiting their shared variability.

Author

Bouland GA, Tesi N, Mahfouz A, and Reinders MJT

Abstract

To investigate the functional significance of genetic risk loci identified through genome-wide association studies (GWASs), genetic loci are linked to genes based on their capacity to account for variation in gene expression, resulting in expression quantitative trait loci (eQTL). Following this, gene set analyses are commonly used to gain insights into functionality. However, the efficacy of this approach is hampered by small effect sizes and the burden of multiple testing. We propose an alternative approach: instead of examining the cumulative associations of individual genes within a gene set, we consider the collective variation of the entire gene set. We introduce the concept of gene set QTL (gsQTL), and show it to be more adept at identifying links between genetic risk variants and specific gene sets. Notably, gsQTL experiences less susceptibility to inflation or deflation of significant enrichments compared with conventional methods. Furthermore, we demonstrate the broader applicability of shared variability within gene sets. This is evident in scenarios such as the coordinated regulation of genes by a transcription factor or coordinated differential expression.

Published
2024
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46. NMR metabolomics-guided DNA methylation mortality predictors.

Author

Bizzarri D, Reinders MJT, Kuiper L, Beekman M, Deelen J, van Meurs JBJ, van Dongen J, Pool R, Boomsma DI, Ghanbari M, Franke L, Slagboom PE, and van den Akker EB

Subjects
Humans, Male, Female, Aged, Mortality, Metabolome, Middle Aged, Magnetic Resonance Spectroscopy methods, Aged, 80 and over, DNA Methylation, Metabolomics methods, Biomarkers
Abstract

Background: 1 H-NMR metabolomics and DNA methylation in blood are widely known biomarkers predicting age-related physiological decline and mortality yet exert mutually independent mortality and frailty signals., Methods: Leveraging multi-omics data in four Dutch population studies (N = 5238, ∼40% of which male) we investigated whether the mortality signal captured by 1 H-NMR metabolomics could guide the construction of DNA methylation-based mortality predictors., Findings: We trained DNA methylation-based surrogates for 64 metabolomic analytes and found that analytes marking inflammation, fluid balance, or HDL/VLDL metabolism could be accurately reconstructed using DNA-methylation assays. Interestingly, a previously reported multi-analyte score indicating mortality risk (MetaboHealth) could also be accurately reconstructed. Sixteen of our derived surrogates, including the MetaboHealth surrogate, showed significant associations with mortality, independent of relevant covariates., Interpretation: The addition of our metabolic analyte-derived surrogates to the well-established epigenetic clock GrimAge demonstrates that our surrogates potentially represent valuable mortality signal., Funding: BBMRI-NL, X-omics, VOILA, Medical Delta, NWO, ERC., Competing Interests: Declaration of interests Authors declare no competing interests., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Published
2024
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47. Machine learning-based biomarker profile derived from 4210 serially measured proteins predicts clinical outcome of patients with heart failure.

Author

de Bakker M, Petersen TB, Rueten-Budde AJ, Akkerhuis KM, Umans VA, Brugts JJ, Germans T, Reinders MJT, Katsikis PD, van der Spek PJ, Ostroff R, She R, Lanfear D, Asselbergs FW, Boersma E, Rizopoulos D, and Kardys I

Abstract

Aims: Risk assessment tools are needed for timely identification of patients with heart failure (HF) with reduced ejection fraction (HFrEF) who are at high risk of adverse events. In this study, we aim to derive a small set out of 4210 repeatedly measured proteins, which, along with clinical characteristics and established biomarkers, carry optimal prognostic capacity for adverse events, in patients with HFrEF., Methods and Results: In 382 patients, we performed repeated blood sampling (median follow-up: 2.1 years) and applied an aptamer-based multiplex proteomic approach. We used machine learning to select the optimal set of predictors for the primary endpoint (PEP: composite of cardiovascular death, heart transplantation, left ventricular assist device implantation, and HF hospitalization). The association between repeated measures of selected proteins and PEP was investigated by multivariable joint models. Internal validation (cross-validated c -index) and external validation (Henry Ford HF PharmacoGenomic Registry cohort) were performed. Nine proteins were selected in addition to the MAGGIC risk score, N-terminal pro-hormone B-type natriuretic peptide, and troponin T: suppression of tumourigenicity 2, tryptophanyl-tRNA synthetase cytoplasmic, histone H2A Type 3, angiotensinogen, deltex-1, thrombospondin-4, ADAMTS-like protein 2, anthrax toxin receptor 1, and cathepsin D. N-terminal pro-hormone B-type natriuretic peptide and angiotensinogen showed the strongest associations [hazard ratio (95% confidence interval): 1.96 (1.17-3.40) and 0.66 (0.49-0.88), respectively]. The multivariable model yielded a c -index of 0.85 upon internal validation and c -indices up to 0.80 upon external validation. The c -index was higher than that of a model containing established risk factors ( P = 0.021)., Conclusion: Nine serially measured proteins captured the most essential prognostic information for the occurrence of adverse events in patients with HFrEF, and provided incremental value for HF prognostication beyond established risk factors. These proteins could be used for dynamic, individual risk assessment in a prospective setting. These findings also illustrate the potential value of relatively 'novel' biomarkers for prognostication., Clinical Trial Registration: https://clinicaltrials.gov/ct2/show/NCT01851538?term=nCT01851538&draw=2&rank=1 24., Competing Interests: Conflict of interest: R.O. is employed by Somalogic Inc. D.L. reports non-financial support from Somalogic Inc., during the conduct of the study; grants and personal fees from Janssen, personal fees from Ortho Diagnostics, personal fees from DCRI (Novartis), grants from Bayer, grants from Astra Zeneca, grants from Critical Diagnostics, non-financial support from Somalogic, grants from Lilly, personal fees from ACI (Abbott Laboratories), personal fees from Martin Pharmaceuticals, personal fees from Illumina, personal fees from Vicardia, other from Hridaya, grants and personal fees from Amgen, personal fees from Cytokinetics, outside the submitted work. In addition, D.L. has a patent genomic predictors of BB response issued. The other authors have no disclosures to report., (© The Author(s) 2023. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Published
2023
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48. Resilience and resistance to the accumulation of amyloid plaques and neurofibrillary tangles in centenarians: An age-continuous perspective.

Author

Zhang M, Ganz AB, Rohde S, Rozemuller AJM, Bank NB, Reinders MJT, Scheltens P, Hulsman M, Hoozemans JJM, and Holstege H

Subjects
Aged, 80 and over, Humans, Aged, Adolescent, Young Adult, Adult, Middle Aged, Plaque, Amyloid pathology, Centenarians, Brain pathology, Neurofibrillary Tangles pathology, Alzheimer Disease pathology
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., (© 2022 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Published
2023
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49. Single-cell RNA sequencing data reveals rewiring of transcriptional relationships in Alzheimer's Disease associated with risk variants.

Author

Bouland GA, Marinus KI, van Kesteren RE, Smit AB, Mahfouz A, and Reinders MJT

Abstract

Understanding how genetic risk variants contribute to Alzheimer's Disease etiology remains a challenge. Single-cell RNA sequencing (scRNAseq) allows for the investigation of cell type specific effects of genomic risk loci on gene expression. Using seven scRNAseq datasets totalling >1.3 million cells, we investigated differential correlation of genes between healthy individuals and individuals diagnosed with Alzheimer's Disease. Using the number of differential correlations of a gene to estimate its involvement and potential impact, we present a prioritization scheme for identifying probable causal genes near genomic risk loci. Besides prioritizing genes, our approach pin-points specific cell types and provides insight into the rewiring of gene-gene relationships associated with Alzheimer's.

Published
2023
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50. Identifying Aging and Alzheimer Disease-Associated Somatic Variations in Excitatory Neurons From the Human Frontal Cortex.

Author

Zhang M, Bouland GA, Holstege H, and Reinders MJT

Abstract

Background and Objectives: With age, somatic mutations accumulated in human brain cells can lead to various neurologic disorders and brain tumors. Because the incidence rate of Alzheimer disease (AD) increases exponentially with age, investigating the association between AD and the accumulation of somatic mutation can help understand the etiology of AD., Methods: We designed a somatic mutation detection workflow by contrasting genotypes derived from whole-genome sequencing (WGS) data with genotypes derived from scRNA-seq data and applied this workflow to 76 participants from the Religious Order Study and the Rush Memory and Aging Project (ROSMAP) cohort. We focused only on excitatory neurons, the dominant cell type in the scRNA-seq data., Results: We identified 196 sites that harbored at least 1 individual with an excitatory neuron-specific somatic mutation (ENSM), and these 196 sites were mapped to 127 genes. The single base substitution (SBS) pattern of the putative ENSMs was best explained by signature SBS5 from the Catalogue of Somatic Mutations in Cancer (COSMIC) mutational signatures, a clock-like pattern correlating with the age of the individual. The count of ENSMs per individual also showed an increasing trend with age. Among the mutated sites, we found 2 sites tend to have more mutations in older individuals (16:6899517 [ RBFOX1 ], p = 0.04; 4:21788463 [ KCNIP4 ], p < 0.05). In addition, 2 sites were found to have a higher odds ratio to detect a somatic mutation in AD samples (6:73374221 [ KCNQ5 ], p = 0.01 and 13:36667102 [ DCLK1 ], p = 0.02). Thirty-two genes that harbor somatic mutations unique to AD and the KCNQ5 and DCLK1 genes were used for gene ontology (GO)-term enrichment analysis. We found the AD-specific ENSMs enriched in the GO-term "vocalization behavior" and "intraspecies interaction between organisms." Of interest we observed both age-specific and AD-specific ENSMs enriched in the K + channel-associated genes., Discussion: Our results show that combining scRNA-seq and WGS data can successfully detect putative somatic mutations. The putative somatic mutations detected from ROSMAP data set have provided new insights into the association of AD and aging with brain somatic mutagenesis., Competing Interests: The authors report no disclosures relevant to the manuscript. Full disclosure form information provided by the authors is available with the full text of this article at Neurology.org/NG., (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.)

Published
2023
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