64 results on '"Ibanez, L."'
Search Results
2. Trastornos de tics e impulso premonitorio: validación de la versión española de la «Escala para el Impulso Premonitorio al Tic» en niños y adolescentes
- Author
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Forcadell, E., Garcia-Delgar, B., Nicolau, R., Pérez-Vigil, A., Cordovilla, C., Lázaro, L., Ibáñez, L., Mir, P., Madruga-Garrido, M., Correa-Vela, M., and Morer, A.
- Published
- 2023
- Full Text
- View/download PDF
3. Can we correct first metatarsal rotation and sesamoid position with the 3D Lapidus procedure?
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Ferreyra, M., Viladot Pericé, R., Nuñez-Samper, M., Ibáñez, L., Ibarra, M., and Vilá-Rico, J.
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- 2022
- Full Text
- View/download PDF
4. A bit thick: Hidden risks in thickening products’ labelling for dysphagia treatment
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Bolivar-Prados, M., Tomsen, N., Arenas, C., Ibáñez, L., and Clave, P.
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- 2022
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5. COVID-19 pandemic: Impact on the rate of viral conjunctivitis
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Conde Bachiller, Y., Puente Gete, B., Gil Ibáñez, L., Esquivel Benito, G., Asencio Duran, M., and Dabad Moreno, J.V.
- Published
- 2022
- Full Text
- View/download PDF
6. Pandemia COVID-19: impacto sobre la tasa de conjuntivitis virales
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Conde Bachiller, Y., Puente Gete, B., Gil Ibáñez, L., Esquivel Benito, G., Asencio Duran, M., and Dabad Moreno, J.V.
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- 2022
- Full Text
- View/download PDF
7. Current clinical practice patterns with robotic salvage radical prostatectomy: Oncological results from 10 high-volume robotic centers
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Wenzel, M., primary, Di Maida, F., additional, Gomez Rivas, J., additional, Ibanez, L., additional, Bravi, C.A., additional, De Groote, R., additional, Piramide, F., additional, Turri, F., additional, Kowalczyk, K., additional, Würnschimmel, C., additional, Sharma, G., additional, Andras, I., additional, Lambert, E., additional, Liakos, N., additional, Darlington, D., additional, Paciotti, M., additional, Sorce, G., additional, Galfano, A., additional, Dell’Oglio, P., additional, Mottrie, A., additional, Patel, V., additional, Chun, F., additional, Moschovas, M.C., additional, and Larcher, A., additional
- Published
- 2024
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- View/download PDF
8. Targeted co-expression networks for the study of traits.
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Gómez-Pascual, A., Rocamora-Pérez, G., Ibanez, L., and Botía, J. A.
- Subjects
GENE regulatory networks ,GENE expression ,ALZHEIMER'S disease ,MONASTICISM & religious orders ,AGE factors in memory - Abstract
Weighted Gene Co-expression Network Analysis (WGCNA) is a widely used approach for the generation of gene co-expression networks. However, networks generated with this tool usually create large modules with a large set of functional annotations hard to decipher. We have developed TGCN, a new method to create Targeted Gene Co-expression Networks. This method identifies the transcripts that best predict the trait of interest based on gene expression using a refinement of the LASSO regression. Then, it builds the co-expression modules around those transcripts. Algorithm properties were characterized using the expression of 13 brain regions from the Genotype-Tissue Expression project. When comparing our method with WGCNA, TGCN networks lead to more precise modules that have more specific and yet rich biological meaning. Then, we illustrate its applicability by creating an APP-TGCN on The Religious Orders Study and Memory and Aging Project dataset, aiming to identify the molecular pathways specifically associated with APP role in Alzheimer's disease. Main biological findings were further validated in two independent cohorts. In conclusion, we provide a new framework that serves to create targeted networks that are smaller, biologically relevant and useful in high throughput hypothesis driven research. The TGCN R package is available on Github: https://github.com/aliciagp/TGCN. [ABSTRACT FROM AUTHOR]
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- 2024
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- View/download PDF
9. Analysis of clinical characteristics in metastatic hormone-sensitive prostate cancer: Bridging the gap between randomized controlled trials and real-world data
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Gómez Rivas, J., primary, Nicoletti, R., additional, Ibanez, L., additional, Golozar, A., additional, Steinbeißer, C., additional, De Meulder, B., additional, Snijder, R., additional, Axelsson, S.E., additional, Ayman, H., additional, Feng, Q., additional, Bjartell, A., additional, Cornford, P., additional, Murtola, T., additional, Willemse, P.P., additional, Prinsen, P., additional, and N dow, J., additional
- Published
- 2023
- Full Text
- View/download PDF
10. New insights into the genetic etiology of Alzheimer's disease and related dementias
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Bellenguez, C., Küçükali, F., Jansen, I. E., Kleineidam, L., Moreno-Grau, S., Amin, N., Naj, A. C., Campos-Martin, R., Grenier-Boley, B., Andrade, V., Holmans, P. A., Boland, A., Damotte, V., van der Lee, S. J., Costa, M. R., Kuulasmaa, T., Yang, Q., de Rojas, I., Bis, J. C., Yaqub, A., Prokic, I., Chapuis, J., Ahmad, S., Giedraitis, V., Aarsland, D., Garcia-Gonzalez, P., Abdelnour, C., Alarcón-Martín, E., Alcolea, D., Alegret, M., Alvarez, I., Álvarez, V., Armstrong, N. J., Tsolaki, A., Antúnez, C., Appollonio, I., Arcaro, M., Archetti, S., Pastor, A. A., Arosio, B., Athanasiu, L., Bailly, H., Banaj, N., Baquero, M., Barral, S., Beiser, A., Pastor, A. B., Below, J. E., Benchek, P., Benussi, L., Berr, C., Besse, C., Bessi, V., Binetti, G., Bizarro, A., Blesa, R., Boada, M., Boerwinkle, E., Borroni, B., Boschi, S., Bossù, P., Bråthen, G., Bressler, J., Bresner, C., Brodaty, H., Brookes, K. J., Brusco, L. I., Buiza-Rueda, D., Bûrger, K., Burholt, V., Bush, W. S., Calero, M., Cantwell, L. B., Chene, G., Chung, J., Cuccaro, M. L., Carracedo, Á., Cecchetti, R., Cervera-Carles, L., Charbonnier, C., Chen, H. -H., Chillotti, C., Ciccone, S., Claassen, J. A. H. R., Clark, C., Conti, E., Corma-Gómez, A., Costantini, E., Custodero, C., Daian, D., Dalmasso, M. C., Daniele, A., Dardiotis, E., Dartigues, J. -F., de Deyn, P. P., de Paiva Lopes, K., de Witte, L. D., Debette, S., Deckert, J., del Ser, T., Denning, N., Destefano, A., Dichgans, M., Diehl-Schmid, J., Diez-Fairen, M., Rossi, P. D., Djurovic, S., Duron, E., Düzel, E., Dufouil, C., Eiriksdottir, G., Engelborghs, S., Escott-Price, V., Espinosa, A., Ewers, M., Faber, K. M., Fabrizio, T., Nielsen, S. F., Fardo, D. W., Farotti, L., Fenoglio, C., Fernández-Fuertes, M., Ferrari, R., Ferreira, C. B., Ferri, E., Fin, B., Fischer, P., Fladby, T., Fließbach, K., Fongang, B., Fornage, M., Fortea, J., Foroud, T. M., Fostinelli, S., Fox, N. C., Franco-Macías, E., Bullido, M. J., Frank-García, A., Froelich, L., Fulton-Howard, B., Galimberti, D., García-Alberca, J. M., García-González, P., Garcia-Madrona, S., Garcia-Ribas, G., Ghidoni, R., Giegling, I., Giorgio, G., Goate, A. M., Goldhardt, O., Gomez-Fonseca, D., González-Pérez, A., Graff, C., Grande, G., Green, E., Grimmer, T., Grünblatt, E., Grunin, M., Gudnason, V., Guetta-Baranes, T., Haapasalo, A., Hadjigeorgiou, G., Haines, J. L., Hamilton-Nelson, K. L., Hampel, H., Hanon, O., Hardy, J., Hartmann, A. M., Hausner, L., Harwood, J., Heilmann-Heimbach, S., Helisalmi, S., Heneka, M. T., Hernández, I., Herrmann, M. J., Hoffmann, P., Holmes, C., Holstege, H., Vilas, R. H., Hulsman, M., Humphrey, J., Biessels, G. J., Jian, X., Johansson, C., Jun, G. R., Kastumata, Y., Kauwe, J., Kehoe, P. G., Kilander, L., Ståhlbom, A. K., Kivipelto, M., Koivisto, A., Kornhuber, J., Kosmidis, M. H., Kukull, W. A., Kuksa, P. P., Kunkle, B. W., Kuzma, A. B., Lage, C., Laukka, E. J., Launer, L., Lauria, A., Lee, C. -Y., Lehtisalo, J., Lerch, O., Lleó, A., Longstreth, W., Lopez, O., de Munain, A. L., Love, S., Löwemark, M., Luckcuck, L., Lunetta, K. L., Ma, Y., Macías, J., Macleod, C. A., Maier, W., Mangialasche, F., Spallazzi, M., Marquié, M., Marshall, R., Martin, E. R., Montes, A. M., Rodríguez, C. M., Masullo, C., Mayeux, R., Mead, S., Mecocci, P., Medina, M., Meggy, A., Mehrabian, S., Mendoza, S., Menéndez-González, M., Mir, P., Moebus, S., Mol, M., Molina-Porcel, L., Montrreal, L., Morelli, L., Moreno, F., Morgan, K., Mosley, T., Nöthen, M. M., Muchnik, C., Mukherjee, S., Nacmias, B., Ngandu, T., Nicolas, G., Nordestgaard, B. G., Olaso, R., Orellana, A., Orsini, M., Ortega, G., Padovani, A., Paolo, C., Papenberg, G., Parnetti, L., Pasquier, F., Pastor, P., Peloso, G., Pérez-Cordón, A., Pérez-Tur, J., Pericard, P., Peters, O., Pijnenburg, Y. A. L., Pineda, J. A., Piñol-Ripoll, G., Pisanu, C., Polak, T., Popp, J., Posthuma, D., Priller, J., Puerta, R., Quenez, O., Quintela, I., Thomassen, J. Q., Rábano, A., Rainero, I., Rajabli, F., Ramakers, I., Real, L. M., Reinders, M. J. T., Reitz, C., Reyes-Dumeyer, D., Ridge, P., Riedel-Heller, S., Riederer, P., Roberto, N., Rodriguez-Rodriguez, E., Rongve, A., Allende, I. R., Rosende-Roca, M., Royo, J. L., Rubino, E., Rujescu, D., Sáez, M. E., Sakka, P., Saltvedt, I., Sanabria, Á., Sánchez-Arjona, M. B., Sanchez-Garcia, F., Juan, P. S., Sánchez-Valle, R., Sando, S. B., Sarnowski, C., Satizabal, C. L., Scamosci, M., Scarmeas, N., Scarpini, E., Scheltens, P., Scherbaum, N., Scherer, M., Schmid, M., Schneider, A., Schott, J. M., Selbæk, G., Seripa, D., Serrano, M., Sha, J., Shadrin, A. A., Skrobot, O., Slifer, S., Snijders, G. J. L., Soininen, H., Solfrizzi, V., Solomon, A., Song, Y. E., Sorbi, S., Sotolongo-Grau, O., Spalletta, G., Spottke, A., Squassina, A., Stordal, E., Tartan, J. P., Tárraga, L., Tesí, N., Thalamuthu, A., Thomas, T., Tosto, G., Traykov, L., Tremolizzo, L., Tybjærg-Hansen, A., Uitterlinden, A., Ullgren, A., Ulstein, I., Valero, S., Valladares, O., Broeckhoven, C. V., Vance, J., Vardarajan, B. N., van der Lugt, A., Dongen, J. V., van Rooij, J., van Swieten, J., Vandenberghe, R., Verhey, F., Vidal, J. -S., Vogelgsang, J., Vyhnalek, M., Wagner, M., Wallon, D., Wang, L. -S., Wang, R., Weinhold, L., Wiltfang, J., Windle, G., Woods, B., Yannakoulia, M., Zare, H., Zhao, Y., Zhang, X., Zhu, C., Zulaica, M., Laczo, J., Matoska, V., Serpente, M., Assogna, F., Piras, F., Ciullo, V., Shofany, J., Ferrarese, C., Andreoni, S., Sala, G., Zoia, C. P., Zompo, M. D., Benussi, A., Bastiani, P., Takalo, M., Natunen, T., Laatikainen, T., Tuomilehto, J., Antikainen, R., Strandberg, T., Lindström, J., Peltonen, M., Abraham, R., Al-Chalabi, A., Bass, N. J., Brayne, C., Brown, K. S., Collinge, J., Craig, D., Deloukas, P., Fox, N., Gerrish, A., Gill, M., Gwilliam, R., Harold, D., Hollingworth, P., Johnston, J. A., Jones, L., Lawlor, B., Livingston, G., Lovestone, S., Lupton, M., Lynch, A., Mann, D., Mcguinness, B., Mcquillin, A., O’Donovan, M. C., Owen, M. J., Passmore, P., Powell, J. F., Proitsi, P., Rossor, M., Shaw, C. E., Smith, A. D., Gurling, H., Todd, S., Mummery, C., Ryan, N., Lacidogna, G., Adarmes-Gómez, A., Mauleón, A., Pancho, A., Gailhajenet, A., Lafuente, A., Macias-García, D., Martín, E., Pelejà, E., Carrillo, F., Merlín, I. S., Garrote-Espina, L., Vargas, L., Carrion-Claro, M., Marín, M., Labrador, M., Buendia, M., Alonso, M. D., Guitart, M., Moreno, M., Ibarria, M., Periñán, M., Aguilera, N., Gómez-Garre, P., Cañabate, P., Escuela, R., Pineda-Sánchez, R., Vigo-Ortega, R., Jesús, S., Preckler, S., Rodrigo-Herrero, S., Diego, S., Vacca, A., Roveta, F., Salvadori, N., Chipi, E., Boecker, H., Laske, C., Perneczky, R., Anastasiou, C., Janowitz, D., Malik, R., Anastasiou, A., Parveen, K., López-García, S., Antonell, A., Mihova, K. Y., Belezhanska, D., Weber, H., Kochen, S., Solis, P., Medel, N., Lisso, J., Sevillano, Z., Politis, D. G., Cores, V., Cuesta, C., Ortiz, C., Bacha, J. I., Rios, M., Saenz, A., Abalos, M. S., Kohler, E., Palacio, D. L., Etchepareborda, I., Kohler, M., Novack, G., Prestia, F. A., Galeano, P., Castaño, E. M., Germani, S., Toso, C. R., Rojo, M., Ingino, C., Mangone, C., Rubinsztein, D. C., Teipel, S., Fievet, N., Deramerourt, V., Forsell, C., Thonberg, H., Bjerke, M., Roeck, E. D., Martínez-Larrad, M. T., Olivar, N., Cano, A., Macias, J., Maroñas, O., Nuñez-Llaves, R., Olivé, C., Adarmes-Gómez, A. D., Amer-Ferrer, G., Antequera, M., Burguera, J. A., Casajeros, M. J., Martinez de Pancorbo, M., Hevilla, S., Espinosa, M. A. L., Legaz, A., Manzanares, S., Marín-Muñoz, J., Marín, T., Martínez, B., Martínez, V., Martínez-Lage Álvarez, P., Iriarte, M. M., Periñán-Tocino, M. T., Real de Asúa, D., Rodrigo, S., Sastre, I., Vicente, M. P., Vivancos, L., Epelbaum, J., Hannequin, D., Campion, D., Deramecourt, V., Tzourio, C., Brice, A., Dubois, B., Williams, A., Thomas, C., Davies, C., Nash, W., Dowzell, K., Morales, A. C., Bernardo-Harrington, M., Turton, J., Lord, J., Brown, K., Vardy, E., Fisher, E., Warren, J. D., Ryan, N. S., Guerreiro, R., Uphill, J., Bass, N., Heun, R., Kölsch, H., Schürmann, B., Lacour, A., Herold, C., Powell, J., Patel, Y., Hodges, A., Becker, T., Warden, D., Wilcock, G., Clarke, R., Ben-Shlomo, Y., Hooper, N. M., Pickering-Brown, S., Sussams, R., Warner, N., Bayer, A., Heuser, I., Drichel, D., Klopp, N., Mayhaus, M., Riemenschneider, M., Pinchler, S., Feulner, T., Gu, W., van den Bussche, H., Hüll, M., Frölich, L., Wichmann, H. -E., Jöckel, K. -H., O’Donovan, M., Owen, M., Bahrami, S., Bosnes, I., Selnes, P., Bergh, S., Palotie, A., Daly, M., Jacob, H., Matakidou, A., Runz, H., John, S., Plenge, R., Mccarthy, M., Hunkapiller, J., Ehm, M., Waterworth, D., Fox, C., Malarstig, A., Klinger, K., Call, K., Behrens, T., Loerch, P., Mäkelä, T., Kaprio, J., Virolainen, P., Pulkki, K., Kilpi, T., Perola, M., Partanen, J., Pitkäranta, A., Kaarteenaho, R., Vainio, S., Turpeinen, M., Serpi, R., Laitinen, T., Mäkelä, J., Kosma, V. -M., Kujala, U., Tuovila, O., Hendolin, M., Pakkanen, R., Waring, J., Riley-Gillis, B., Liu, J., Biswas, S., Diogo, D., Marshall, C., Hu, X., Gossel, M., Graham, R., Cummings, B., Ripatti, S., Schleutker, J., Arvas, M., Carpén, O., Hinttala, R., Kettunen, J., Mannermaa, A., Laukkanen, J., Julkunen, V., Remes, A., Kälviäinen, R., Peltola, J., Tienari, P., Rinne, J., Ziemann, A., Esmaeeli, S., Smaoui, N., Lehtonen, A., Eaton, S., Lahdenperä, S., van Adelsberg, J., Michon, J., Kerchner, G., Bowers, N., Teng, E., Eicher, J., Mehta, V., Gormley, P., Linden, K., Whelan, C., Xu, F., Pulford, D., Färkkilä, M., Pikkarainen, S., Jussila, A., Blomster, T., Kiviniemi, M., Voutilainen, M., Georgantas, B., Heap, G., Rahimov, F., Usiskin, K., Lu, T., Oh, D., Kalpala, K., Miller, M., Mccarthy, L., Eklund, K., Palomäki, A., Isomäki, P., Pirilä, L., Kaipiainen-Seppänen, O., Huhtakangas, J., Lertratanakul, A., Hochfeld, M., Bing, N., Gordillo, J. E., Mars, N., Pelkonen, M., Kauppi, P., Kankaanranta, H., Harju, T., Close, D., Greenberg, S., Chen, H., Betts, J., Ghosh, S., Salomaa, V., Niiranen, T., Juonala, M., Metsärinne, K., Kähönen, M., Junttila, J., Laakso, M., Pihlajamäki, J., Sinisalo, J., Taskinen, M. -R., Tuomi, T., Challis, B., Peterson, A., Chu, A., Parkkinen, J., Muslin, A., Joensuu, H., Meretoja, T., Aaltonen, L., Mattson, J., Auranen, A., Karihtala, P., Kauppila, S., Auvinen, P., Elenius, K., Popovic, R., Schutzman, J., Loboda, A., Chhibber, A., Lehtonen, H., Mcdonough, S., Crohns, M., Kulkarni, D., Kaarniranta, K., Turunen, J. A., Ollila, T., Seitsonen, S., Uusitalo, H., Aaltonen, V., Uusitalo-Järvinen, H., Luodonpää, M., Hautala, N., Loomis, S., Strauss, E., Podgornaia, A., Hoffman, J., Tasanen, K., Huilaja, L., Hannula-Jouppi, K., Salmi, T., Peltonen, S., Koulu, L., Harvima, I., Wu, Y., Choy, D., Pussinen, P., Salminen, A., Salo, T., Rice, D., Nieminen, P., Palotie, U., Siponen, M., Suominen, L., Mäntylä, P., Gursoy, U., Anttonen, V., Sipilä, K., Davis, J. W., Quarless, D., Petrovski, S., Wigmore, E., Chen, C. -Y., Bronson, P., Tsai, E., Huang, Y., Maranville, J., Shaikho, E., Mohammed, E., Wadhawan, S., Kvikstad, E., Caliskan, M., Chang, D., Bhangale, T., Pendergrass, S., Holzinger, E., Chen, X., Hedman, Å., King, K. S., Wang, C., Xu, E., Auge, F., Chatelain, C., Rajpal, D., Liu, D., Xia, T. -H., Brauer, M., Kurki, M., Karjalainen, J., Havulinna, A., Jalanko, A., Palta, P., della Briotta Parolo, P., Zhou, W., Lemmelä, S., Rivas, M., Harju, J., Lehisto, A., Ganna, A., Llorens, V., Laivuori, H., Rüeger, S., Niemi, M. E., Tukiainen, T., Reeve, M. P., Heyne, H., Palin, K., Garcia-Tabuenca, J., Siirtola, H., Kiiskinen, T., Lee, J., Tsuo, K., Elliott, A., Kristiansson, K., Hyvärinen, K., Ritari, J., Koskinen, M., Pylkäs, K., Kalaoja, M., Karjalainen, M., Mantere, T., Kangasniemi, E., Heikkinen, S., Laakkonen, E., Sipeky, C., Heron, S., Karlsson, A., Jambulingam, D., Rathinakannan, V. S., Kajanne, R., Aavikko, M., Jiménez, M. G., della Briotta Parola, P., Kanai, M., Kaunisto, M., Kilpeläinen, E., Sipilä, T. P., Brein, G., Awaisa, G., Shcherban, A., Donner, K., Loukola, A., Laiho, P., Sistonen, T., Kaiharju, E., Laukkanen, M., Järvensivu, E., Lähteenmäki, S., Männikkö, L., Wong, R., Mattsson, H., Hiekkalinna, T., Paajanen, T., Pärn, K., Gracia-Tabuenca, J., Abner, E., Adams, P. M., Aguirre, A., Albert, M. S., Albin, R. L., Allen, M., Alvarez, L., Apostolova, L. G., Arnold, S. E., Asthana, S., Atwood, C. S., Ayres, G., Baldwin, C. T., Barber, R. C., Barnes, L. L., Beach, T. G., Becker, J. T., Beecham, G. W., Beekly, D., Benitez, B. A., Bennett, D., Bertelson, J., Margaret, F. E., Bird, T. D., Blacker, D., Boeve, B. F., Bowen, J. D., Boxer, A., Brewer, J., Burke, J. R., Burns, J. M., Buxbaum, J. D., Cairns, N. J., Cao, C., Carlson, C. S., Carlsson, C. M., Carney, R. M., Carrasquillo, M. M., Chasse, S., Chesselet, M. -F., Chesi, A., Chin, N. A., Chui, H. C., Craft, S., Crane, P. K., Cribbs, D. H., Crocco, E. A., Cruchaga, C., Cullum, M., Darby, E., Davis, B., De Jager, P. L., Decarli, C., Detoledo, J., Dick, M., Dickson, D. W., Dombroski, B. A., Doody, R. S., Duara, R., Ertekin-Taner, N., Evans, D. A., Fairchild, T. J., Fallon, K. B., Farlow, M. R., Farrell, J. J., Fernandez-Hernandez, V., Ferris, S., Frosch, M. P., Galasko, D. R., Gamboa, A., Gearing, M., Geschwind, D. H., Ghetti, B., Gilbert, J. R., Grabowski, T. J., Graff-Radford, N. R., Grant, S. F. A., Green, R. C., Growdon, J. H., Hakonarson, H., Hall, J., Hamilton, R. L., Harari, O., Harrell, L. E., Haut, J., Head, E., Henderson, V. W., Hernandez, M., Hohman, T., Honig, L. S., Huebinger, R. M., Huentelman, M. J., Hulette, C. M., Hyman, B. T., Hynan, L. S., Ibanez, L., Jarvik, G. P., Jayadev, S., Jin, L. -W., Johnson, K., Johnson, L., Kamboh, M. I., Karydas, A. M., Katz, M. J., Kaye, J. A., Keene, C. D., Khaleeq, A., Kim, R., Knebl, J., Kowall, N. W., Kramer, J. H., Laferla, F. M., Lah, J. J., Larson, E. B., Lee, E. B., Lerner, A., Leung, Y. Y., Leverenz, J. B., Levey, A. I., Li, M., Lieberman, A. P., Lipton, R. B., Logue, M., Lyketsos, C. G., Malamon, J., Mains, D., Marson, D. C., Martiniuk, F., Mash, D. C., Masliah, E., Massman, P., Masurkar, A., Mccormick, W. C., Mccurry, S. M., Mcdavid, A. N., Mckee, A. C., Mesulam, M., Mez, J., Miller, B. L., Miller, C. A., Miller, J. W., Montine, T. J., Monuki, E. S., Morris, J. C., Myers, A. J., Nguyen, T., O’Bryant, S., Olichney, J. M., Ory, M., Palmer, R., Parisi, J. E., Paulson, H. L., Pavlik, V., Paydarfar, D., Perez, V., Peskind, E., Petersen, R. C., Phillips-Cremins, J. E., Pierce, A., Polk, M., Poon, W. W., Potter, H., Qu, L., Quiceno, M., Quinn, J. F., Raj, A., Raskind, M., Reiman, E. M., Reisberg, B., Reisch, J. S., Ringman, J. M., Roberson, E. D., Rodriguear, M., Rogaeva, E., Rosen, H. J., Rosenberg, R. N., Royall, D. R., Sager, M. A., Sano, M., Saykin, A. J., Schneider, J. A., Schneider, L. S., Seeley, W. W., Small, S., Smith, A. G., Smith, J. P., Sonnen, J. A., Spina, S., George-Hyslop, P. 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Peters, O, Pijnenburg, Y, Pineda, J, Piñol-Ripoll, G, Pisanu, C, Polak, T, Popp, J, Posthuma, D, Priller, J, Puerta, R, Quenez, O, Quintela, I, Thomassen, J, Rábano, A, Rainero, I, Rajabli, F, Ramakers, I, Real, L, Reinders, M, Reitz, C, Reyes-Dumeyer, D, Ridge, P, Riedel-Heller, S, Riederer, P, Roberto, N, Rodriguez-Rodriguez, E, Rongve, A, Allende, I, Rosende-Roca, M, Royo, J, Rubino, E, Rujescu, D, Sáez, M, Sakka, P, Saltvedt, I, Sanabria, Á, Sánchez-Arjona, M, Sanchez-Garcia, F, Juan, P, Sánchez-Valle, R, Sando, S, Sarnowski, C, Satizabal, C, Scamosci, M, Scarmeas, N, Scarpini, E, Scheltens, P, Scherbaum, N, Scherer, M, Schmid, M, Schneider, A, Schott, J, Selbæk, G, Seripa, D, Serrano, M, Sha, J, Shadrin, A, Skrobot, O, Slifer, S, Snijders, G, Soininen, H, Solfrizzi, V, Solomon, A, Song, Y, Sorbi, S, Sotolongo-Grau, O, Spalletta, G, Spottke, A, Squassina, A, Stordal, E, Tartan, J, Tárraga, L, Tesí, N, Thalamuthu, A, Thomas, T, Tosto, G, Traykov, L, Tremolizzo, L, Tybjærg-Hansen, A, Uitterlinden, A, Ullgren, A, Ulstein, I, Valero, S, Valladares, O, Broeckhoven, C, Vance, J, Vardarajan, B, van der Lugt, A, Dongen, J, van Rooij, J, van Swieten, J, Vandenberghe, R, Verhey, F, Vidal, J, Vogelgsang, J, Vyhnalek, M, Wagner, M, Wallon, D, Wang, L, Wang, R, Weinhold, L, Wiltfang, J, Windle, G, Woods, B, Yannakoulia, M, Zare, H, Zhao, Y, Zhang, X, Zhu, C, Zulaica, M, Andreoni, S, Ferrarese, C, Sala, G, Zoia, C, Farrer, L, Psaty, B, Ghanbari, M, Raj, T, Sachdev, P, Mather, K, Jessen, F, Ikram, M, de Mendonça, A, Hort, J, Tsolaki, M, Pericak-Vance, M, Amouyel, P, Williams, J, Frikke-Schmidt, R, Clarimon, J, Deleuze, J, Rossi, G, Seshadri, S, Andreassen, O, Ingelsson, M, Hiltunen, M, Sleegers, K, Schellenberg, G, van Duijn, C, Sims, R, van der Flier, W, Ruiz, A, Ramirez, A, Lambert, J, VU University medical center, Amsterdam Neuroscience - Neurodegeneration, Neurology, Human genetics, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Neuroscience - Compulsivity, Impulsivity & Attention, APH - Personalized Medicine, APH - Methodology, Bellenguez, Céline [0000-0002-1240-7874], Küçükali, Fahri [0000-0002-3835-9639], Amin, Najaf [0000-0002-8944-1771], Holmans, Peter A [0000-0003-0870-9412], van der Lee, Sven J [0000-0003-1606-8643], Costa, Marcos R [0000-0002-4928-2163], Kuulasmaa, Teemu [0000-0002-1795-7314], Yang, Qiong [0000-0002-3658-1375], de Rojas, Itziar [0000-0002-2148-381X], Bis, Joshua C [0000-0002-3409-1110], Yaqub, Amber [0000-0002-3579-8054], Prokic, Ivana [0000-0002-0370-1473], Chapuis, Julien [0000-0002-5802-2857], Ahmad, Shahzad [0000-0002-8658-3790], Giedraitis, Vilmantas [0000-0003-3423-2021], Garcia-Gonzalez, Pablo [0000-0003-0125-5403], Alcolea, Daniel [0000-0002-3819-3245], Alvarez, Ignacio [0000-0002-8537-3935], Tsolaki, Anthoula [0000-0002-5563-7776], Baquero, Miquel [0000-0002-6861-1831], Pastor, Ana Belén [0000-0001-9637-4688], Berr, Claudine [0000-0001-5254-7655], Bessi, Valentina [0000-0002-6176-3584], Boada, Mercè 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[0000-0002-7493-8777], Peloso, Gina [0000-0002-5355-8636], Pérez-Cordón, Alba [0000-0002-6028-0791], Pérez-Tur, Jordi [0000-0002-9111-1712], Pericard, Pierre [0000-0001-8167-6448], Pineda, Juan A [0000-0002-3751-0296], Pisanu, Claudia [0000-0002-9151-4319], Posthuma, Danielle [0000-0001-7582-2365], Puerta, Raquel [0000-0002-1191-5893], Quenez, Olivier [0000-0002-8273-8505], Thomassen, Jesper Qvist [0000-0003-3484-9531], Real, Luis M [0000-0003-4932-7429], Reinders, Marcel JT [0000-0002-1148-1562], Reitz, Christiane [0000-0001-8757-7889], Riedel-Heller, Steffi [0000-0003-4321-6090], Rodriguez-Rodriguez, Eloy [0000-0001-7742-677X], Rongve, Arvid [0000-0002-0476-4134], Sáez, María Eugenia [0000-0001-9299-2534], Saltvedt, Ingvild [0000-0002-7897-9808], Juan, Pascual Sánchez [0000-0002-6081-8037], Sarnowski, Chloé [0000-0002-6090-7099], Satizabal, Claudia L [0000-0002-1115-4430], Schott, Jonathan M [0000-0003-2059-024X], Selbæk, Geir [0000-0001-6511-8219], Shadrin, Alexey A 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Sachdev, Perminder [0000-0002-9595-3220], Mather, Karen [0000-0003-4143-8941], Ikram, M Arfan [0000-0003-0372-8585], Tsolaki, Magda [0000-0002-2072-8010], Pericak-Vance, Margaret A [0000-0001-7283-8804], Amouyel, Philippe [0000-0001-9088-234X], Williams, Julie [0000-0002-4069-0259], Frikke-Schmidt, Ruth [0000-0003-4084-5027], Seshadri, Sudha [0000-0001-6135-2622], Andreassen, Ole A [0000-0002-4461-3568], Sleegers, Kristel [0000-0002-0283-2332], van Duijn, Cornelia M [0000-0002-2374-9204], Sims, Rebecca [0000-0002-3885-1199], van der Flier, Wiesje M [0000-0001-8766-6224], Ramirez, Alfredo [0000-0003-4991-763X], Lambert, Jean-Charles [0000-0003-0829-7817], Apollo - University of Cambridge Repository, Complex Trait Genetics, Clinical sciences, Neuroprotection & Neuromodulation, Pathologic Biochemistry and Physiology, Clinical Biology, Epidemiology, Internal Medicine, Psychiatrie & Neuropsychologie, RS: MHeNs - R1 - Cognitive Neuropsychiatry and Clinical Neuroscience, MUMC+: MA Med Staf Spec Psychiatrie (9), UAM. Departamento de Biología Molecular, University of Helsinki, Department of Neurosciences, HUS Internal Medicine and Rehabilitation, Timo Strandberg / Principal Investigator, Department of Medicine, Clinicum, HUS Neurocenter, Neurologian yksikkö, Centre of Excellence in Complex Disease Genetics, HUS Abdominal Center, Institut Pasteur, Institut National de la Santé et de la Recherche Médicale (France), European Commission, LabEx DISTALZ, Pérez-Tur, Jordi, University Children’s Hospital Basel (Suiza), INSERM (Francia), Lille Métropole Communauté Urbaine, Government of France (Francia), EADB, GR@ACE, DEGESCO, EADI, GERAD, Demgene, FinnGen, ADGC, CHARGE, Holmans, Peter A. [0000-0003-0870-9412], van der Lee, Sven J. [0000-0003-1606-8643], Costa, Marcos R. [0000-0002-4928-2163], Bis, Joshua C. [0000-0002-3409-1110], Brookes, Keeley J. [0000-0003-2427-2513], Bush, William S. [0000-0002-9729-6519], de Witte, Lot D. [0000-0002-7235-9958], del Ser, Teodoro [0000-0001-9806-7083], Fox, Nick C. [0000-0002-6660-657X], Bullido, María J. [0000-0002-6477-1117], Goate, Alison M. [0000-0002-0576-2472], Herrmann, Martin J. [0000-0001-9970-2122], Jun, Gyungah R. [0000-0002-3230-8697], Kehoe, Patrick G. [0000-0002-7542-1139], Kosmidis, Mary H. [0000-0001-8790-1220], Lunetta, Kathryn L. [0000-0002-9268-810X], MacLeod, Catherine A. [0000-0002-9314-7380], Nöthen, Markus M. [0000-0002-8770-2464], Nordestgaard, Børge G. [0000-0002-1954-7220], Pineda, Juan A. [0000-0002-3751-0296], Real, Luis M. [0000-0003-4932-7429], Reinders, Marcel J. T. [0000-0002-1148-1562], Satizabal, Claudia L. [0000-0002-1115-4430], Schott, Jonathan M. [0000-0003-2059-024X], Shadrin, Alexey A. [0000-0002-7467-250X], Farrer, Lindsay A. [0000-0001-5533-4225], Psaty, Bruce M. [0000-0002-7278-2190], Ikram, M. Arfan [0000-0003-0372-8585], Pericak-Vance, Margaret A. [0000-0001-7283-8804], Andreassen, Ole A. [0000-0002-4461-3568], van Duijn, Cornelia M. [0000-0002-2374-9204], van der Flier, Wiesje M. [0000-0001-8766-6224], and Molecular Neuroscience and Ageing Research (MOLAR)
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tau Proteins/genetics ,Alzheimer`s disease Donders Center for Medical Neuroscience [Radboudumc 1] ,Neurologi ,MED/03 - GENETICA MEDICA ,45/43 ,Medizin ,Stress-related disorders Donders Center for Medical Neuroscience [Radboudumc 13] ,genetics [Alzheimer Disease] ,Genome-Wide Association Study ,Humans ,tau Proteins ,Alzheimer Disease ,Cognitive Dysfunction ,VARIANTS ,pathology [Alzheimer Disease] ,Tau Proteins ,Settore BIO/13 - Biologia Applicata ,Cognitive Dysfunction/psychology ,692/699/375/365/1283 ,IMPUTATION ,article ,1184 Genetics, developmental biology, physiology ,Biología y Biomedicina / Biología ,AMYLOID-BETA ,Settore MED/26 - NEUROLOGIA ,Neurology ,psychology [Cognitive Dysfunction] ,Medical Genetics ,Human ,Neuroscience(all) ,631/208/205/2138 ,All institutes and research themes of the Radboud University Medical Center ,SDG 3 - Good Health and Well-being ,ddc:570 ,Genetics ,Genetic Predisposition to Disease ,GENOME-WIDE ASSOCIATION ,METAANALYSIS ,Medicinsk genetik ,MED/26 - NEUROLOGIA ,Alzheimer Disease/genetics ,neurology ,tau Protein ,NECROSIS-FACTOR-ALPHA ,RISK LOCI ,genetics [tau Proteins] ,PREDICTION MODELS ,Human medicine ,GENERATION ,RESPONSES - Abstract
25 páginas, 6 figuras, 2 tablas, 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 ε4 allele., This work was funded by a grant (EADB) from the EU Joint Programme – Neurodegenerative Disease Research. INSERM UMR1167 is also funded by the INSERM, Institut Pasteur de Lille, Lille Métropole Communauté Urbaine and French government’s LABEX DISTALZ program (development of innovative strategies for a transdisciplinary approach to AD). Full consortium acknowledgements and funding are in the Supplementary Not
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- 2022
11. 28 Addressing Workplace Violence: Health Care Staff Safety, a Culture of Caring
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Barata, I., primary, Calandrella, C., additional, Feinman, R., additional, Maurice, K., additional, Kasulke, L., additional, Urban, K., additional, Ibanez, L., additional, Nassar, J., additional, Ferrigno, J., additional, and Derleth, W., additional
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- 2022
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12. Stroke genetics informs drug discovery and risk prediction across ancestries
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Mishra, A, Malik, R, Hachiya, T, Jurgenson, T, Namba, S, Posner, DC, Kamanu, FK, Koido, M, Le Grand, Q, Shi, M, He, Y, Georgakis, MK, Caro, I, Krebs, K, Liaw, Y-C, Vaura, FC, Lin, K, Winsvold, BS, Srinivasasainagendra, V, Parodi, L, Bae, H-J, Chauhan, G, Chong, MR, Tomppo, L, Akinyemi, R, Roshchupkin, GV, Habib, N, Jee, YH, Thomassen, JQ, Abedi, V, Carcel-Marquez, J, Nygaard, M, Leonard, HL, Yang, C, Yonova-Doing, E, Knol, MJ, Lewis, AJ, Judy, RL, Ago, T, Amouyel, P, Armstrong, ND, Bakker, MK, Bartz, TM, Bennett, DA, Bis, JC, Bordes, C, Borte, S, Cain, A, Ridker, PM, Cho, K, Chen, Z, Cruchaga, C, Cole, JW, de Jager, PL, de Cid, R, Endres, M, Ferreira, LE, Geerlings, MI, Gasca, NC, Gudnason, V, Hata, J, He, J, Heath, AK, Ho, Y-L, Havulinna, AS, Hopewell, JC, Hyacinth, HI, Inouye, M, Jacob, MA, Jeon, CE, Jern, C, Kamouchi, M, Keene, KL, Kitazono, T, Kittner, SJ, Konuma, T, Kumar, A, Lacaze, P, Launer, LJ, Lee, K-J, Lepik, K, Li, J, Li, L, Manichaikul, A, Markus, HS, Marston, NA, Meitinger, T, Mitchell, BD, Montellano, FA, Morisaki, T, Mosley, TH, Nalls, MA, Nordestgaard, BG, O'Donnell, MJ, Okada, Y, Onland-Moret, NC, Ovbiagele, B, Peters, A, Psaty, BM, Rich, SS, Rosand, J, Sabatine, MS, Sacco, RL, Saleheen, D, Sandset, EC, Salomaa, V, Sargurupremraj, M, Sasaki, M, Satizabal, CL, Schmidt, CO, Shimizu, A, Smith, NL, Sloane, KL, Sutoh, Y, Sun, YV, Tanno, K, Tiedt, S, Tatlisumak, T, Torres-Aguila, NP, Tiwari, HK, Tregouet, D-A, Trompet, S, Tuladhar, AM, Tybjaerg-Hansen, A, van Vugt, M, Vibo, R, Verma, SS, Wiggins, KL, Wennberg, P, Woo, D, Wilson, PWF, Xu, H, Yang, Q, Yoon, K, Millwood, IY, Gieger, C, Ninomiya, T, Grabe, HJ, Jukema, JW, Rissanen, IL, Strbian, D, Kim, YJ, Chen, P-H, Mayerhofer, E, Howson, JMM, Irvin, MR, Adams, H, Wassertheil-Smoller, S, Christensen, K, Ikram, MA, Rundek, T, Worrall, BB, Lathrop, GM, Riaz, M, Simonsick, EM, Korv, J, Franca, PHC, Zand, R, Prasad, K, Frikke-Schmidt, R, de Leeuw, F-E, Liman, T, Haeusler, KG, Ruigrok, YM, Heuschmann, PU, Longstreth, WT, Jung, KJ, Bastarache, L, Pare, G, Damrauer, SM, Chasman, DI, Rotter, JI, Anderson, CD, Zwart, J-A, Niiranen, TJ, Fornage, M, Liaw, Y-P, Seshadri, S, Fernandez-Cadenas, I, Walters, RG, Ruff, CT, Owolabi, MO, Huffman, JE, Milani, L, Kamatani, Y, Dichgans, M, Debette, S, Lee, J-M, Cheng, Y-C, Meschia, JF, Chen, WM, Sale, MM, Zonderman, AB, Evans, MK, Wilson, JG, Correa, A, Traylor, M, Lewis, CM, Reiner, A, Haessler, J, Langefeld, CD, Gottesman, RF, Yaffe, K, Liu, YM, Kooperberg, C, Lange, LA, Furie, KL, Arnett, DK, Benavente, OR, Grewal, RP, Peddareddygari, LR, Hveem, K, Lindstrom, S, Wang, L, Smith, EN, Gordon, W, Vlieg, AVH, de Andrade, M, Brody, JA, Pattee, JW, Brumpton, BM, Suchon, P, Chen, M-H, Frazer, KA, Turman, C, Germain, M, MacDonald, J, Braekkan, SK, Armasu, SM, Pankratz, N, Jackson, RD, Nielsen, JB, Giulianin, F, Puurunen, MK, Ibrahim, M, Heckbert, SR, Bammler, TK, McCauley, BM, Taylor, KD, Pankow, JS, Reiner, AP, Gabrielsen, ME, Deleuze, J-F, O'Donnell, CJ, Kim, J, McKnight, B, Kraft, P, Hansen, J-B, Rosendaal, FR, Heit, JA, Tang, W, Morange, P-E, Johnson, AD, Kabrhel, C, van Dijk, EJ, Koudstaal, PJ, Luijckx, G-J, Nederkoorn, PJ, van Oostenbrugge, RJ, Visser, MC, Wermer, MJH, Kappelle, LJ, Esko, T, Metspalu, A, Magi, R, Nelis, M, Levi, CR, Maguire, J, Jimenez-Conde, J, Sharma, P, Sudlow, CLM, Rannikmae, K, Schmidt, R, Slowik, A, Pera, J, Thijs, VNS, Lindgren, AG, Ilinca, A, Melander, O, Engstrom, G, Rexrode, KM, Rothwell, PM, Stanne, TM, Johnson, JA, Danesh, J, Butterworth, AS, Heitsch, L, Boncoraglio, GB, Kubo, M, Pezzini, A, Rolfs, A, Giese, A-K, Weir, D, Ross, OA, Lemmons, R, Soderholm, M, Cushman, M, Jood, K, McDonough, CW, Bell, S, Linkohr, B, Lee, T-H, Putaala, J, Lopez, OL, Carty, CL, Jian, X, Schminke, U, Cullell, N, Delgado, P, Ibanez, L, Krupinski, J, Lioutas, V, Matsuda, K, Montaner, J, Muino, E, Roquer, J, Sarnowski, C, Sattar, N, Sibolt, G, Teumer, A, Rutten-Jacobs, L, Kanai, M, Gretarsdottir, S, Rost, NS, Yusuf, S, Almgren, P, Ay, H, Bevan, S, Brown, RD, Carrera, C, Buring, JE, Chen, W-M, Cotlarciuc, I, de Bakker, PIW, DeStefano, AL, den Hoed, M, Duan, Q, Engelter, ST, Falcone, GJ, Gustafsson, S, Hassan, A, Holliday, EG, Howard, G, Hsu, F-C, Ingelsson, E, Harris, TB, Kissela, BM, Kleindorfer, DO, Langenberg, C, Leys, D, Lin, W-Y, Lorentzen, E, Magnusson, PK, McArdle, PF, Pulit, SL, Rice, K, Sakaue, S, Sapkota, BR, Tanislav, C, Thorleifsson, G, Thorsteinsdottir, U, Tzourio, C, van Duijn, CM, Walters, M, Wareham, NJ, Amin, N, Aparicio, HJ, Attia, J, Beiser, AS, Berr, C, Bustamante, M, Caso, V, Choi, SH, Chowhan, A, Dartigues, J-F, Delavaran, H, Dorr, M, Ford, I, Gurpreet, WS, Hamsten, A, Hozawa, A, Ingelsson, M, Iwasaki, M, Kaffashian, S, Kalra, L, Kjartansson, O, Kloss, M, Labovitz, DL, Laurie, CC, Lind, L, Lindgren, CM, Makoto, H, Minegishi, N, Morris, AP, Mueller-Nurasyid, M, Norrving, B, Ogishima, S, Parati, EA, Pedersen, NL, Perola, M, Jousilahti, P, Pileggi, S, Rabionet, R, Riba-Llena, I, Ribases, M, Romero, JR, Rudd, AG, Sarin, A-P, Sarju, R, Satoh, M, Sawada, N, Sigurdsson, A, Smith, A, Stine, OC, Stott, DJ, Strauch, K, Takai, T, Tanaka, H, Touze, E, Tsugane, S, Uitterlinden, AG, Valdimarsson, EM, van der Lee, SJ, Wakai, K, Williams, SR, Wolfe, CDA, Wong, Q, Yamaji, T, Sanghera, DK, Stefansson, K, Martinez-Majander, N, Sobue, K, Soriano-Tarraga, C, Volzke, H, Akpa, O, Sarfo, FS, Akpalu, A, Obiako, R, Wahab, K, Osaigbovo, G, Owolabi, L, Komolafe, M, Jenkins, C, Arulogun, O, Ogbole, G, Adeoye, AM, Akinyemi, J, Agunloye, A, Fakunle, AG, Uvere, E, Olalere, A, Adebajo, OJ, Chen, J, Clarke, R, Collins, R, Guo, Y, Wang, C, Lv, J, Peto, R, Chen, Y, Fairhurst-Hunter, Z, Hill, M, Pozarickij, A, Schmidt, D, Stevens, B, Turnbull, I, Yu, C, Nagai, A, Murakami, Y, Shiroma, EJ, Sigurdsson, S, Ghanbari, M, Boerwinkle, E, Fongang, B, Wang, R, Ikram, MK, Volker, U, de Laat, KF, van Norden, AGW, de Kort, PL, Vermeer, SE, Brouwers, PJAM, Gons, RAR, den Heijer, T, van Dijk, GW, van Rooij, FGW, Aamodt, AH, Skogholt, AH, Willer, CJ, Heuch, I, Hagen, K, Fritsche, LG, Pedersen, LM, Ellekjaer, H, Zhou, W, Martinsen, AE, Kristoffersen, ES, Thomas, LF, Kleinschnitz, C, Frantz, S, Ungethum, K, Gallego-Fabrega, C, Lledos, M, Llucia-Carol, L, Sobrino, T, Campos, F, Castillo, J, Freijo, M, Arenillas, JF, Obach, V, Alvarez-Sabin, J, Molina, CA, Ribo, M, Munoz-Narbona, L, Lopez-Cancio, E, Millan, M, Diaz-Navarro, R, Vives-Bauza, C, Serrano-Heras, G, Segura, T, Dhar, R, Delgado-Mederos, R, Prats-Sanchez, L, Camps-Renom, P, Blay, N, Sumoy, L, Marti-Fabregas, J, Schnohr, P, Jensen, GB, Benn, M, Afzal, S, Kamstrup, PR, van Setten, J, van der Laan, SW, Vonk, JMJ, Kim, B-J, Curtze, S, Tiainen, M, Kinnunen, J, Menon, V, Sung, YJ, Saillour-Glenisson, F, Gravel, S, Mishra, A, Malik, R, Hachiya, T, Jurgenson, T, Namba, S, Posner, DC, Kamanu, FK, Koido, M, Le Grand, Q, Shi, M, He, Y, Georgakis, MK, Caro, I, Krebs, K, Liaw, Y-C, Vaura, FC, Lin, K, Winsvold, BS, Srinivasasainagendra, V, Parodi, L, Bae, H-J, Chauhan, G, Chong, MR, Tomppo, L, Akinyemi, R, Roshchupkin, GV, Habib, N, Jee, YH, Thomassen, JQ, Abedi, V, Carcel-Marquez, J, Nygaard, M, Leonard, HL, Yang, C, Yonova-Doing, E, Knol, MJ, Lewis, AJ, Judy, RL, Ago, T, Amouyel, P, Armstrong, ND, Bakker, MK, Bartz, TM, Bennett, DA, Bis, JC, Bordes, C, Borte, S, Cain, A, Ridker, PM, Cho, K, Chen, Z, Cruchaga, C, Cole, JW, de Jager, PL, de Cid, R, Endres, M, Ferreira, LE, Geerlings, MI, Gasca, NC, Gudnason, V, Hata, J, He, J, Heath, AK, Ho, Y-L, Havulinna, AS, Hopewell, JC, Hyacinth, HI, Inouye, M, Jacob, MA, Jeon, CE, Jern, C, Kamouchi, M, Keene, KL, Kitazono, T, Kittner, SJ, Konuma, T, Kumar, A, Lacaze, P, Launer, LJ, Lee, K-J, Lepik, K, Li, J, Li, L, Manichaikul, A, Markus, HS, Marston, NA, Meitinger, T, Mitchell, BD, Montellano, FA, Morisaki, T, Mosley, TH, Nalls, MA, Nordestgaard, BG, O'Donnell, MJ, Okada, Y, Onland-Moret, NC, Ovbiagele, B, Peters, A, Psaty, BM, Rich, SS, Rosand, J, Sabatine, MS, Sacco, RL, Saleheen, D, Sandset, EC, Salomaa, V, Sargurupremraj, M, Sasaki, M, Satizabal, CL, Schmidt, CO, Shimizu, A, Smith, NL, Sloane, KL, Sutoh, Y, Sun, YV, Tanno, K, Tiedt, S, Tatlisumak, T, Torres-Aguila, NP, Tiwari, HK, Tregouet, D-A, Trompet, S, Tuladhar, AM, Tybjaerg-Hansen, A, van Vugt, M, Vibo, R, Verma, SS, Wiggins, KL, Wennberg, P, Woo, D, Wilson, PWF, Xu, H, Yang, Q, Yoon, K, Millwood, IY, Gieger, C, Ninomiya, T, Grabe, HJ, Jukema, JW, Rissanen, IL, Strbian, D, Kim, YJ, Chen, P-H, Mayerhofer, E, Howson, JMM, Irvin, MR, Adams, H, Wassertheil-Smoller, S, Christensen, K, Ikram, MA, Rundek, T, Worrall, BB, Lathrop, GM, Riaz, M, Simonsick, EM, Korv, J, Franca, PHC, Zand, R, Prasad, K, Frikke-Schmidt, R, de Leeuw, F-E, Liman, T, Haeusler, KG, Ruigrok, YM, Heuschmann, PU, Longstreth, WT, Jung, KJ, Bastarache, L, Pare, G, Damrauer, SM, Chasman, DI, Rotter, JI, Anderson, CD, Zwart, J-A, Niiranen, TJ, Fornage, M, Liaw, Y-P, Seshadri, S, Fernandez-Cadenas, I, Walters, RG, Ruff, CT, Owolabi, MO, Huffman, JE, Milani, L, Kamatani, Y, Dichgans, M, Debette, S, Lee, J-M, Cheng, Y-C, Meschia, JF, Chen, WM, Sale, MM, Zonderman, AB, Evans, MK, Wilson, JG, Correa, A, Traylor, M, Lewis, CM, Reiner, A, Haessler, J, Langefeld, CD, Gottesman, RF, Yaffe, K, Liu, YM, Kooperberg, C, Lange, LA, Furie, KL, Arnett, DK, Benavente, OR, Grewal, RP, Peddareddygari, LR, Hveem, K, Lindstrom, S, Wang, L, Smith, EN, Gordon, W, Vlieg, AVH, de Andrade, M, Brody, JA, Pattee, JW, Brumpton, BM, Suchon, P, Chen, M-H, Frazer, KA, Turman, C, Germain, M, MacDonald, J, Braekkan, SK, Armasu, SM, Pankratz, N, Jackson, RD, Nielsen, JB, Giulianin, F, Puurunen, MK, Ibrahim, M, Heckbert, SR, Bammler, TK, McCauley, BM, Taylor, KD, Pankow, JS, Reiner, AP, Gabrielsen, ME, Deleuze, J-F, O'Donnell, CJ, Kim, J, McKnight, B, Kraft, P, Hansen, J-B, Rosendaal, FR, Heit, JA, Tang, W, Morange, P-E, Johnson, AD, Kabrhel, C, van Dijk, EJ, Koudstaal, PJ, Luijckx, G-J, Nederkoorn, PJ, van Oostenbrugge, RJ, Visser, MC, Wermer, MJH, Kappelle, LJ, Esko, T, Metspalu, A, Magi, R, Nelis, M, Levi, CR, Maguire, J, Jimenez-Conde, J, Sharma, P, Sudlow, CLM, Rannikmae, K, Schmidt, R, Slowik, A, Pera, J, Thijs, VNS, Lindgren, AG, Ilinca, A, Melander, O, Engstrom, G, Rexrode, KM, Rothwell, PM, Stanne, TM, Johnson, JA, Danesh, J, Butterworth, AS, Heitsch, L, Boncoraglio, GB, Kubo, M, Pezzini, A, Rolfs, A, Giese, A-K, Weir, D, Ross, OA, Lemmons, R, Soderholm, M, Cushman, M, Jood, K, McDonough, CW, Bell, S, Linkohr, B, Lee, T-H, Putaala, J, Lopez, OL, Carty, CL, Jian, X, Schminke, U, Cullell, N, Delgado, P, Ibanez, L, Krupinski, J, Lioutas, V, Matsuda, K, Montaner, J, Muino, E, Roquer, J, Sarnowski, C, Sattar, N, Sibolt, G, Teumer, A, Rutten-Jacobs, L, Kanai, M, Gretarsdottir, S, Rost, NS, Yusuf, S, Almgren, P, Ay, H, Bevan, S, Brown, RD, Carrera, C, Buring, JE, Chen, W-M, Cotlarciuc, I, de Bakker, PIW, DeStefano, AL, den Hoed, M, Duan, Q, Engelter, ST, Falcone, GJ, Gustafsson, S, Hassan, A, Holliday, EG, Howard, G, Hsu, F-C, Ingelsson, E, Harris, TB, Kissela, BM, Kleindorfer, DO, Langenberg, C, Leys, D, Lin, W-Y, Lorentzen, E, Magnusson, PK, McArdle, PF, Pulit, SL, Rice, K, Sakaue, S, Sapkota, BR, Tanislav, C, Thorleifsson, G, Thorsteinsdottir, U, Tzourio, C, van Duijn, CM, Walters, M, Wareham, NJ, Amin, N, Aparicio, HJ, Attia, J, Beiser, AS, Berr, C, Bustamante, M, Caso, V, Choi, SH, Chowhan, A, Dartigues, J-F, Delavaran, H, Dorr, M, Ford, I, Gurpreet, WS, Hamsten, A, Hozawa, A, Ingelsson, M, Iwasaki, M, Kaffashian, S, Kalra, L, Kjartansson, O, Kloss, M, Labovitz, DL, Laurie, CC, Lind, L, Lindgren, CM, Makoto, H, Minegishi, N, Morris, AP, Mueller-Nurasyid, M, Norrving, B, Ogishima, S, Parati, EA, Pedersen, NL, Perola, M, Jousilahti, P, Pileggi, S, Rabionet, R, Riba-Llena, I, Ribases, M, Romero, JR, Rudd, AG, Sarin, A-P, Sarju, R, Satoh, M, Sawada, N, Sigurdsson, A, Smith, A, Stine, OC, Stott, DJ, Strauch, K, Takai, T, Tanaka, H, Touze, E, Tsugane, S, Uitterlinden, AG, Valdimarsson, EM, van der Lee, SJ, Wakai, K, Williams, SR, Wolfe, CDA, Wong, Q, Yamaji, T, Sanghera, DK, Stefansson, K, Martinez-Majander, N, Sobue, K, Soriano-Tarraga, C, Volzke, H, Akpa, O, Sarfo, FS, Akpalu, A, Obiako, R, Wahab, K, Osaigbovo, G, Owolabi, L, Komolafe, M, Jenkins, C, Arulogun, O, Ogbole, G, Adeoye, AM, Akinyemi, J, Agunloye, A, Fakunle, AG, Uvere, E, Olalere, A, Adebajo, OJ, Chen, J, Clarke, R, Collins, R, Guo, Y, Wang, C, Lv, J, Peto, R, Chen, Y, Fairhurst-Hunter, Z, Hill, M, Pozarickij, A, Schmidt, D, Stevens, B, Turnbull, I, Yu, C, Nagai, A, Murakami, Y, Shiroma, EJ, Sigurdsson, S, Ghanbari, M, Boerwinkle, E, Fongang, B, Wang, R, Ikram, MK, Volker, U, de Laat, KF, van Norden, AGW, de Kort, PL, Vermeer, SE, Brouwers, PJAM, Gons, RAR, den Heijer, T, van Dijk, GW, van Rooij, FGW, Aamodt, AH, Skogholt, AH, Willer, CJ, Heuch, I, Hagen, K, Fritsche, LG, Pedersen, LM, Ellekjaer, H, Zhou, W, Martinsen, AE, Kristoffersen, ES, Thomas, LF, Kleinschnitz, C, Frantz, S, Ungethum, K, Gallego-Fabrega, C, Lledos, M, Llucia-Carol, L, Sobrino, T, Campos, F, Castillo, J, Freijo, M, Arenillas, JF, Obach, V, Alvarez-Sabin, J, Molina, CA, Ribo, M, Munoz-Narbona, L, Lopez-Cancio, E, Millan, M, Diaz-Navarro, R, Vives-Bauza, C, Serrano-Heras, G, Segura, T, Dhar, R, Delgado-Mederos, R, Prats-Sanchez, L, Camps-Renom, P, Blay, N, Sumoy, L, Marti-Fabregas, J, Schnohr, P, Jensen, GB, Benn, M, Afzal, S, Kamstrup, PR, van Setten, J, van der Laan, SW, Vonk, JMJ, Kim, B-J, Curtze, S, Tiainen, M, Kinnunen, J, Menon, V, Sung, YJ, Saillour-Glenisson, F, and Gravel, S
- Abstract
Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.
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- 2022
13. Home Blood Pressure Self-monitoring plus Self-titration of Antihypertensive Medication for Poorly Controlled Hypertension in Primary Care: the ADAMPA Randomized Clinical Trial
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Martinez-Ibanez P, Marco-Moreno I, Peiro S, Martinez-Ibanez L, Barreira-Franch I, Bellot-Pujalte L, Avelino-Hidalgo E, Escrig-Veses M, Boveda-Garcia M, Calleja-del-Ser M, Ferrero-Gregori A, Iftimi A, Hurtado I, Garcia-Sempere A, Rodriguez-Bernal C, Gimenez-Loreiro M, Sanfelix-Gimeno G, and Sanfelix-Genoves J
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primary care ,blood pressure self-monitoring ,randomized clinical trial ,patient empowerment ,blood pressure self-management - Abstract
BACKGROUND: Patient empowerment through pharmacological self-management is a common strategy in some chronic diseases such as diabetes, but it is rarely used for controlling blood pressure. OBJECTIVE : This study aimed to assess self-monitoring plus self-titration of antihypertensive medication versus usual care for reducing systolic blood pressure (SBP) at 12 months in poorly controlled hypertensive patients. DESIGN: The ADAMPA study was a pragmatic, controlled, randomized, non-masked clinical trial with two parallel arms in Valencia, Spain. PARTICIPANTS: Hypertensive patients older than 40 years, with SBP over 145 mmHg and/or diastolic blood pressure (DBP) over 90 mmHg, were recruited from July 2017 to June 2018. INTERVENTION: Participants were randomized 1:1 to usual care versus an individualized, pre-arranged plan based on self-monitoring plus self-titration. MAIN MEASURE: The primary outcome was the adjusted mean difference (AMD) in SBP between groups at 12 months. KEY RESULTS: Primary outcome data were available for 312 patients (intervention n=156, control n=156) of the 366 who were initially recruited. The AMD in SBP at 12 months (main analysis) was -2.9 mmHg (95% CI, -5.9 to 0.1, p=0.061), while the AMD in DBP was -1.9 mmHg (95% CI, -3.7 to 0.0, p=0.052). The results of the subgroup analysis were consistent with these for the main outcome measures. More patients in the intervention group achieved good blood pressure control (
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- 2022
14. P129 - Real-world data analysis of treatment outcomes for patients with metastatic hormone-sensitive prostate cancer: development of a survival prediction model. Results from the European network of excellence for big data in prostate cancer (PIONEER)
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Gómez Rivas, J., Nicoletti, R., Golozar, A., Ayman, H., Steinbeißer, C., Ibañez, L., De Meulder, B., Axelsson, S.E., Snijder, R., Feng, Q., Bjartell, A., Cornford, P., Willemse, P., Prinsen, P., Murtola, T.J., and N´dow, J.
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- 2023
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15. P096 - Real-world data analysis of clinical characteristics in metastatic hormone-sensitive prostate cancer: Are patients from RCTs the same from real life? Data from the European network of excellence for big data in prostate cancer (PIONEER).
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Gómez Rivas, J., Nicoletti, R., Golozar, A., Steinbeißer, C., De Meulder, B., Snijder, R., Ibañez, L., Axelsson, S.E., Ayman, H., Feng, Q., Murtola, T.J., Bjartell, A., Cornford, P., Willemse, P., Prinsen, P., and N´dow, J.
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- 2023
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16. 1796P Real-world analysis of metastatic hormone-sensitive prostate cancer: Are randomized clinical trials more trustworthy? Insights from PIONEER, the European network of excellence for big data in prostate cancer
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Gómez Rivas, J., Nicoletti, R., Golozar, A., Steinbeißer, C., Ibañez, L., De Meulder, B., Evans Axelsson, S., Snijder, R., Bjartell, A., Cornford, P., Willemse, P-P., Prinsen, P., Murtola, T., and N'Dow, J.
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- 2023
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17. A0510 - Current clinical practice patterns with robotic salvage radical prostatectomy: Oncological results from 10 high-volume robotic centers.
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Wenzel, M., Di Maida, F., Gomez Rivas, J., Ibanez, L., Bravi, C.A., De Groote, R., Piramide, F., Turri, F., Kowalczyk, K., Würnschimmel, C., Sharma, G., Andras, I., Lambert, E., Liakos, N., Darlington, D., Paciotti, M., Sorce, G., Galfano, A., Dell'Oglio, P., and Mottrie, A.
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PHYSICIAN practice patterns , *RADICAL prostatectomy , *ROBOTICS - Published
- 2024
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18. A0659 - Which men with cN1 prostate cancer at PSMA PET/CT represent the ideal candidate for radical prostatectomy? Development of a novel risk stratification tool for individualized approaches based on a large, multi-institutional series.
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Barletta, F.M., Mazzone, E., Gandaglia, G., Bianchi, L., Schiavina, R., Afferi, L., Mattei, A., Zanotti, F., Reitano, G., Rajwa, P., Shariat, S.F., Kesch, C., Ibanez, L., Gomez-Rivas, J., Marra, G., Guo, H., Zhuang, J., Amparore, D., Cisero, E., and Porpiglia, F.
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PROSTATE cancer patients , *RADICAL prostatectomy - Published
- 2023
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19. A0248 - The prognostic impact of preoperative psma-pet on early oncological outcomes in prostate cancer patients treated with radical prostatectomy: Results of a multi-center analysis.
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Scuderi, S.L.A., Gandaglia, G., Mazzone, E., Huebner, N., Brunocilla, E., Dal Moro, F., Sartorello, A., Ibanez, L., Jesús, M-S., Mattei, A., Afferi, L., Shariat, S., Wolfgang, F., Picchio, M., Marra, G., Zattoni, F., Reitano, G., Rajwa, P., Gomez-Rivas, J., and Kesch, C.
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PROSTATE cancer patients , *CANCER prognosis , *RADICAL prostatectomy - Published
- 2023
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20. Benchmarking of a multi-biomarker low-volume panel for Alzheimer's disease and related dementia research.
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Ibanez L, Liu M, Beric A, Timsina J, Kohlfeld P, Bergmann K, Lowery J, Sykora N, Sanchez-Montejo B, Brock W, Budde JP, Bateman RJ, Barthelemy N, Schindler SE, Holtzman DM, Benzinger TLS, Xiong C, Tarawneh R, Moulder K, Morris JC, Sung YJ, and Cruchaga C
- Abstract
Introduction: In the research setting, obtaining accurate established biomarker measurements and maximizing use of the precious samples is key. Accurate technologies are available for Alzheimer's disease (AD), but no platform can measure all the established and emerging biomarkers in one run. The NUcleic acid Linked Immuno-Sandwich Assay (NULISA) is a technology that requires 15 µL of sample to measure more than 100 analytes., Methods: We compared AD-relevant biomarkers included in the NULISA against validated assays in cerebrospinal fluid (CSF) and plasma., Results: CSF measures of amyloid beta 42/40, and phosphorylated tau (p-tau)217 are highly correlated when measured by immunoassay, mass spectrometry, or NULISA. In plasma, p-tau217 performance is similar to that reported with other technologies when predicting amyloidosis. Other biomarkers show a wide range of correlation values depending on the fluid and the platform., Discussion: The NULISA multiplexed platform produces reliable results for established biomarkers in CSF that are useful in research settings, with the advantage of measuring additional biomarkers using minimal sample volume., Highlights: We tested the novel technology NUcleic acid Linked Immuno-Sandwich Assay (NULISA) in the dementia research setting. NULISA multiplexed platform produces reliable results for established and emerging biomarkers using minimal sample volume. Cerebrospinal fluid measures of amyloid beta 42/40, and phosphorylated tau (p-tau)217 are highly correlated when measured by immunoassay, mass spectrometry, or NULISA. In plasma, p-tau217 performance is similar to that reported with other technologies when predicting amyloidosis. NULISA measures are useful in research settings, with the advantage of measuring additional biomarkers using minimal sample volume., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)
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- 2024
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21. Circulating blood circular RNA in Parkinson's Disease; from involvement in pathology to diagnostic tools in at-risk individuals.
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Beric A, Sun Y, Sanchez S, Martin C, Powell T, Kumar R, Pardo JA, Darekar G, Sanford J, Dikec D, Phillips B, Botia JA, Cruchaga C, and Ibanez L
- Abstract
To identify circRNAs associated with Parkinson's disease (PD) we leveraged two of the largest publicly available studies with longitudinal clinical and blood transcriptomic data. We performed a cross-sectional study utilizing the last visit of each participant (N = 1848), and a longitudinal analysis that included 1166 participants with at least two time points. We identified 192 differentially expressed circRNAs, with effects that were sustained during disease, in mutation carriers, and diverse ancestry. The 192 circRNAs were leveraged to distinguish between PD and healthy participants with a ROC AUC of 0.797. Further, 71 circRNAs were sufficient to distinguish between genetic PD (AUC
71 = 0.954) and, at-risk participants (AUC71 = 0.929) and healthy controls, supporting that circRNAs have the potential to aid the diagnosis of PD. Finally, we identified five circRNAs highly correlated with symptom severity. Overall, we demonstrated that circRNAs play an important role in PD and can be clinically relevant to improve diagnostic and monitoring., Competing Interests: Competing interests The funders of the study had no role in the collection, analysis, or interpretation of data; in the writing of the report; or in the decision to submit the paper for publication. C.C. is a member of the advisory board of Vivid genetics, Halia Therapeutics and ADx Healthcare and has received research support from Biogen, EISAI, Alector and Parabon. The rest of the authors report no conflict of interest., (© 2024. The Author(s).)- Published
- 2024
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22. Comparative neurofilament light chain trajectories in CSF and plasma in autosomal dominant Alzheimer's disease.
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Hofmann A, Häsler LM, Lambert M, Kaeser SA, Gräber-Sultan S, Obermüller U, Kuder-Buletta E, la Fougere C, Laske C, Vöglein J, Levin J, Fox NC, Ryan NS, Zetterberg H, Llibre-Guerra JJ, Perrin RJ, Ibanez L, Schofield PR, Brooks WS, Day GS, Farlow MR, Allegri RF, Chrem Mendez P, Ikeuchi T, Kasuga K, Lee JH, Roh JH, Mori H, Lopera F, Bateman RJ, McDade E, Gordon BA, Chhatwal JP, Jucker M, and Schultz SA
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- Humans, Male, Female, Middle Aged, Cross-Sectional Studies, Adult, Longitudinal Studies, Amyloid beta-Peptides cerebrospinal fluid, Amyloid beta-Peptides blood, Atrophy, Gray Matter pathology, Gray Matter diagnostic imaging, Aged, Positron-Emission Tomography, Disease Progression, Alzheimer Disease cerebrospinal fluid, Alzheimer Disease blood, Alzheimer Disease genetics, Alzheimer Disease diagnosis, Neurofilament Proteins blood, Neurofilament Proteins cerebrospinal fluid, Biomarkers cerebrospinal fluid, Biomarkers blood
- Abstract
Disease-modifying therapies for Alzheimer's disease (AD) are likely to be most beneficial when initiated in the presymptomatic phase. To track the benefit of such interventions, fluid biomarkers are of great importance, with neurofilament light chain protein (NfL) showing promise for monitoring neurodegeneration and predicting cognitive outcomes. Here, we update and complement previous findings from the Dominantly Inherited Alzheimer Network Observational Study by using matched cross-sectional and longitudinal cerebrospinal fluid (CSF) and plasma samples from 567 individuals, allowing timely comparative analyses of CSF and blood trajectories across the entire disease spectrum. CSF and plasma trajectories were similar at presymptomatic stages, discriminating mutation carriers from non-carrier controls 10-20 years before the estimated onset of clinical symptoms, depending on the statistical model used. However, after symptom onset the rate of change in CSF NfL continued to increase steadily, whereas the rate of change in plasma NfL leveled off. Both plasma and CSF NfL changes were associated with grey-matter atrophy, but not with Aβ-PET changes, supporting a temporal decoupling of Aβ deposition and neurodegeneration. These observations support NfL in both CSF and blood as an early marker of neurodegeneration but suggest that NfL measured in the CSF may be better suited for monitoring clinical trial outcomes in symptomatic AD patients., Competing Interests: Competing interests R.J.B. receives research funding from the US NIH, Biogen, AbbVie, Bristol Myers Squibb, Novartis, the US National Intelligence Authority, US National Institute of Neurological Disorders and Stroke, Centene, the Rainwater Foundation, the BrightFocus Foundation, the Association for Frontotemporal Degeneration Biomarkers Initiative, Coins for Alzheimer’s Research Trust Fund, the Good Ventures Foundation, Hoffman–La Roche, CogState, Signant, the Cure Alzheimer’s Research Trust Fund, Eisai, and C2N Diagnostics; receives royalties or licenses from C2N Diagnostics payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing, or educational events from the Korean Dementia Association, the American Neurological Association, Fondazione Prada, Weill Cornell Medical College, Harvard University, Beeson, and Adler Symposium. G.S.D. receives research funding from the US NIH, the Alzheimer’s Association, and the Chan–Zuckerberg Initiative; consulting fees from Parabon Nanolabs and Arialysis Therapeutics; and payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing, or educational events from PeerView Media, Continuing Education, Eli Lilly, DynaMed, and SixSense Concierge. E.M. receives research funding from the US National Intelligence Authority, Eisai, Eli Lilly, Roche, and the Gerald and Henrietta Rauenhorst Foundation; consulting fees from AstraZeneca, Sanofi, and Merck; and payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing, or educational events from the Alzheimer Association, Projects in Knowledge, and Neurology Live. H.Z. has served at scientific advisory boards and/or as a consultant for Abbvie, Acumen, Alector, Alzinova, ALZPath, Amylyx, Annexon, Apellis, Artery Therapeutics, AZTherapies, Cognito Therapeutics, CogRx, Denali, Eisai, Merry Life, Nervgen, Novo Nordisk, Optoceutics, Passage Bio, Pinteon Therapeutics, Prothena, Red Abbey Labs, reMYND, Roche, Samumed, Siemens Healthineers, Triplet Therapeutics, and Wave, has given lectures in symposia sponsored by Alzecure, Biogen, Cellectricon, Fujirebio, Lilly, Novo Nordisk, and Roche, and is a co-founder of Brain Biomarker Solutions in Gothenburg AB (BBS), which is a part of the GU Ventures Incubator Program (outside submitted work). J.L. is a consultant for and receives grants, contracts, and royalties from Eisai, Eli Lilly, the German Center of Neurodegenerative Diseases, the German Ministry for Research and Education, the Anton and Petra Ehrmann Foundation, the Luneburg Foundation, Innovationsfonds, the Michael J Fox Foundation, CurePSP, the Jerome LeJeune Foundation, the Alzheimer Forschungs Initiative, Deutsche Stiftung Down Syndrom, Else Kroner Fresenius Stiftung, and MODAG. JLlG receives research funding from the NIH-NIA, the Alzheimer’s Association, the Michael J. Fox Foundation, the Foundation for Barnes-Jewish Hospital and the McDonnell Academy. M.J. receives payment or honoraria for lectures, presentations, speakers, bureaus, manuscript writing, or educational events from Eisai. All other authors declare no competing interests., (© 2024. The Author(s).)
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- 2024
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23. Author Correction: Targeted co-expression networks for the study of traits.
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Gómez-Pascual A, Rocamora-Pérez G, Ibanez L, and Botía JA
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- 2024
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24. Proteogenomic analysis of human cerebrospinal fluid identifies neurologically relevant regulation and implicates causal proteins for Alzheimer's disease.
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Western D, Timsina J, Wang L, Wang C, Yang C, Phillips B, Wang Y, Liu M, Ali M, Beric A, Gorijala P, Kohlfeld P, Budde J, Levey AI, Morris JC, Perrin RJ, Ruiz A, Marquié M, Boada M, de Rojas I, Rutledge J, Oh H, Wilson EN, Le Guen Y, Reus LM, Tijms B, Visser PJ, van der Lee SJ, Pijnenburg YAL, Teunissen CE, Del Campo Milan M, Alvarez I, Aguilar M, Greicius MD, Pastor P, Pulford DJ, Ibanez L, Wyss-Coray T, Sung YJ, and Cruchaga C
- Abstract
The integration of quantitative trait loci (QTLs) with disease genome-wide association studies (GWASs) has proven successful in prioritizing candidate genes at disease-associated loci. QTL mapping has been focused on multi-tissue expression QTLs or plasma protein QTLs (pQTLs). We generated a cerebrospinal fluid (CSF) pQTL atlas by measuring 6,361 proteins in 3,506 samples. We identified 3,885 associations for 1,883 proteins, including 2,885 new pQTLs, demonstrating unique genetic regulation in CSF. We identified CSF-enriched pleiotropic regions on chromosome (chr)3q28 near OSTN and chr19q13.32 near APOE that were enriched for neuron specificity and neurological development. We integrated our associations with Alzheimer's disease (AD) through proteome-wide association study (PWAS), colocalization and Mendelian randomization and identified 38 putative causal proteins, 15 of which have drugs available. Finally, we developed a proteomics-based AD prediction model that outperforms genetics-based models. These findings will be instrumental to further understand the biology and identify causal and druggable proteins for brain and neurological traits., Competing Interests: Competing interests C.C. has received research support from GSK and Eisai. The funders of the study had no role in the collection, analysis or interpretation of data; in the writing of the report; or in the decision to submit the paper for publication. C.C. is a member of the advisory board of Circular Genomics and owns stocks in this company. D.J.P. is an employee of GSK and holds stock in GSK. M.d.C.M. has been an invited speaker at Eisai. M.d.C.M. is an associate editor at Alzheimer’s Research and Therapy. B.T. and P.J.V. are inventors on a patent (WO2020197399A1, owned by Stichting VUmc). C.E.T. has a collaboration contract with ADx Neurosciences, Quanterix and Eli Lilly and performed contract research or received grants from AC Immune, Axon Neuroscience, BioConnect, Bioorchestra, Brainstorm Therapeutics, Celgene, EIP Pharma, Eisai, Grifols, Novo Nordisk, PeopleBio, Roche, Toyama and Vivoryon. She serves on editorial boards of Medidact Neurologie–Springer, Alzheimer’s Research and Therapy and Neurology: Neuroimmunology and Neuroinflammation and is an editor of the Neuromethods book (Springer). She had speaker contracts for Roche, Grifols and Novo Nordisk. The rest of the authors declare no competing interest., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)
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- 2024
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25. Genetic architecture of cerebrospinal fluid and brain metabolite levels and the genetic colocalization of metabolites with human traits.
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Wang C, Yang C, Western D, Ali M, Wang Y, Phuah CL, Budde J, Wang L, Gorijala P, Timsina J, Ruiz A, Pastor P, Fernandez MV, Panyard DJ, Engelman CD, Deming Y, Boada M, Cano A, Garcia-Gonzalez P, Graff-Radford NR, Mori H, Lee JH, Perrin RJ, Ibanez L, Sung YJ, and Cruchaga C
- Abstract
Brain metabolism perturbation can contribute to traits and diseases. We conducted a genome-wide association study for cerebrospinal fluid (CSF) and brain metabolite levels, identifying 205 independent associations (47.3% new signals, containing 11 new loci) for 139 CSF metabolites, and 32 independent associations (43.8% new signals, containing 4 new loci) for 31 brain metabolites. Of these, 96.9% (CSF) and 71.4% (brain) of the new signals belonged to previously analyzed metabolites in blood or urine. We integrated the metabolite quantitative trait loci (MQTLs) with 23 neurological, psychiatric and common human traits and diseases through colocalization to identify metabolites and biological processes implicated in these phenotypes. Combining CSF and brain, we identified 71 metabolite-trait associations, such as glycerophosphocholines with Alzheimer's disease, O-sulfo-L-tyrosine with Parkinson's disease, glycine, xanthine with waist-to-hip ratio and ergothioneine with inflammatory bowel disease. Our study expanded the knowledge of MQTLs in the central nervous system, providing insights into human traits., Competing Interests: Competing interests C.C. has received research support from GSK and EISAI and is a member of the advisory board of Circular Genomics and owns stocks. A.R. and M.B. have received research support from Grifols, Roche, Araclon and Janssen. The funders of the study had no role in the collection, analysis or interpretation of data; in the writing of the report; or in the decision to submit the paper for publication. All other authors have no conflict of interest., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)
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- 2024
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26. Longitudinal associations between exercise and biomarkers in autosomal dominant Alzheimer's disease.
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Sewell KR, Doecke JD, Xiong C, Benzinger T, Masters CL, Laske C, Jucker M, Lopera F, Gordon BA, Llibre-Guerra J, Levin J, Huey ED, Hassenstab J, Schofield PR, Day GS, Fox NC, Chhatwal J, Ibanez L, Roh JH, Perrin R, Lee JH, Allegri RF, Supnet-Bell C, Berman SB, Daniels A, Noble J, Martins RN, Rainey-Smith S, Peiffer J, Gardener SL, Bateman RJ, Morris JC, McDade E, Erickson KI, Sohrabi HR, and Brown BM
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- Humans, Male, Female, Adult, Longitudinal Studies, Middle Aged, Mutation, Alzheimer Disease genetics, Biomarkers cerebrospinal fluid, Exercise physiology, Amyloid beta-Peptides cerebrospinal fluid, Positron-Emission Tomography, Magnetic Resonance Imaging, Brain diagnostic imaging, Brain pathology
- Abstract
Introduction: We investigated longitudinal associations between self-reported exercise and Alzheimer's disease (AD)-related biomarkers in individuals with autosomal dominant AD (ADAD) mutations., Methods: Participants were 308 ADAD mutation carriers aged 39.7 ± 10.8 years from the Dominantly Inherited Alzheimer's Network. Weekly exercise volume was measured via questionnaire and associations with brain volume (magnetic resonance imaging), cerebrospinal fluid biomarkers, and brain amyloid beta (Aβ) measured by positron emission tomography were investigated., Results: Greater volume of weekly exercise at baseline was associated with slower accumulation of brain Aβ at preclinical disease stages β = -0.16 [-0.23 to -0.08], and a slower decline in multiple brain regions including hippocampal volume β = 0.06 [0.03 to 0.08]., Discussion: Exercise is associated with more favorable profiles of AD-related biomarkers in individuals with ADAD mutations. Exercise may have therapeutic potential for delaying the onset of AD; however, randomized controlled trials are vital to determine a causal relationship before a clinical recommendation of exercise is implemented., Highlights: Greater self-reported weekly exercise predicts slower declines in brain volume in autosomal dominant Alzheimer's disease (ADAD). Greater self-reported weekly exercise predicts slower accumulation of brain amyloid beta in ADAD. Associations varied depending on closeness to estimated symptom onset., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)
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- 2024
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27. CSF proteomics identifies early changes in autosomal dominant Alzheimer's disease.
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Shen Y, Timsina J, Heo G, Beric A, Ali M, Wang C, Yang C, Wang Y, Western D, Liu M, Gorijala P, Budde J, Do A, Liu H, Gordon B, Llibre-Guerra JJ, Joseph-Mathurin N, Perrin RJ, Maschi D, Wyss-Coray T, Pastor P, Renton AE, Surace EI, Johnson ECB, Levey AI, Alvarez I, Levin J, Ringman JM, Allegri RF, Seyfried N, Day GS, Wu Q, Fernández MV, Tarawneh R, McDade E, Morris JC, Bateman RJ, Goate A, Ibanez L, Sung YJ, and Cruchaga C
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- Humans, Male, Female, Middle Aged, Adult, Mutation, Aged, Machine Learning, Alzheimer Disease cerebrospinal fluid, Alzheimer Disease genetics, Alzheimer Disease pathology, Alzheimer Disease metabolism, Proteomics methods, Biomarkers cerebrospinal fluid
- Abstract
In this high-throughput proteomic study of autosomal dominant Alzheimer's disease (ADAD), we sought to identify early biomarkers in cerebrospinal fluid (CSF) for disease monitoring and treatment strategies. We examined CSF proteins in 286 mutation carriers (MCs) and 177 non-carriers (NCs). The developed multi-layer regression model distinguished proteins with different pseudo-trajectories between these groups. We validated our findings with independent ADAD as well as sporadic AD datasets and employed machine learning to develop and validate predictive models. Our study identified 137 proteins with distinct trajectories between MCs and NCs, including eight that changed before traditional AD biomarkers. These proteins are grouped into three stages: early stage (stress response, glutamate metabolism, neuron mitochondrial damage), middle stage (neuronal death, apoptosis), and late presymptomatic stage (microglial changes, cell communication). The predictive model revealed a six-protein subset that more effectively differentiated MCs from NCs, compared with conventional biomarkers., Competing Interests: Declaration of interests C.C. has received research support from GSK and EISAI. C.C. is a member of the advisory board of Circular Genomics and owns stocks in these companies. C.C. is on the advisory board of ADmit. J.L. reports speaker fees from Bayer Vital, Biogen, EISAI, TEVA, Zambon, Merck, and Roche; consulting fees from Axon Neuroscience, EISAI, and Biogen; author fees from Thieme medical publishers and W. Kohlhammer GmbH medical publishers; and is inventor in a patent “Oral Phenylbutyrate for Treatment of Human 4-Repeat Tauopathies” (EP 23 156 122.6). He receives compensation for serving as chief medical officer for MODAG GmbH and is a beneficiary of the phantom share program of MODAG GmbH. E.M. reports research support received from NIA (U01AG059798), Anonymous Foundation, GHR, Alzheimer Association, Eli Lilly Eisai, and Hoffmann-La Roche and paid consulting for Eli Lilly, Alector, Alzamend, Sanofi, AstraZeneca, Hoffmann-La Roche, Grifols, and Merck., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)
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- 2024
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28. A comprehensive head-to-head comparison of key plasma phosphorylated tau 217 biomarker tests.
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Warmenhoven N, Salvadó G, Janelidze S, Mattsson-Carlgren N, Bali D, Orduña Dolado A, Kolb H, Triana-Baltzer G, Barthélemy NR, Schindler SE, Aschenbrenner AJ, Raji CA, Benzinger TLS, Morris JC, Ibanez L, Timsina J, Cruchaga C, Bateman RJ, Ashton N, Arslan B, Zetterberg H, Blennow K, Pichet Binette A, and Hansson O
- Abstract
Plasma phosphorylated-tau 217 (p-tau217) is currently the most promising biomarker for reliable detection of Alzheimer's disease (AD) pathology. Various p-tau217 assays have been developed, but their relative performance is unclear. We compared key plasma p-tau217 tests using cross-sectional and longitudinal measures of amyloid-β (Aβ)-PET, tau-PET, and cognition as outcomes, and benchmarked them against cerebrospinal fluid (CSF) biomarker tests. Samples from 998 individuals (mean[range] age 68.5[20.0-92.5], 53% female) from the Swedish BioFINDER-2 cohort, including both cognitively unimpaired and cognitively impaired individuals, were analyzed. Plasma p-tau217 was measured with mass spectrometry (MS) assays (the ratio between phosphorylated and non-phosphorylated [%p-tau217WashU] and p-tau217WashU) as well as with immunoassays (p-tau217Lilly, p-tau217Janssen, p-tau217ALZpath). CSF biomarkers included p-tau217Lilly, the FDA-approved p-tau181/Aβ42Elecsys, and p-tau181Elecsys. All plasma p-tau217 tests exhibited a high ability to detect abnormal Aβ-PET (AUC range: 0.91-0.96) and tau-PET (AUC range: 0.94-0.97). Plasma %p-tau217WashU had the highest performance, with significantly higher AUCs than all the immunoassays (Pdiff<0.007). For detecting Aβ-PET status, %p-tau217WashU had an accuracy of 0.93 (immunoassays: 0.83-0.88), sensitivity of 91% (immunoassays: 84-87%), and a specificity of 94% (immunoassays: 85-89%). Among immunoassays, p-tau217Lilly and plasma p-tau217ALZpath had higher AUCs than plasma p-tau217Janssen for Aβ-PET status (Pdiff<0.006), and p-tau217Lilly outperformed plasma p-tau217ALZpath for tau-PET status (Pdiff=0.025). Plasma %p-tau217WashU exhibited stronger associations with all PET load outcomes compared to immunoassays; baseline Aβ-PET load (R2: 0.72; immunoassays: 0.47-0.58; Pdiff<0.001), baseline tau-PET load (R2: 0.51; immunoassays: 0.38-0.45; Pdiff<0.001), longitudinal Aβ-PET load (R2: 0.53; immunoassays: 0.31-0.38; Pdiff<0.001) and longitudinal tau-PET load (R2: 0.50; immunoassays: 0.35-0.43; Pdiff<0.014). Among immunoassays, plasma p-tau217Lilly was more associated with Aβ-PET load than plasma p-tau217Janssen (Pdiff<0.020) and with tau-PET load than both plasma p-tau217Janssen and plasma p-tau217ALZpath (all Pdiff<0.010). Plasma %p-tau217 also correlated more strongly with baseline cognition (Mini-Mental State Examination[MMSE]) than all immunoassays (R2 %p-tau217WashU: 0.33; immunoassays: 0.27-0.30; Pdiff<0.024). The main results were replicated in an external cohort from Washington University in St Louis (n =219). Finally, p-tau217NULISA showed similar performance to other immunoassays in subsets of both cohorts. In summary, both MS- and immunoassay-based p-tau217 tests generally perform well in identifying Aβ-PET, tau-PET, and cognitive abnormalities, but %p-tau217WashU performed significantly better than all the examined immunoassays. Plasma %p-tau217 may be considered as a stand-alone confirmatory test for AD pathology, while some immunoassays might be better suited as triage tests where positive results are confirmed with a second test, which needs to be determined by future reviews incorporating results from multiple cohorts., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain.)
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- 2024
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29. Plasma acellular transcriptome contains Parkinson's disease signatures that can inform clinical diagnosis.
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Beric A, Cisterna-García A, Martin C, Kumar R, Alfradique-Dunham I, Boyer K, Saliu IO, Yamada S, Sanford J, Western D, Liu M, Alvarez I, Perlmutter JS, Norris SA, Pastor P, Zhao G, Botia J, and Ibanez L
- Abstract
We aimed to identify plasma cell-free transcripts (cfRNA) associated with Parkinson's disease (PD) that also have a high predictive value to differentiate PD from healthy controls. Leveraging two independent populations from two different movement disorder centers we identified 2,188 differentially expressed cfRNAs after meta-analysis. The identified transcripts were enriched in PD relevant pathways, such as PD (p=9.26×10
-4 ), ubiquitin-mediated proteolysis (p=7.41×10-5 ) and endocytosis (p=4.21×10-6 ). Utilizing in-house and publicly available brain, whole blood, and acellular plasma transcriptomic and proteomic PD datasets, we found significant overlap across dysregulated biological species in the different tissues and the different biological layers. We developed three predictive models containing increasing number of transcripts that can distinguish PD from healthy control with an area under the ROC Curve (AUC) ≥0.85. Finally, we showed that several of the predictive transcripts significantly correlate with symptom severity measured by UPDRS-III. Overall, we have demonstrated that cfRNA contains pathological signatures and has the potential to be utilized as biomarker to aid in PD diagnostics and monitoring., Competing Interests: COMPETING INTERESTS The funders of the study had no role in the collection, analysis, or interpretation of data; in the writing of the report; or in the decision to submit the paper for publication. SY is an employee of Daiichi Sankyo Co., Ltd. LI and AB are named as inventors on the invention disclosure filed in relation to this work. The rest of the authors report no conflict of interest.- Published
- 2024
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30. 15 Years of Longitudinal Genetic, Clinical, Cognitive, Imaging, and Biochemical Measures in DIAN.
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Daniels AJ, McDade E, Llibre-Guerra JJ, Xiong C, Perrin RJ, Ibanez L, Supnet-Bell C, Cruchaga C, Goate A, Renton AE, Benzinger TLS, Gordon BA, Hassenstab J, Karch C, Popp B, Levey A, Morris J, Buckles V, Allegri RF, Chrem P, Berman SB, Chhatwal JP, Farlow MR, Fox NC, Day GS, Ikeuchi T, Jucker M, Lee JH, Levin J, Lopera F, Takada L, Sosa AL, Martins R, Mori H, Noble JM, Salloway S, Huey E, Rosa-Neto P, Sánchez-Valle R, Schofield PR, Roh JH, and Bateman RJ
- Abstract
This manuscript describes and summarizes the Dominantly Inherited Alzheimer Network Observational Study (DIAN Obs), highlighting the wealth of longitudinal data, samples, and results from this human cohort study of brain aging and a rare monogenic form of Alzheimer's disease (AD). DIAN Obs is an international collaborative longitudinal study initiated in 2008 with support from the National Institute on Aging (NIA), designed to obtain comprehensive and uniform data on brain biology and function in individuals at risk for autosomal dominant AD (ADAD). ADAD gene mutations in the amyloid protein precursor ( APP ), presenilin 1 ( PSEN1 ), or presenilin 2 ( PSEN2 ) genes are deterministic causes of ADAD, with virtually full penetrance, and a predictable age at symptomatic onset. Data and specimens collected are derived from full clinical assessments, including neurologic and physical examinations, extensive cognitive batteries, structural and functional neuro-imaging, amyloid and tau pathological measures using positron emission tomography (PET), flurordeoxyglucose (FDG) PET, cerebrospinal fluid and blood collection (plasma, serum, and whole blood), extensive genetic and multi-omic analyses, and brain donation upon death. This comprehensive evaluation of the human nervous system is performed longitudinally in both mutation carriers and family non-carriers, providing one of the deepest and broadest evaluations of the human brain across decades and through AD progression. These extensive data sets and samples are available for researchers to address scientific questions on the human brain, aging, and AD.
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31. Ubiquitin-Proteasome System in the Different Stages of Dominantly Inherited Alzheimer's Disease.
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McDade E, Liu H, Bui Q, Hassenstab J, Gordon B, Benzinger T, Shen Y, Timsina J, Wang L, Sung YJ, Karch C, Renton A, Daniels A, Morris J, Xiong C, Ibanez L, Perrin R, Llibre-Guerra JJ, Day G, Supnet-Bell C, Xu X, Berman S, Chhatwal J, Ikeuchi T, Kasuga K, Niimi Y, Huey E, Schofield P, Brooks W, Ryan N, Jucker M, Laske C, Levin J, Vöglein J, Roh JH, Lopera F, Bateman R, and Cruchaga C
- Abstract
This study explored the role of the ubiquitin-proteasome system (UPS) in dominantly inherited Alzheimer's disease (DIAD) by examining changes in cerebrospinal fluid (CSF) levels of UPS proteins along with disease progression, AD imaging biomarkers (PiB PET, tau PET), neurodegeneration imaging measures (MRI, FDG PET), and Clinical Dementia Rating
® (CDR® ). Using the SOMAscan assay, we detected subtle increases in specific ubiquitin enzymes associated with proteostasis in mutation carriers (MCs) up to two decades before the estimated symptom onset. This was followed by more pronounced elevations of UPS-activating enzymes, including E2 and E3 proteins, and ubiquitin-related modifiers. Our findings also demonstrated consistent correlations between UPS proteins and CSF biomarkers such as Aβ42/40 ratio, total tau, various phosphorylated tau species to total tau ratios (ptau181/T181, ptauT205/T205, ptauS202/S202, ptauT217/T217), and MTBR-tau243, alongside Neurofilament light chain (NfL) and the CDR® . Notably, a positive association was observed with imaging markers (PiB PET, tau PET) and a negative correlation with markers of neurodegeneration (FDG PET, MRI), highlighting a significant link between UPS dysregulation and neurodegenerative processes. The correlations suggest that the increase in multiple UPS proteins with rising tau levels and tau-tangle associated markers, indicating a potential role for the UPS in relation to misfolded tau/neurofibrillary tangles (NFTs) and symptom onset. These findings indicate that elevated CSF UPS proteins in DIAD MCs could serve as early indicators of disease progression and suggest a link between UPS dysregulation and amyloid plaque, tau tangles formation, implicating the UPS as a potential therapeutic target in AD pathogenesis., Competing Interests: RJB is the Director of the DIAN-TU and Principal Investigator of DIAN and the DIAN-TU-001 trial. Unrelated to this study, for the DIAN-TU, he receives research support from the NIA, Eli Lilly and Company, F. Hoffman-La Roche, Ltd., Eisai, Alzheimer’s Association, GHR Foundation, Anonymous Organization, DIAN-TU Pharma Consortium (Active Members: Biogen, Eisai, Eli Lilly and Company, Janssen, F. Hoffmann-La Roche, Ltd./Genentech). JH is a paid consultant/advisor for Parabon Nanolabs, Roche, Prothena, and AlzPath. GYRH reports no competing interests directly relevant to this work. He has received grants or contracts from CIHR, NIA/NIH, has been a clinical trials investigator supported by Biogen, Cassava, and Lilly, has participated in expert advisory committee supported by Biogen, Roche, and NovoNordisk, and is the current president of C5R (Consortium of Canadian Centres for Clinical Cognitive Research). EMM receives Grant Funding from NIA; Institutional funding from Eli Lilly, Hoffmann-La Roche, Eisai. He is a DSMB member (paid directly) for Alector; Eli Lilly; a Scientific Advisory Board Member (paid directly to me) for Alzamend, Fondation Alzheimer. He acts as a Consultant/Advisor for Sage Therapeutics, Eli Lilly, Sanofi, AstraZeneca,Hoffmann La-Roche. CC has received research support from GSK and EISAI. The funders of the study had no role in the collection, analysis, or interpretation of data; in the writing of the report; or in the decision to submit the paper for publication. CC is a member of the advisory board of Circular Genomics and owns stocks in these companies. DP is an employee of GlaxoSmithKline (GSK) and holds stock in GSK. CX is supported by National Institute on Aging (NIA) grants R01 AG067505 and R01 AG053550. All other authors have nothing to disclose. JCM is the Friedman Distinguished Professor of Neurology, Associate Director, Knight ADRC; Associate Director of DIAN and Founding Principal Investigator of DIAN. He is funded by NIH grants # P30 AG066444; P01AG003991; P01AG026276; and U19 AG024904. Neither he nor his family owns stock or has equity interest (outside of mutual funds or other externally directed accounts) in any pharmaceutical or biotechnology company. TLSB has investigator-initiated research funding from the NIH, the Alzheimer’s Association, the Barnes-Jewish Hospital Foundation and Avid Radiopharmaceuticals. Dr. Benzinger participates as a site investigator in clinical trials sponsored by Avid Radiopharmaceuticals, Eli Lilly and Company, Biogen, Eisai, Jaansen, and F. Hoffmann-La Roche, Ltd. She also serves as an unpaid consultant to Eisai and Siemensand is on the Speaker’s Bureau for Biogen. AER reports no competing interests. He receives research support for this work from the National Institute on Aging (R01AG053267, U19AG032438) TI reports no competing interests. He received research support for this work from AMED (JP23dk0207066 and JP23dk0207049). GSD reports no competing interests directly relevant to this work. His research is supported by NIH (K23AG064029, U01AG057195, U01NS120901, U19AG032438). He serves as a consultant for Parabon Nanolabs Inc and as a Topic Editor (Dementia) for DynaMed (EBSCO). He is the co-Project PI for a clinical trial in anti-NMDAR encephalitis, which receives support from Amgen Pharmaceuticals, and a consultant for Arialys Therapeutics. He has developed educational materials for PeerView Media, Inc, and Continuing Education Inc. He owns stock in ANI pharmaceuticals. Dr. Day’s institution has received support from Eli Lilly for development and participation in an educational event promoting early diagnosis of symptomatic Alzheimer disease, and in-kind contributions of radiotracer precursors for tau-PET neuroimaging in studies of memory and aging (via Avid Radiopharmaceuticals, a wholly owned subsidiary of Eli Lilly). RJP is Neuropathology Core Leader for the DIAN observational study and the DIAN Trials Unit. He receives research support for this work from the National Institute on Aging (U19 AG032438, U19AG032438-09S1, R01AG068319). His laboratory receives cost recovery funding from Biogen for tissue procurement and processing services related to ALS clinical trials. Neither he nor his family owns stock or has equity interest (outside of mutual funds or other externally directed accounts) in any pharmaceutical or biotechnology company. FL has grants not related to this paper from NIH, DIAN, Enroll-HD and BIOGEN. JL reports speaker fees from Bayer Vital, Biogen, EISAI, TEVA, Zambon, Esteve, Merck and Roche, consulting fees from Axon Neuroscience, EISAI and Biogen, author fees from Thieme medical publishers and W. Kohlhammer GmbH medical publishers and is inventor in a patent “Oral Phenylbutyrate for Treatment of Human 4-Repeat Tauopathies” (EP 23 156 122.6) filed by LMU Munich. In addition, he reports compensation for serving as chief medical officer for MODAG GmbH, is beneficiary of the phantom share program of MODAG GmbH and is inventor in a patent “Pharmaceutical Composition and Methods of Use” (EP 22 159 408.8) filed by MODAG GmbH, all activities outside the submitted work. SBB receives support from the National Institute on Aging (NIA) and the Michael J Fox Foundation. All other authors have nothing to disclose.- Published
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32. Genetic and multi-omic resources for Alzheimer disease and related dementia from the Knight Alzheimer Disease Research Center.
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Fernandez MV, Liu M, Beric A, Johnson M, Cetin A, Patel M, Budde J, Kohlfeld P, Bergmann K, Lowery J, Flynn A, Brock W, Sanchez Montejo B, Gentsch J, Sykora N, Norton J, Gentsch J, Valdez O, Gorijala P, Sanford J, Sun Y, Wang C, Western D, Timsina J, Mangetti Goncalves T, Do AN, Sung YJ, Zhao G, Morris JC, Moulder K, Holtzman DM, Bateman RJ, Karch C, Hassenstab J, Xiong C, Schindler SE, Balls-Berry JJ, Benzinger TLS, Perrin RJ, Denny A, Snider BJ, Stark SL, Ibanez L, and Cruchaga C
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- Humans, Genomics, Biomarkers, Dementia genetics, Proteomics, Multiomics, Alzheimer Disease genetics
- Abstract
The Knight-Alzheimer Disease Research Center (Knight-ADRC) at Washington University in St. Louis has pioneered and led worldwide seminal studies that have expanded our clinical, social, pathological, and molecular understanding of Alzheimer Disease. Over more than 40 years, research volunteers have been recruited to participate in cognitive, neuropsychologic, imaging, fluid biomarkers, genomic and multi-omic studies. Tissue and longitudinal data collected to foster, facilitate, and support research on dementia and aging. The Genetics and high throughput -omics core (GHTO) have collected of more than 26,000 biological samples from 6,625 Knight-ADRC participants. Samples available include longitudinal DNA, RNA, non-fasted plasma, cerebrospinal fluid pellets, and peripheral blood mononuclear cells. The GHTO has performed deep molecular profiling (genomic, transcriptomic, epigenomic, proteomic, and metabolomic) from large number of brain (n = 2,117), CSF (n = 2,012) and blood/plasma (n = 8,265) samples with the goal of identifying novel risk and protective variants, identify novel molecular biomarkers and causal and druggable targets. Overall, the resources available at GHTO support the increase of our understanding of Alzheimer Disease., (© 2024. The Author(s).)
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- 2024
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33. Proteogenomics in cerebrospinal fluid and plasma reveals new biological fingerprint of cerebral small vessel disease.
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Debette S, Caro I, Western D, Namba S, Sun N, Kawaguchi S, He Y, Fujita M, Roshchupkin G, D'Aoust T, Duperron MG, Sargurupremraj M, Tsuchida A, Koido M, Ahmadi M, Yang C, Timsina J, Ibanez L, Matsuda K, Suzuki Y, Oda Y, Kanai A, Jandaghi P, Munter HM, Auld D, Astafeva I, Puerta R, Rotter J, Psaty B, Bis J, Longstreth W, Couffinhal T, Garcia-Gonzalez P, Pytel V, Marquié M, Cano A, Boada M, Joliot M, Lathrop M, Le Grand Q, Launer L, Wardlaw J, Heiman M, Ruiz A, Matthews P, Seshadri S, Fornage M, Adams H, Mishra A, Trégouët DA, Okada Y, Kellis M, De Jager P, Tzourio C, Kamatani Y, Matsuda F, and Cruchaga C
- Abstract
Cerebral small vessel disease (cSVD) is a leading cause of stroke and dementia with no specific mechanism-based treatment. We used Mendelian randomization to combine a unique cerebrospinal fluid (CSF) and plasma pQTL resource with the latest European-ancestry GWAS of MRI-markers of cSVD (white matter hyperintensities, perivascular spaces). We describe a new biological fingerprint of 49 protein-cSVD associations, predominantly in the CSF. We implemented a multipronged follow-up, across fluids, platforms, and ancestries (Europeans and East-Asian), including testing associations of direct plasma protein measurements with MRI-cSVD. We highlight 16 proteins robustly associated in both CSF and plasma, with 24/4 proteins identified in CSF/plasma only. cSVD-proteins were enriched in extracellular matrix and immune response pathways, and in genes enriched in microglia and specific microglial states (integration with single-nucleus RNA sequencing). Immune-related proteins were associated with MRI-cSVD already at age twenty. Half of cSVD-proteins were associated with stroke, dementia, or both, and seven cSVD-proteins are targets for known drugs (used for other indications in directions compatible with beneficial therapeutic effects. This first cSVD proteogenomic signature opens new avenues for biomarker and therapeutic developments., Competing Interests: Competing interests C.C. has received research support from GSK and EISAI and is a member of the advisory board of Circular Genomics and owns stocks in this company. CC is part of the scientific advisory board for ADmit. B.P. serves on the Steering Committee of the Yale Open Data Project funded by Johnson & Johnson. P.M.M. has received an honourarium as Chair of the UKRI Medical Research Council Neuroscience and Mental Health Board until March 2024. He acknowledges consultancy fees from, Biogen, Sudo. Nimbus and GSK. He has received speakers’ honoraria from Sanofi and Redburn, and has received research or educational funds from Biogen, Merck, Bristol Meyers Squibb and Nimbus. J.W declares no commercial COI; various academic research grants and is CI for LACunar Intervention Trials. The authors declared no potential conflicts of interest with respect to research, authorship, and/or publication of this article. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.
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34. Downstream Biomarker Effects of Gantenerumab or Solanezumab in Dominantly Inherited Alzheimer Disease: The DIAN-TU-001 Randomized Clinical Trial.
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Wagemann O, Liu H, Wang G, Shi X, Bittner T, Scelsi MA, Farlow MR, Clifford DB, Supnet-Bell C, Santacruz AM, Aschenbrenner AJ, Hassenstab JJ, Benzinger TLS, Gordon BA, Coalier KA, Cruchaga C, Ibanez L, Perrin RJ, Xiong C, Li Y, Morris JC, Lah JJ, Berman SB, Roberson ED, van Dyck CH, Galasko D, Gauthier S, Hsiung GR, Brooks WS, Pariente J, Mummery CJ, Day GS, Ringman JM, Mendez PC, St George-Hyslop P, Fox NC, Suzuki K, Okhravi HR, Chhatwal J, Levin J, Jucker M, Sims JR, Holdridge KC, Proctor NK, Yaari R, Andersen SW, Mancini M, Llibre-Guerra J, Bateman RJ, and McDade E
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- Humans, Female, Male, Double-Blind Method, Middle Aged, Adult, Amyloid beta-Peptides cerebrospinal fluid, Chitinase-3-Like Protein 1 blood, Chitinase-3-Like Protein 1 cerebrospinal fluid, Aged, Neurofilament Proteins cerebrospinal fluid, Neurofilament Proteins blood, Antibodies, Monoclonal, Humanized administration & dosage, Antibodies, Monoclonal, Humanized pharmacology, Antibodies, Monoclonal, Humanized therapeutic use, Alzheimer Disease drug therapy, Alzheimer Disease cerebrospinal fluid, Alzheimer Disease blood, Biomarkers cerebrospinal fluid, Biomarkers blood
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Importance: Effects of antiamyloid agents, targeting either fibrillar or soluble monomeric amyloid peptides, on downstream biomarkers in cerebrospinal fluid (CSF) and plasma are largely unknown in dominantly inherited Alzheimer disease (DIAD)., Objective: To investigate longitudinal biomarker changes of synaptic dysfunction, neuroinflammation, and neurodegeneration in individuals with DIAD who are receiving antiamyloid treatment., Design, Setting, and Participants: From 2012 to 2019, the Dominantly Inherited Alzheimer Network Trial Unit (DIAN-TU-001) study, a double-blind, placebo-controlled, randomized clinical trial, investigated gantenerumab and solanezumab in DIAD. Carriers of gene variants were assigned 3:1 to either drug or placebo. The present analysis was conducted from April to June 2023. DIAN-TU-001 spans 25 study sites in 7 countries. Biofluids and neuroimaging from carriers of DIAD gene variants in the gantenerumab, solanezumab, and placebo groups were analyzed., Interventions: In 2016, initial dosing of gantenerumab, 225 mg (subcutaneously every 4 weeks) was increased every 8 weeks up to 1200 mg. In 2017, initial dosing of solanezumab, 400 mg (intravenously every 4 weeks) was increased up to 1600 mg every 4 weeks., Main Outcomes and Measures: Longitudinal changes in CSF levels of neurogranin, soluble triggering receptor expressed on myeloid cells 2 (sTREM2), chitinase 3-like 1 protein (YKL-40), glial fibrillary acidic protein (GFAP), neurofilament light protein (NfL), and plasma levels of GFAP and NfL., Results: Of 236 eligible participants screened, 43 were excluded. A total of 142 participants (mean [SD] age, 44 [10] years; 72 female [51%]) were included in the study (gantenerumab, 52 [37%]; solanezumab, 50 [35%]; placebo, 40 [28%]). Relative to placebo, gantenerumab significantly reduced CSF neurogranin level at year 4 (mean [SD] β = -242.43 [48.04] pg/mL; P < .001); reduced plasma GFAP level at year 1 (mean [SD] β = -0.02 [0.01] ng/mL; P = .02), year 2 (mean [SD] β = -0.03 [0.01] ng/mL; P = .002), and year 4 (mean [SD] β = -0.06 [0.02] ng/mL; P < .001); and increased CSF sTREM2 level at year 2 (mean [SD] β = 1.12 [0.43] ng/mL; P = .01) and year 4 (mean [SD] β = 1.06 [0.52] ng/mL; P = .04). Solanezumab significantly increased CSF NfL (log) at year 4 (mean [SD] β = 0.14 [0.06]; P = .02). Correlation analysis for rates of change found stronger correlations between CSF markers and fluid markers with Pittsburgh compound B positron emission tomography for solanezumab and placebo., Conclusions and Relevance: This randomized clinical trial supports the importance of fibrillar amyloid reduction in multiple AD-related processes of neuroinflammation and neurodegeneration in CSF and plasma in DIAD. Additional studies of antiaggregated amyloid therapies in sporadic AD and DIAD are needed to determine the utility of nonamyloid biomarkers in determining disease modification., Trial Registration: ClinicalTrials.gov Identifier: NCT04623242.
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35. α-Synuclein seed amplification assay detects Lewy body co-pathology in autosomal dominant Alzheimer's disease late in the disease course and dependent on Lewy pathology burden.
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Levin J, Baiardi S, Quadalti C, Rossi M, Mammana A, Vöglein J, Bernhardt A, Perrin RJ, Jucker M, Preische O, Hofmann A, Höglinger GU, Cairns NJ, Franklin EE, Chrem P, Cruchaga C, Berman SB, Chhatwal JP, Daniels A, Day GS, Ryan NS, Goate AM, Gordon BA, Huey ED, Ibanez L, Karch CM, Lee JH, Llibre-Guerra J, Lopera F, Masters CL, Morris JC, Noble JM, Renton AE, Roh JH, Frosch MP, Keene CD, McLean C, Sanchez-Valle R, Schofield PR, Supnet-Bell C, Xiong C, Giese A, Hansson O, Bateman RJ, McDade E, and Parchi P
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- Aged, Female, Humans, Male, Middle Aged, Amyloid beta-Peptides cerebrospinal fluid, Amyloid beta-Peptides metabolism, Brain pathology, Disease Progression, Mutation, alpha-Synuclein cerebrospinal fluid, alpha-Synuclein genetics, Alzheimer Disease cerebrospinal fluid, Alzheimer Disease diagnosis, Alzheimer Disease genetics, Alzheimer Disease pathology, Lewy Bodies pathology
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Introduction: Amyloid beta and tau pathology are the hallmarks of sporadic Alzheimer's disease (AD) and autosomal dominant AD (ADAD). However, Lewy body pathology (LBP) is found in ≈ 50% of AD and ADAD brains., Methods: Using an α-synuclein seed amplification assay (SAA) in cerebrospinal fluid (CSF) from asymptomatic (n = 26) and symptomatic (n = 27) ADAD mutation carriers, including 12 with known neuropathology, we investigated the timing of occurrence and prevalence of SAA positive reactivity in ADAD in vivo., Results: No asymptomatic participant and only 11% (3/27) of the symptomatic patients tested SAA positive. Neuropathology revealed LBP in 10/12 cases, primarily affecting the amygdala or the olfactory areas. In the latter group, only the individual with diffuse LBP reaching the neocortex showed α-synuclein seeding activity in CSF in vivo., Discussion: Results suggest that in ADAD LBP occurs later than AD pathology and often as amygdala- or olfactory-predominant LBP, for which CSF α-synuclein SAA has low sensitivity., Highlights: Cerebrospinal fluid (CSF) real-time quaking-induced conversion (RT-QuIC) detects misfolded α-synuclein in ≈ 10% of symptomatic autosomal dominant Alzheimer's disease (ADAD) patients. CSF RT-QuIC does not detect α-synuclein seeding activity in asymptomatic mutation carriers. Lewy body pathology (LBP) in ADAD mainly occurs as olfactory only or amygdala-predominant variants. LBP develops late in the disease course in ADAD. CSF α-synuclein RT-QuIC has low sensitivity for focal, low-burden LBP., (© 2024 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)
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- 2024
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36. Comparison of tau spread in people with Down syndrome versus autosomal-dominant Alzheimer's disease: a cross-sectional study.
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Wisch JK, McKay NS, Boerwinkle AH, Kennedy J, Flores S, Handen BL, Christian BT, Head E, Mapstone M, Rafii MS, O'Bryant SE, Price JC, Laymon CM, Krinsky-McHale SJ, Lai F, Rosas HD, Hartley SL, Zaman S, Lott IT, Tudorascu D, Zammit M, Brickman AM, Lee JH, Bird TD, Cohen A, Chrem P, Daniels A, Chhatwal JP, Cruchaga C, Ibanez L, Jucker M, Karch CM, Day GS, Lee JH, Levin J, Llibre-Guerra J, Li Y, Lopera F, Roh JH, Ringman JM, Supnet-Bell C, van Dyck CH, Xiong C, Wang G, Morris JC, McDade E, Bateman RJ, Benzinger TLS, Gordon BA, and Ances BM
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- Male, Female, Humans, Adult, Cross-Sectional Studies, Amyloid beta-Peptides metabolism, tau Proteins metabolism, Amyloid, Magnetic Resonance Imaging methods, Positron-Emission Tomography methods, Alzheimer Disease genetics, Down Syndrome, Cognitive Dysfunction pathology
- Abstract
Background: In people with genetic forms of Alzheimer's disease, such as in Down syndrome and autosomal-dominant Alzheimer's disease, pathological changes specific to Alzheimer's disease (ie, accumulation of amyloid and tau) occur in the brain at a young age, when comorbidities related to ageing are not present. Studies including these cohorts could, therefore, improve our understanding of the early pathogenesis of Alzheimer's disease and be useful when designing preventive interventions targeted at disease pathology or when planning clinical trials. We compared the magnitude, spatial extent, and temporal ordering of tau spread in people with Down syndrome and autosomal-dominant Alzheimer's disease., Methods: In this cross-sectional observational study, we included participants (aged ≥25 years) from two cohort studies. First, we collected data from the Dominantly Inherited Alzheimer's Network studies (DIAN-OBS and DIAN-TU), which include carriers of autosomal-dominant Alzheimer's disease genetic mutations and non-carrier familial controls recruited in Australia, Europe, and the USA between 2008 and 2022. Second, we collected data from the Alzheimer Biomarkers Consortium-Down Syndrome study, which includes people with Down syndrome and sibling controls recruited from the UK and USA between 2015 and 2021. Controls from the two studies were combined into a single group of familial controls. All participants had completed structural MRI and tau PET (
18 F-flortaucipir) imaging. We applied Gaussian mixture modelling to identify regions of high tau PET burden and regions with the earliest changes in tau binding for each cohort separately. We estimated regional tau PET burden as a function of cortical amyloid burden for both cohorts. Finally, we compared the temporal pattern of tau PET burden relative to that of amyloid., Findings: We included 137 people with Down syndrome (mean age 38·5 years [SD 8·2], 74 [54%] male, and 63 [46%] female), 49 individuals with autosomal-dominant Alzheimer's disease (mean age 43·9 years [11·2], 22 [45%] male, and 27 [55%] female), and 85 familial controls, pooled from across both studies (mean age 41·5 years [12·1], 28 [33%] male, and 57 [67%] female), who satisfied the PET quality-control procedure for tau-PET imaging processing. 134 (98%) people with Down syndrome, 44 (90%) with autosomal-dominant Alzheimer's disease, and 77 (91%) controls also completed an amyloid PET scan within 3 years of tau PET imaging. Spatially, tau PET burden was observed most frequently in subcortical and medial temporal regions in people with Down syndrome, and within the medial temporal lobe in people with autosomal-dominant Alzheimer's disease. Across the brain, people with Down syndrome had greater concentrations of tau for a given level of amyloid compared with people with autosomal-dominant Alzheimer's disease. Temporally, increases in tau were more strongly associated with increases in amyloid for people with Down syndrome compared with autosomal-dominant Alzheimer's disease., Interpretation: Although the general progression of amyloid followed by tau is similar for people Down syndrome and people with autosomal-dominant Alzheimer's disease, we found subtle differences in the spatial distribution, timing, and magnitude of the tau burden between these two cohorts. These differences might have important implications; differences in the temporal pattern of tau accumulation might influence the timing of drug administration in clinical trials, whereas differences in the spatial pattern and magnitude of tau burden might affect disease progression., Funding: None., Competing Interests: Declaration of interests TLSB has received funding from the National Institutes of Health and Siemens; has a licensing agreement from Sora Neuroscience but receives no financial compensation; has received honoraria for lectures, presentations, speakers bureaus, or educational events from Biogen and Eisai Genetech; has served on a scientific advisory board for Biogen; holds a leadership role in other board, society, committee, or advocacy groups for the American Society for Neuroradiology (unpaid) and Quantitative Imaging Biomarkers Alliance (unpaid); and has participated in radiopharmaceuticals and technology transfers with Avid Radiopharmaceuticals, Cerveau, and LMI. EMD received support from the National Institute on Aging, an anonymous organisation, the GHR Foundation, the DIAN-TU Pharma Consortium, Eli Lilly, and F Hoffmann La-Roche; has received speaking fees from Eisai and Eli Lilly; and is on the data safety and monitoring board and advisory boards of Eli Lilly, Alector, and Alzamend. WS has received research funding from the National Institute on Aging and the Eunice Kennedy Shriver National Institute of Child Health and Human Development. JPC serves as the chair of the American Neurological Association Dementia and Aging Special Interest Group and is on the medical advisory board of Humana Healthcare. CC has received consulting fees from GSK and Alector. AMF reports personal fees from Roche Diagnostics, Araclon/Grifols, and Diadem Research and grants from Biogen, outside the submitted work. BLH has received research funding from Roche and Autism Speaks; receives royalties from Oxford University Press for book publications; and is the chair of the data safety and monitoring board for the US Department of Defense-funded study Comparative Effectiveness of EIBI and MABA (NCT04078061). BTC receives research funding from the National Institutes of Health. EH receives research funding from the National Institutes of Health and the BrightFocus Foundation. FL is supported by grants from the National Institute on Aging. HDR has received funding from the National Institutes of Health and is on the scientific advisory committee for the Hereditary Disease Foundation. J-HL has received research funding from the National Institutes of Health and the National Institute on Aging. RJP receives research funding from the National Institutes of Health and the National Institute on Aging. RJB is Director of DIAN-TU and Principal Investigator of DIAN-TU001; receives research support from the National Institute on Aging of the National Institutes of Health, DIAN-TU trial pharmaceutical partners (Eli Lilly, F Hoffmann-La Roche, Janssen, Eisai, Biogen, and Avid Radiopharmaceuticals), the Alzheimer's Association, the GHR Foundation, an anonymous organisation, the DIAN-TU Pharma Consortium (active members Biogen, Eisai, Eli Lilly, Janssen, and F Hoffmann-La Roche/Genentech; previous members AbbVie, Amgen, AstraZeneca, Forum, Mithridion, Novartis, Pfizer, Sanofi, and United Neuroscience), the NfL Consortium (F Hoffmann-La Roche, Biogen, AbbVie, and Bristol Myers Squibb), and the Tau SILK Consortium (Eli Lilly, Biogen, and AbbVie); has been an invited speaker and consultant for AC Immune, F Hoffmann-La Roche, the Korean Dementia Association, the American Neurological Association, and Janssen; has been a consultant for Amgen, F Hoffmann-La Roche, and Eisai; and has submitted the US non-provisional patent application named Methods for Measuring the Metabolism of CNS Derived Biomolecules In Vivo (13/005,233 [RJB and DH]) and a provisional patent application named Plasma Based Methods for Detecting CNS Amyloid Deposition (PCT/UC2018/030518 [VO and RJB]). BMA receives research funding from the National Institutes of Health and has a patent (Markers of Neurotoxicity in CAR T Patients). MSR has received consulting fees from AC Immune, Embic, and Keystone Bio and has received research support from the National Institutes of Health, Avid, Baxter, Eisai, Elan, Genentech, Janssen, Lilly, Merck, and Roche. JHR has received funding from the Korea Dementia Research Project through the Korea Dementia Research Center, funded by the Ministry of Health & Welfare and the Ministry of Science and ICT, South Korea (HU21C0066). All other authors declare no competing interests., (Copyright © 2024 Elsevier Ltd. All rights reserved.)- Published
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37. Multi-cohort cerebrospinal fluid proteomics identifies robust molecular signatures for asymptomatic and symptomatic Alzheimer's disease.
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Cruchaga C, Ali M, Shen Y, Do A, Wang L, Western D, Liu M, Beric A, Budde J, Gentsch J, Schindler S, Morris J, Holtzman D, Fernández M, Ruiz A, Alvarez I, Aguilar M, Pastor P, Rutledge J, Oh H, Wilson E, Le Guen Y, Khalid R, Robins C, Pulford D, Ibanez L, Wyss-Coray T, and Ju Sung Y
- Abstract
Changes in Amyloid-β (A), hyperphosphorylated Tau (T) in brain and cerebrospinal fluid (CSF) precedes AD symptoms, making CSF proteome a potential avenue to understand the pathophysiology and facilitate reliable diagnostics and therapies. Using the AT framework and a three-stage study design (discovery, replication, and meta-analysis), we identified 2,173 proteins dysregulated in AD, that were further validated in a third totally independent cohort. Machine learning was implemented to create and validate highly accurate and replicable (AUC>0.90) models that predict AD biomarker positivity and clinical status. These models can also identify people that will convert to AD and those AD cases with faster progression. The associated proteins cluster in four different protein pseudo-trajectories groups spanning the AD continuum and were enrichment in specific pathways including neuronal death, apoptosis and tau phosphorylation (early stages), microglia dysregulation and endolysosomal dysfuncton(mid-stages), brain plasticity and longevity (mid-stages) and late microglia-neuron crosstalk (late stages)., Competing Interests: Additional Declarations: Yes there is potential Competing Interest. CC has received research support from: GSK and EISAI. CC is a member of the scientific advisory board of Circular Genomics and owns stocks. CC is a member of the scientific advisory board of ADmit. The other co-authors have nothing to declare. CC and MA have an invention disclosure for the prediction models, including protein IDs, weights, cut off and algorithms. Competing interests CC has received research support from: GSK and EISAI. CC is a member of the scientific advisory board of Circular Genomics and owns stocks. CC is a member of the scientific advisory board of ADmit. The other co-authors have nothing to declare. CC and MA have an invention disclosures for the prediction models, including protein IDs, weights, cut off and algorithms,
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- 2024
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38. Circulating blood circular RNA in Parkinson's Disease; a systematic study.
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Beric A, Sun Y, Sanchez S, Martin C, Powell T, Adrian Pardo J, Sanford J, Botia JA, Cruchaga C, and Ibanez L
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We aimed to identify circRNAs associated with Parkinson's disease (PD) by leveraging 1,848 participants and 1,789 circRNA from two of the largest publicly available studies with longitudinal clinical and blood transcriptomic data. To comprehensively understand changes in circRNAs we performed a cross-sectional study utilizing the last visit of each participant, and a longitudinal (mix model) analysis that included 1,166 participants with at least two time points. We identified 192 circRNAs differentially expressed in PD participants compared to healthy controls, with effects that were consistent in the mixed models, mutation carriers, and diverse ancestry. Finally, we included the 149 circRNA in a model with a ROC AUC of 0.825, showing that have the potential to aid the diagnosis of PD. Overall, we demonstrated that circRNAs play an important role in PD and can be leveraged as biomarkers., Competing Interests: Competing Interests: The funders of the study had no role in the collection, analysis, or interpretation of data; in the writing of the report; or in the decision to submit the paper for publication. CC is a member of the advisory board of Vivid genetics, Halia Therapeutics and ADx Healthcare and has received research support from Biogen, EISAI, Alector and Parabon. The rest of the authors report no conflict of interest.
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39. Systematic proteomics in Autosomal dominant Alzheimer's disease reveals decades-early changes of CSF proteins in neuronal death, and immune pathways.
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Shen Y, Ali M, Timsina J, Wang C, Do A, Western D, Liu M, Gorijala P, Budde J, Liu H, Gordon B, McDade E, Morris JC, Llibre-Guerra JJ, Bateman RJ, Joseph-Mathurin N, Perrin RJ, Maschi D, Wyss-Coray T, Pastor P, Goate A, Renton AE, Surace EI, Johnson ECB, Levey AI, Alvarez I, Levin J, Ringman JM, Allegri RF, Seyfried N, Day GS, Wu Q, Fernández MV, Ibanez L, Sung YJ, and Cruchaga C
- Abstract
Background: To date, there is no high throughput proteomic study in the context of Autosomal Dominant Alzheimer's disease (ADAD). Here, we aimed to characterize early CSF proteome changes in ADAD and leverage them as potential biomarkers for disease monitoring and therapeutic strategies., Methods: We utilized Somascan® 7K assay to quantify protein levels in the CSF from 291 mutation carriers (MCs) and 185 non-carriers (NCs). We employed a multi-layer regression model to identify proteins with different pseudo-trajectories between MCs and NCs. We replicated the results using publicly available ADAD datasets as well as proteomic data from sporadic Alzheimer's disease (sAD). To biologically contextualize the results, we performed network and pathway enrichment analyses. Machine learning was applied to create and validate predictive models., Findings: We identified 125 proteins with significantly different pseudo-trajectories between MCs and NCs. Twelve proteins showed changes even before the traditional AD biomarkers (Aβ42, tau, ptau). These 125 proteins belong to three different modules that are associated with age at onset: 1) early stage module associated with stress response, glutamate metabolism, and mitochondria damage; 2) the middle stage module, enriched in neuronal death and apoptosis; and 3) the presymptomatic stage module was characterized by changes in microglia, and cell-to-cell communication processes, indicating an attempt of rebuilding and establishing new connections to maintain functionality. Machine learning identified a subset of nine proteins that can differentiate MCs from NCs better than traditional AD biomarkers (AUC>0.89)., Interpretation: Our findings comprehensively described early proteomic changes associated with ADAD and captured specific biological processes that happen in the early phases of the disease, fifteen to five years before clinical onset. We identified a small subset of proteins with the potentials to become therapy-monitoring biomarkers of ADAD MCs., Funding: Proteomic data generation was supported by NIH: RF1AG044546.
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- 2024
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40. Advanced structural brain aging in preclinical autosomal dominant Alzheimer disease.
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Millar PR, Gordon BA, Wisch JK, Schultz SA, Benzinger TL, Cruchaga C, Hassenstab JJ, Ibanez L, Karch C, Llibre-Guerra JJ, Morris JC, Perrin RJ, Supnet-Bell C, Xiong C, Allegri RF, Berman SB, Chhatwal JP, Chrem Mendez PA, Day GS, Hofmann A, Ikeuchi T, Jucker M, Lee JH, Levin J, Lopera F, Niimi Y, Sánchez-González VJ, Schofield PR, Sosa-Ortiz AL, Vöglein J, Bateman RJ, Ances BM, and McDade EM
- Subjects
- Humans, Amyloid beta-Peptides metabolism, Brain metabolism, Amyloid, Aging, Biomarkers, Positron-Emission Tomography, tau Proteins genetics, tau Proteins metabolism, Alzheimer Disease
- Abstract
Background: "Brain-predicted age" estimates biological age from complex, nonlinear features in neuroimaging scans. The brain age gap (BAG) between predicted and chronological age is elevated in sporadic Alzheimer disease (AD), but is underexplored in autosomal dominant AD (ADAD), in which AD progression is highly predictable with minimal confounding age-related co-pathology., Methods: We modeled BAG in 257 deeply-phenotyped ADAD mutation-carriers and 179 non-carriers from the Dominantly Inherited Alzheimer Network using minimally-processed structural MRI scans. We then tested whether BAG differed as a function of mutation and cognitive status, or estimated years until symptom onset, and whether it was associated with established markers of amyloid (PiB PET, CSF amyloid-β-42/40), phosphorylated tau (CSF and plasma pTau-181), neurodegeneration (CSF and plasma neurofilament-light-chain [NfL]), and cognition (global neuropsychological composite and CDR-sum of boxes). We compared BAG to other MRI measures, and examined heterogeneity in BAG as a function of ADAD mutation variants, APOE ε4 carrier status, sex, and education., Results: Advanced brain aging was observed in mutation-carriers approximately 7 years before expected symptom onset, in line with other established structural indicators of atrophy. BAG was moderately associated with amyloid PET and strongly associated with pTau-181, NfL, and cognition in mutation-carriers. Mutation variants, sex, and years of education contributed to variability in BAG., Conclusions: We extend prior work using BAG from sporadic AD to ADAD, noting consistent results. BAG associates well with markers of pTau, neurodegeneration, and cognition, but to a lesser extent, amyloid, in ADAD. BAG may capture similar signal to established MRI measures. However, BAG offers unique benefits in simplicity of data processing and interpretation. Thus, results in this unique ADAD cohort with few age-related confounds suggest that brain aging attributable to AD neuropathology can be accurately quantified from minimally-processed MRI., (© 2023. The Author(s).)
- Published
- 2023
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41. Identification of the Optimal Candidates for Nodal Staging with Extended Pelvic Lymph Node Dissection Among Prostate Cancer Patients Who Underwent Preoperative Prostate-specific Membrane Antigen Positron Emission Tomography. External Validation of the Memorial Sloan Kettering Cancer Center and Briganti Nomograms and Development of a Novel Tool.
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Gandaglia G, Barletta F, Robesti D, Scuderi S, Rajwa P, Gomez Rivas J, Ibanez L, Soeterik TFW, Bianchi L, Afferi L, Kesch C, Darr C, Guo H, Zhuang J, Zattoni F, Fendler W, Marra G, Stabile A, Amparore D, Huebner NA, Giesen A, Joniau S, Schiavina R, Brunocilla E, Mattei A, Dal Moro F, Sierra JM, Porpiglia F, Picchio M, van den Bergh R, Shariat SF, Montorsi F, and Briganti A
- Subjects
- Male, Humans, Prostate pathology, Neoplasm Staging, Lymphatic Metastasis diagnostic imaging, Lymph Node Excision methods, Positron-Emission Tomography, Nomograms, Prostatic Neoplasms diagnostic imaging, Prostatic Neoplasms surgery, Prostatic Neoplasms pathology
- Abstract
Background: Although the therapeutic role of extended pelvic lymph node dissection (ePLND) in patients with prostate cancer (PCa) is still under debate, this procedure is recommended for staging purposes in selected cases. Nomograms for predicting lymph node invasion (LNI) do not account for prostate-specific membrane antigen (PSMA) positron emission tomography (PET) imaging, which is characterized by a high negative predictive value for nodal metastases., Objective: To externally validate models predicting LNI in patients with miN0M0 PCa at PSMA PET and to develop a novel tool in this setting., Design, Setting, and Participants: Overall, 458 patients with miN0M0 disease undergoing radical prostatectomy (RP) and ePLND at 12 centers between 2017 and 2022 were identified., Outcome Measurements and Statistical Analyses: Available tools were externally validated using calibration plots, the area under the receiver operating characteristic curve (AUC), and decision curve analyses to assess calibration, discrimination, and the net benefit. A novel coefficient-based model was developed, internally validated, and compared with available tools., Results and Limitations: Overall, 53 patients (12%) had LNI. The AUC was 69% for the Briganti 2012, 64% for the Briganti 2017, 73% for the Briganti 2019, and 66% for the Memorial Sloan Kettering Cancer Center nomogram. Multiparametric magnetic resonance imaging stage, biopsy grade group 5, the diameter of the index lesion, and the percentage of positive cores at systematic biopsy were independent predictors of LNI (all p ≤ 0.04). Internal cross-validation confirmed a coefficient-based model with AUC of 78%, better calibration, and a higher net benefit in comparison to the other nomograms assessed. Use of a 5% cutoff would have spared 47% ePLND procedures (vs 13% for the Briganti 2019 nomogram) at the cost of missing only 2.1% LNI cases . The lack of central review of imaging and pathology represents the main limitation., Conclusions: Tools for predicting LNI are associated with suboptimal performance for men with miN0M0 PCa. We propose a novel model for predicting LNI that outperforms available tools in this population., Patient Summary: Tools currently used to predict lymph node invasion (LNI) in prostate cancer are not optimal for men with negative node findings on PET (positron emission tomography) scans, leading to a high number of unnecessary extended pelvic lymph node dissection (ePLND) procedures. A novel tool should be used in clinical practice to identify candidates for ePLND to reduce the risk of unnecessary procedures without missing LNI cases., (Copyright © 2023 European Association of Urology. Published by Elsevier B.V. All rights reserved.)
- Published
- 2023
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42. Cell-free RNA signatures predict Alzheimer's disease.
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Cisterna-García A, Beric A, Ali M, Pardo JA, Chen HH, Fernandez MV, Norton J, Gentsch J, Bergmann K, Budde J, Perlmutter JS, Morris JC, Cruchaga C, Botia JA, and Ibanez L
- Abstract
There is a need for affordable, scalable, and specific blood-based biomarkers for Alzheimer's disease that can be applied to a population level. We have developed and validated disease-specific cell-free transcriptomic blood-based biomarkers composed by a scalable number of transcripts that capture AD pathobiology even in the presymptomatic stages of the disease. Accuracies are in the range of the current CSF and plasma biomarkers, and specificities are high against other neurodegenerative diseases., Competing Interests: The funders of the study had no role in the collection, analysis, or interpretation of data; in the writing of the report; or in the decision to submit the paper for publication. CC is a member of the advisory board of Vivid Genetics, Halia Therapeutics, and ADx Healthcare and has received research support from Biogen, EISAI, Alector and Parabon. The rest of the authors report no conflict of interest. Patent Pending., (© 2023 The Author(s).)
- Published
- 2023
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43. Increasing hub disruption parallels dementia severity in autosomal dominant Alzheimer disease.
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Tu JC, Millar PR, Strain JF, Eck A, Adeyemo B, Daniels A, Karch C, Huey ED, McDade E, Day GS, Yakushev I, Hassenstab J, Morris J, Llibre-Guerra JJ, Ibanez L, Jucker M, Mendez PC, Bateman RJ, Perrin RJ, Benzinger T, Jack CR Jr, Betzel R, Ances BM, Eggebrecht AT, Gordon BA, and Wheelock MD
- Abstract
Hub regions in the brain, recognized for their roles in ensuring efficient information transfer, are vulnerable to pathological alterations in neurodegenerative conditions, including Alzheimer Disease (AD). Given their essential role in neural communication, disruptions to these hubs have profound implications for overall brain network integrity and functionality. Hub disruption, or targeted impairment of functional connectivity at the hubs, is recognized in AD patients. Computational models paired with evidence from animal experiments hint at a mechanistic explanation, suggesting that these hubs may be preferentially targeted in neurodegeneration, due to their high neuronal activity levels-a phenomenon termed "activity-dependent degeneration". Yet, two critical issues were unresolved. First, past research hasn't definitively shown whether hub regions face a higher likelihood of impairment (targeted attack) compared to other regions or if impairment likelihood is uniformly distributed (random attack). Second, human studies offering support for activity-dependent explanations remain scarce. We applied a refined hub disruption index to determine the presence of targeted attacks in AD. Furthermore, we explored potential evidence for activity-dependent degeneration by evaluating if hub vulnerability is better explained by global connectivity or connectivity variations across functional systems, as well as comparing its timing relative to amyloid beta deposition in the brain. Our unique cohort of participants with autosomal dominant Alzheimer Disease (ADAD) allowed us to probe into the preclinical stages of AD to determine the hub disruption timeline in relation to expected symptom emergence. Our findings reveal a hub disruption pattern in ADAD aligned with targeted attacks, detectable even in pre-clinical stages. Notably, the disruption's severity amplified alongside symptomatic progression. Moreover, since excessive local neuronal activity has been shown to increase amyloid deposition and high connectivity regions show high level of neuronal activity, our observation that hub disruption was primarily tied to regional differences in global connectivity and sequentially followed changes observed in Aβ PET cortical markers is consistent with the activity-dependent degeneration model. Intriguingly, these disruptions were discernible 8 years before the expected age of symptom onset. Taken together, our findings not only align with the targeted attack on hubs model but also suggest that activity-dependent degeneration might be the cause of hub vulnerability. This deepened understanding could be instrumental in refining diagnostic techniques and developing targeted therapeutic strategies for AD in the future., Competing Interests: Competing interests All authors report no competing interests.
- Published
- 2023
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44. Correction: Effects of half-dose spiomet treatment in girls with early puberty and accelerated bone maturation: a multicenter, randomized, placebo-controlled study protocol.
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Bassols J, de Zegher F, Diaz M, Carreras-Badosa G, Garcia-Beltran C, Puerto-Carranza E, Oliver-Vila C, Casano P, Franco CA, Malpique R, Lopez-Bermejo A, and Ibanez L
- Published
- 2023
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45. Editorial: Molecular and cellular mechanisms of synaptopathies: emerging synaptic aging-related molecular pathways in neurological disorders.
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Quintá HR, Ibanez L, Cruchaga C, and Maschi D
- Abstract
Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
- Published
- 2023
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46. Proteome wide association studies of LRRK2 variants identify novel causal and druggable proteins for Parkinson's disease.
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Phillips B, Western D, Wang L, Timsina J, Sun Y, Gorijala P, Yang C, Do A, Nykänen NP, Alvarez I, Aguilar M, Pastor P, Morris JC, Schindler SE, Fagan AM, Puerta R, García-González P, de Rojas I, Marquié M, Boada M, Ruiz A, Perlmutter JS, Ibanez L, Perrin RJ, Sung YJ, and Cruchaga C
- Abstract
Common and rare variants in the LRRK2 locus are associated with Parkinson's disease (PD) risk, but the downstream effects of these variants on protein levels remain unknown. We performed comprehensive proteogenomic analyses using the largest aptamer-based CSF proteomics study to date (7006 aptamers (6138 unique proteins) in 3107 individuals). The dataset comprised six different and independent cohorts (five using the SomaScan7K (ADNI, DIAN, MAP, Barcelona-1 (Pau), and Fundació ACE (Ruiz)) and the PPMI cohort using the SomaScan5K panel). We identified eleven independent SNPs in the LRRK2 locus associated with the levels of 25 proteins as well as PD risk. Of these, only eleven proteins have been previously associated with PD risk (e.g., GRN or GPNMB). Proteome-wide association study (PWAS) analyses suggested that the levels of ten of those proteins were genetically correlated with PD risk, and seven were validated in the PPMI cohort. Mendelian randomization analyses identified GPNMB, LCT, and CD68 causal for PD and nominate one more (ITGB2). These 25 proteins were enriched for microglia-specific proteins and trafficking pathways (both lysosome and intracellular). This study not only demonstrates that protein phenome-wide association studies (PheWAS) and trans-protein quantitative trail loci (pQTL) analyses are powerful for identifying novel protein interactions in an unbiased manner, but also that LRRK2 is linked with the regulation of PD-associated proteins that are enriched in microglial cells and specific lysosomal pathways., (© 2023. The Author(s).)
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- 2023
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47. Multi-ancestry genome-wide meta-analysis of 56,241 individuals identifies LRRC4C, LHX5-AS1 and nominates ancestry-specific loci PTPRK , GRB14 , and KIAA0825 as novel risk loci for Alzheimer's disease: the Alzheimer's Disease Genetics Consortium.
- Author
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Rajabli F, Benchek P, Tosto G, Kushch N, Sha J, Bazemore K, Zhu C, Lee WP, Haut J, Hamilton-Nelson KL, Wheeler NR, Zhao Y, Farrell JJ, Grunin MA, Leung YY, Kuksa PP, Li D, Lucio da Fonseca E, Mez JB, Palmer EL, Pillai J, Sherva RM, Song YE, Zhang X, Iqbal T, Pathak O, Valladares O, Kuzma AB, Abner E, Adams PM, Aguirre A, Albert MS, Albin RL, Allen M, Alvarez L, Apostolova LG, Arnold SE, Asthana S, Atwood CS, Ayres G, Baldwin CT, Barber RC, Barnes LL, Barral S, Beach TG, Becker JT, Beecham GW, Beekly D, Benitez BA, Bennett D, Bertelson J, Bird TD, Blacker D, Boeve BF, Bowen JD, Boxer A, Brewer J, Burke JR, Burns JM, Buxbaum JD, Cairns NJ, Cantwell LB, Cao C, Carlson CS, Carlsson CM, Carney RM, Carrasquillo MM, Chasse S, Chesselet MF, Chin NA, Chui HC, Chung J, Craft S, Crane PK, Cribbs DH, Crocco EA, Cruchaga C, Cuccaro ML, Cullum M, Darby E, Davis B, De Jager PL, DeCarli C, DeToledo J, Dick M, Dickson DW, Dombroski BA, Doody RS, Duara R, Ertekin-Taner N, Evans DA, Faber KM, Fairchild TJ, Fallon KB, Fardo DW, Farlow MR, Fernandez-Hernandez V, Ferris S, Foroud TM, Frosch MP, Fulton-Howard B, Galasko DR, Gamboa A, Gearing M, Geschwind DH, Ghetti B, Gilbert JR, Goate AM, Grabowski TJ, Graff-Radford NR, Green RC, Growdon JH, Hakonarson H, Hall J, Hamilton RL, Harari O, Hardy J, Harrell LE, Head E, Henderson VW, Hernandez M, Hohman T, Honig LS, Huebinger RM, Huentelman MJ, Hulette CM, Hyman BT, Hynan LS, Ibanez L, Jarvik GP, Jayadev S, Jin LW, Johnson K, Johnson L, Kamboh MI, Karydas AM, Katz MJ, Kauwe JS, Kaye JA, Keene CD, Khaleeq A, Kim R, Knebl J, Kowall NW, Kramer JH, Kukull WA, LaFerla FM, Lah JJ, Larson EB, Lerner A, Leverenz JB, Levey AI, Lieberman AP, Lipton RB, Logue M, Lopez OL, Lunetta KL, Lyketsos CG, Mains D, Margaret FE, Marson DC, Martin ERR, Martiniuk F, Mash DC, Masliah E, Massman P, Masurkar A, McCormick WC, McCurry SM, McDavid AN, McDonough S, McKee AC, Mesulam M, Miller BL, Miller CA, Miller JW, Montine TJ, Monuki ES, Morris JC, Mukherjee S, Myers AJ, Nguyen T, O'Bryant S, Olichney JM, Ory M, Palmer R, Parisi JE, Paulson HL, Pavlik V, Paydarfar D, Perez V, Peskind E, Petersen RC, Pierce A, Polk M, Poon WW, Potter H, Qu L, Quiceno M, Quinn JF, Raj A, Raskind M, Reiman EM, Reisberg B, Reisch JS, Ringman JM, Roberson ED, Rodriguear M, Rogaeva E, Rosen HJ, Rosenberg RN, Royall DR, Sager MA, Sano M, Saykin AJ, Schneider JA, Schneider LS, Seeley WW, Slifer SH, Small S, Smith AG, Smith JP, Sonnen JA, Spina S, St George-Hyslop P, Stern RA, Stevens AB, Strittmatter SM, Sultzer D, Swerdlow RH, Tanzi RE, Tilson JL, Trojanowski JQ, Troncoso JC, Tsuang DW, Van Deerlin VM, van Eldik LJ, Vance JM, Vardarajan BN, Vassar R, Vinters HV, Vonsattel JP, Weintraub S, Welsh-Bohmer KA, Whitehead PL, Wijsman EM, Wilhelmsen KC, Williams B, Williamson J, Wilms H, Wingo TS, Wisniewski T, Woltjer RL, Woon M, Wright CB, Wu CK, Younkin SG, Yu CE, Yu L, Zhu X, Kunkle BW, Bush WS, Wang LS, Farrer LA, Haines JL, Mayeux R, Pericak-Vance MA, Schellenberg GD, Jun GR, Reitz C, and Naj AC
- Abstract
Limited ancestral diversity has impaired our ability to detect risk variants more prevalent in non-European ancestry groups in genome-wide association studies (GWAS). We constructed and analyzed a multi-ancestry GWAS dataset in the Alzheimer's Disease (AD) Genetics Consortium (ADGC) to test for novel shared and ancestry-specific AD susceptibility loci and evaluate underlying genetic architecture in 37,382 non-Hispanic White (NHW), 6,728 African American, 8,899 Hispanic (HIS), and 3,232 East Asian individuals, performing within-ancestry fixed-effects meta-analysis followed by a cross-ancestry random-effects meta-analysis. We identified 13 loci with cross-ancestry associations including known loci at/near CR1 , BIN1 , TREM2 , CD2AP , PTK2B , CLU , SHARPIN , MS4A6A , PICALM , ABCA7 , APOE and two novel loci not previously reported at 11p12 ( LRRC4C ) and 12q24.13 ( LHX5-AS1 ). Reflecting the power of diverse ancestry in GWAS, we observed the SHARPIN locus using 7.1% the sample size of the original discovering single-ancestry GWAS (n=788,989). We additionally identified three GWS ancestry-specific loci at/near ( PTPRK ( P =2.4×10
-8 ) and GRB14 ( P =1.7×10-8 ) in HIS), and KIAA0825 ( P =2.9×10-8 in NHW). Pathway analysis implicated multiple amyloid regulation pathways (strongest with Padjusted =1.6×10-4 ) and the classical complement pathway ( Padjusted =1.3×10-3 ). Genes at/near our novel loci have known roles in neuronal development ( LRRC4C, LHX5-AS1 , and PTPRK ) and insulin receptor activity regulation ( GRB14 ). These findings provide compelling support for using traditionally-underrepresented populations for gene discovery, even with smaller sample sizes.- Published
- 2023
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48. Proteogenomic analysis of human cerebrospinal fluid identifies neurologically relevant regulation and informs causal proteins for Alzheimer's disease.
- Author
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Cruchaga C, Western D, Timsina J, Wang L, Wang C, Yang C, Ali M, Beric A, Gorijala P, Kohlfeld P, Budde J, Levey A, Morris J, Perrin R, Ruiz A, Marquié M, Boada M, de Rojas I, Rutledge J, Oh H, Wilson E, Guen YL, Alvarez I, Aguilar M, Greicius M, Pastor P, Pulford D, Ibanez L, Wyss-Coray T, Sung YJ, and Phillips B
- Abstract
The integration of quantitative trait loci (QTL) with disease genome-wide association studies (GWAS) has proven successful at prioritizing candidate genes at disease-associated loci. QTL mapping has mainly been focused on multi-tissue expression QTL or plasma protein QTL (pQTL). Here we generated the largest-to-date cerebrospinal fluid (CSF) pQTL atlas by analyzing 7,028 proteins in 3,107 samples. We identified 3,373 independent study-wide associations for 1,961 proteins, including 2,448 novel pQTLs of which 1,585 are unique to CSF, demonstrating unique genetic regulation of the CSF proteome. In addition to the established chr6p22.2-21.32 HLA region, we identified pleiotropic regions on chr3q28 near OSTN and chr19q13.32 near APOE that were enriched for neuron-specificity and neurological development. We also integrated this pQTL atlas with the latest Alzheimer's disease (AD) GWAS through PWAS, colocalization and Mendelian Randomization and identified 42 putative causal proteins for AD, 15 of which have drugs available. Finally, we developed a proteomics-based risk score for AD that outperforms genetics-based polygenic risk scores. These findings will be instrumental to further understand the biology and identify causal and druggable proteins for brain and neurological traits., Competing Interests: CC has received research support from GSK and EISAI. The funders of the study had no role in the collection, analysis, or interpretation of data; in the writing of the report; or in the decision to submit the paper for publication. CC is a member of the advisory board of Vivid Genomics and Circular Genomics and owns stocks in these companies. DP is an employee of GlaxoSmithKline (GSK) and holds stock in GSK.
- Published
- 2023
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49. KMT2D acetylation by CREBBP reveals a cooperative functional interaction at enhancers in normal and malignant germinal center B cells.
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Vlasevska S, Garcia-Ibanez L, Duval R, Holmes AB, Jahan R, Cai B, Kim A, Mo T, Basso K, Soni RK, Bhagat G, Dalla-Favera R, and Pasqualucci L
- Subjects
- Animals, Humans, Mice, Acetylation, B-Lymphocytes metabolism, CREB-Binding Protein genetics, CREB-Binding Protein metabolism, Germinal Center, Mutation, Protein Processing, Post-Translational, Lymphoma, Follicular genetics, Lymphoma, Follicular metabolism, Lymphoma, Follicular pathology, Lymphoma, Large B-Cell, Diffuse pathology
- Abstract
Heterozygous inactivating mutations of the KMT2D methyltransferase and the CREBBP acetyltransferase are among the most common genetic alterations in B cell lymphoma and co-occur in 40 to 60% of follicular lymphoma (FL) and 30% of EZB/C3 diffuse large B cell lymphoma (DLBCL) cases, suggesting they may be coselected. Here, we show that combined germinal center (GC)-specific haploinsufficiency of Crebbp and Kmt2d synergizes in vivo to promote the expansion of abnormally polarized GCs, a common preneoplastic event. These enzymes form a biochemical complex on select enhancers/superenhancers that are critical for the delivery of immune signals in the GC light zone and are only corrupted upon dual Crebbp / Kmt2d loss, both in mouse GC B cells and in human DLBCL. Moreover, CREBBP directly acetylates KMT2D in GC-derived B cells, and, consistently, its inactivation by FL/DLBCL-associated mutations abrogates its ability to catalyze KMT2D acetylation. Genetic and pharmacologic loss of CREBBP and the consequent decrease in KMT2D acetylation lead to reduced levels of H3K4me1, supporting a role for this posttranslational modification in modulating KMT2D activity. Our data identify a direct biochemical and functional interaction between CREBBP and KMT2D in the GC, with implications for their role as tumor suppressors in FL/DLBCL and for the development of precision medicine approaches targeting enhancer defects induced by their combined loss.
- Published
- 2023
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50. The impact of nature video exposure on pro-environmental behavior: An experimental investigation.
- Author
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Ibanez L and Roussel S
- Subjects
- Humans, Data Collection, Organizations
- Abstract
We analyze whether exposure to a nature documentary increases pro-environmental behavior (PEB). We test this causal link in an experiment where subjects viewed a video featuring either an urban (control treatment) or a nature setting (nature treatment). We consider two types of behavior: a monetary donation to an environmental non-governmental organization (ENGO) that we call an eco-donation, and subsequently, a non-monetary decision (i.e., recycle or not recycle headphone protectors) that we call an eco-action. We find that virtual exposure to nature boosts both eco-donation and eco-action. Interestingly, the increase in PEB only occurs for individuals who express low environmental values. We did not find any negative or positive spillover effects on the eco-action. We finally provide robustness checks and discuss policy implications., Competing Interests: NO authors have competing interests, (Copyright: © 2022 Ibanez, Roussel. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
- Published
- 2022
- Full Text
- View/download PDF
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