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1. Common and rare variant association analyses in amyotrophic lateral sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology (vol 53, pg 1636, 2021)

Author

van Rheenen, W, van der Spek, RAA, Bakker, MK, van Vugt, JJFA, Hop, PJ, Zwamborn, RAJ, de Klein, N, Westra, HJ, Bakker, OB, Deelen, P, Shireby, G, Hannon, E, Moisse, M, Baird, D, Restuadi, R, Dolzhenko, E, Dekker, AM, Gawor, K, Westeneng, HJ, Tazelaar, GHP, van Eijk, KR, Kooyman, M, Byrne, RP, Doherty, M, Heverin, M, Al Khleifat, A, Iacoangeli, A, Shatunov, A, Ticozzi, N, Cooper-Knock, J, Smith, BN, Gromicho, M, Chandran, S, Pal, S, Morrison, KE, Shaw, PJ, Hardy, J, Orrell, RW, Sendtner, M, Meyer, T, Basak, N, van der Kooi, AJ, Ratti, A, Fogh, I, Gellera, C, Lauria, G, Corti, S, Cereda, C, Sproviero, D, Soraru, G, Siciliano, G, Filosto, M, Padovani, A, Chio, A, Calvo, A, Moglia, C, Brunetti, M, Canosa, A, Grassano, M, Beghi, E, Pupillo, E, Logroscino, G, Nefussy, B, Osmanovic, A, Nordin, A, Lerner, Y, Zabari, M, Gotkine, M, Baloh, RH, Bell, S, Vourc'h, P, Corcia, P, Couratier, P, Millecamps, S, Meininger, V, Salachas, F, Pardina, JMS, Assialioui, A, Rojas-Garcia, R, Dion, PA, Ross, JP, Ludolph, AC, Weishaupt, JH, Brenner, D, Freischmidt, A, Bensimon, G, Brice, A, Durr, A, Payan, CAM, Saker-Delye, S, Wood, NW, Topp, S, Rademakers, R, Tittmann, L, Lieb, W, Franke, A, Ripke, S, Braun, A, Kraft, J, Whiteman, DC, Olsen, CM, Uitterlinden, AG, Hofman, A, Rietschel, M, Cichon, S, Nothen, MM, Amouyel, P, Comi, G, Riva, N, Lunetta, C, Gerardi, F, Cotelli, MS, Rinaldi, F, Chiveri, L, Guaita, MC, Perrone, P, Diamanti, L, Ferrarese, C, Tremolizzo, L, Delodovici, ML, Bono, G, Manera, U, Vasta, R, Bombaci, A, Casale, F, Fuda, G, Salamone, P, Iazzolino, B, Peotta, L, Cugnasco, P, De Marco, G, Torrieri, MC, Palumbo, F, Gallone, S, Barberis, M, Sbaiz, L, Gentile, S, Mauro, A, De Marchi, F, D'Alfonso, S, Bertolotto, A, Gionco, M, Leotta, D, Odddenino, E, Imperiale, D, Cavallo, R, Pignatta, P, De Mattei, M, Geda, C, Papurello, DM, Gusmaroli, G, Comi, C, Labate, C, Ruiz, L, Ferrandi, D, Rota, E, Aguggia, M, Di Vito, N, Meineri, P, Ghiglione, P, Launaro, N, Dotta, M, Di Sapio, A, Giardini, G, Tiloca, C, Peverelli, S, Taroni, F, Pensato, V, Castellotti, B, Comi, GP, Del Bo, R, Ceroni, M, Gagliardi, S, Corrado, L, Mazzini, L, Raggi, F, Simoncini, C, Lo Gerfo, A, Inghilleri, M, Ferlini, A, Simone, IL, Passarella, B, Guerra, V, Zoccolella, S, Nozzoli, C, Mundi, C, Leone, M, Zarrelli, M, Tamma, F, Valluzzi, F, Calabrese, G, Boero, G, Rini, A, Traynor, BJ, Singleton, AB, Neto, MM, Cauchi, RJ, Ophoff, RA, Wiedau-Pazos, M, Lomen-Hoerth, C, van Deerlin, VM, Grosskreutz, J, Roediger, A, Gaur, N, Jork, A, Barthel, T, Theele, E, Ilse, B, Stubendorff, B, Witte, OW, Steinbach, R, Hubner, CA, Graff, C, Brylev, L, Fominykh, V, Demeshonok, V, Ataulina, A, Rogelj, B, Koritnik, B, Zidar, J, Ravnik-Glavac, M, Glavac, D, Stevic, Z, Drory, V, Povedano, M, Blair, IP, Kiernan, MC, Benyamin, B, Henderson, RD, Furlong, S, Mathers, S, McCombe, PA, Needham, M, Ngo, ST, Nicholson, GA, Pamphlett, R, Rowe, DB, Steyn, FJ, Williams, KL, Mather, KA, Sachdev, PS, Henders, AK, Wallace, L, de Carvalho, M, Pinto, S, Petri, S, Weber, M, Rouleau, GA, Silani, V, Curtis, CJ, Breen, G, Glass, JD, Brown, RH, Landers, JE, Shaw, CE, Andersen, PM, Groen, EJN, van Es, MA, Pasterkamp, RJ, Fan, DS, Garton, FC, McRae, AF, Smith, GD, Gaunt, TR, Eberle, MA, Mill, J, McLaughlin, RL, Hardiman, O, Kenna, KP, Wray, NR, Tsai, EL, Runz, H, Franke, L, Al-Chalabi, A, Van Damme, P, van den Berg, LH, Veldink, JH, SLALOM Consortium, PARALS Consortium, SLAGEN Consortium, and SLAP Consortium

Published
2022

2. Author Correction: Common and rare variant association analyses in amyotrophic lateral sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology (Nature Genetics, (2021), 53, 12, (1636-1648), 10.1038/s41588-021-00973-1)

Author

van Rheenen, W., van der Spek, R. A. A., Bakker, M. K., van Vugt, J. J. F. A., Hop, P. J., Zwamborn, R. A. J., de Klein, N., Westra, H. -J., Bakker, O. B., Deelen, P., Shireby, G., Hannon, E., Moisse, M., Baird, D., Restuadi, R., Dolzhenko, E., Dekker, A. M., Gawor, K., Westeneng, H. -J., Tazelaar, G. H. P., van Eijk, K. R., Kooyman, M., Byrne, R. P., Doherty, M., Heverin, M., Al Khleifat, A., Iacoangeli, A., Shatunov, A., Ticozzi, N., Cooper-Knock, J., Smith, B. N., Gromicho, M., Chandran, S., Pal, S., Morrison, K. E., Shaw, P. J., Hardy, J., Orrell, R. W., Sendtner, M., Meyer, T., Basak, N., van der Kooi, A. J., Ratti, A., Fogh, I., Gellera, C., Lauria, G., Corti, S., Cereda, C., Sproviero, D., D'Alfonso, S., Soraru, G., Siciliano, G., Filosto, M., Padovani, A., Chio, A., Calvo, A., Moglia, C., Brunetti, M., Canosa, A., Grassano, M., Beghi, E., Pupillo, E., Logroscino, G., Nefussy, B., Osmanovic, A., Nordin, A., Lerner, Y., Zabari, M., Gotkine, M., Baloh, R. H., Bell, S., Vourc'H, P., Corcia, P., Couratier, P., Millecamps, S., Meininger, V., Salachas, F., Mora Pardina, J. S., Assialioui, A., Rojas-Garcia, R., Dion, P. A., Ross, J. P., Ludolph, A. C., Weishaupt, J. H., Brenner, D., Freischmidt, A., Bensimon, G., Brice, A., Durr, A., Payan, C. A. M., Saker-Delye, S., Wood, N. W., Topp, S., Rademakers, R., Tittmann, L., Lieb, W., Franke, A., Ripke, S., Braun, A., Kraft, J., Whiteman, D. C., Olsen, C. M., Uitterlinden, A. G., Hofman, A., Rietschel, M., Cichon, S., Nothen, M. M., Amouyel, P., Comi, G., Riva, N., Lunetta, C., Gerardi, F., Cotelli, M. S., Rinaldi, F., Chiveri, L., Guaita, M. C., Perrone, P., Ceroni, M., Diamanti, L., Ferrarese, C., Tremolizzo, L., Delodovici, M. L., Bono, G., Manera, U., Vasta, R., Bombaci, A., Casale, F., Fuda, G., Salamone, P., Iazzolino, B., Peotta, L., Cugnasco, P., De Marco, G., Torrieri, M. C., Palumbo, F., Gallone, S., Barberis, M., Sbaiz, L., Gentile, S., Mauro, A., Mazzini, L., De Marchi, F., Corrado, L., Bertolotto, A., Gionco, M., Leotta, D., Odddenino, E., Imperiale, D., Cavallo, R., Pignatta, P., De Mattei, M., Geda, C., Papurello, D. M., Gusmaroli, G., Comi, C., Labate, C., Ruiz, L., Ferrandi, D., Rota, E., Aguggia, M., Di Vito, N., Meineri, P., Ghiglione, P., Launaro, N., Dotta, M., Di Sapio, A., Giardini, G., Tiloca, C., Peverelli, S., Taroni, F., Pensato, V., Castellotti, B., Comi, G. P., Del Bo, R., Gagliardi, S., Raggi, F., Simoncini, C., Lo Gerfo, A., Inghilleri, M., Ferlini, A., Simone, I. L., Passarella, B., Guerra, V., Zoccolella, S., Nozzoli, C., Mundi, C., Leone, M., Zarrelli, M., Tamma, F., Valluzzi, F., Calabrese, G., Boero, G., Rini, A., Traynor, B. J., Singleton, A. B., Mitne Neto, M., Cauchi, R. J., Ophoff, R. A., Wiedau-Pazos, M., Lomen-Hoerth, C., van Deerlin, V. M., Grosskreutz, J., Roediger, A., Gaur, N., Jork, A., Barthel, T., Theele, E., Ilse, B., Stubendorff, B., Witte, O. W., Steinbach, R., Hubner, C. A., Graff, C., Brylev, L., Fominykh, V., Demeshonok, V., Ataulina, A., Rogelj, B., Koritnik, B., Zidar, J., Ravnik-Glavac, M., Glavac, D., Stevic, Z., Drory, V., Povedano, M., Blair, I. P., Kiernan, M. C., Benyamin, B., Henderson, R. D., Furlong, S., Mathers, S., Mccombe, P. A., Needham, M., Ngo, S. T., Nicholson, G. A., Pamphlett, R., Rowe, D. B., Steyn, F. J., Williams, K. L., Mather, K. A., Sachdev, P. S., Henders, A. K., Wallace, L., de Carvalho, M., Pinto, S., Petri, S., Weber, M., Rouleau, G. A., Silani, V., Curtis, C. J., Breen, G., Glass, J. D., Brown, R. H., Landers, J. E., Shaw, C. E., Andersen, P. M., Groen, E. J. N., van Es, M. A., Pasterkamp, R. J., Fan, D., Garton, F. C., Mcrae, A. F., Davey Smith, G., Gaunt, T. R., Eberle, M. A., Mill, J., Mclaughlin, R. L., Hardiman, O., Kenna, K. P., Wray, N. R., Tsai, E., Runz, H., Franke, L., Al-Chalabi, A., Van Damme, P., van den Berg, L. H., and Veldink, J. H.

Published
2022

3. Common and rare variant association analyses in amyotrophic lateral sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology

Author

Rheenen, Wouter van, Spek, Rick A. A. van der, Bakker, Mark K., Vugt, Joke J. F. A. van, Hop, Paul J., Zwamborn, Ramona A. J., Klein, Niek de, Westra, Harm Jan, Bakker, Olivier B., Deelen, Patrick, Shireby, Gemma, Needham, Merrilee, Ceroni, Mauro, Simoncini, Costanza, Gagliardi, Stella, Corrado, Lucia, Garton, Fleur C., Mazzini, Letizia, Westeneng, Henk Jan, Ross, Jay P., Valluzzi, Francesco, Aguggia, Marco, Raggi, Flavia, Rini, Augusto, Traynor, Bryan J., Singleton, Andrew B., Ngo, Shyuan T., Corcia, Philippe, Olsen, Catherine M., Hofman, Albert, Van Eijk, Kristel R., Pasterkamp, R. Jeroen, Tittmann, Lukas, Iacoangeli, Alfredo, Mitne Neto, Miguel, Sproviero, Daisy, Cauchi, Ruben J., Ophoff, Roel A., Wiedau Pazos, Martina, Lomen-Hoerth, Catherine, Deerlin, Vivianna M. van, Nicholson, Garth A., Brylev, Lev, Whiteman, David C., Grosskreutz, Julian, Fan, Dongsheng, Couratier, Philippe, Roediger, Annekathrin, Gaur, Nayana, D’alfonso, Sandra, Uitterlinden, André G., Pamphlett, Roger, Fominykh, Vera, Byrne, Ross P., Lieb, Wolfgang, Iazzolino, Barbara, Dekker, Annelot M., Slap Consortium, Demeshonok, Vera, Millecamps, Stéphanie, Ataulina, Anastasia, Rogelj, Boris, Koritnik, Blaž, Zidar, Janez, Ravnik-Glavač, Metka, Franke, Andre, Mcrae, Allan F., Rowe, Dominic B., Peotta, Laura, Cooper-Knock, Johnathan, Glavač, Damjan, Doherty, Mark, Rietschel, Marcella, Stević, Zorica, Drory, Vivian, Meininger, Vincent, Zarrelli, Michele, Povedano, Monica, Gaunt, Tom R., Steyn, Frederik J., Williams, Kelly L., Smith, Bradley N., Cugnasco, Paolo, Papurello, Diego Maria, Nozzoli, Cecilia, Sorarù, Gianni, Mather, Karen A., Ripke, Stephan, Nöthen, Markus M., Sachdev, Perminder S., Henders, Anjali K., Wallace, Leanne, Carvalho, Mamede de, Gromicho, Marta, Pinto, Susana, Marco, Giovanni de, Al Khleifat, Ahmad, Eberle, Michael A., Braun, Alice, Gusmaroli, Graziano, Siciliano, Gabriele, Petri, Susanne, Breen, Gerome, Weber, Markus, Rouleau, Guy A., Rojas García, Ricardo, Silani, Vincenzo, Amouyel, Philippe, Ghiglione, Paolo, Davey Smith, George, Curtis, Charles J., Shatunov, Aleksey, Mill, Jonathan, Mclaughlin, Russell L., Filosto, Massimiliano, Comi, Cristoforo, Gerfo, Annalisa lo, Ferlini, Alessandra, Riva, Nilo, Mora Pardina, Jesus S., Chiveri, Luca, Hardiman, Orla, Torrieri, Maria Claudia, Kenna, Kevin P., Wray, Naomi R., Tsai, Ellen, Runz, Heiko, Franke, Lude, Padovani, Alessandro, Chandran, Siddharthan, Al Chalabi, Ammar, Assialioui, Abdelilah, Labate, Carmelo, Damme, Philip van, Ticozzi, Nicola, Palumbo, Francesca, Inghilleri, Maurizio, Chiò, Adriano, Pal, Suvankar, Lunetta, Christian, Jörk, Alexander, Cichon, Sven, Kraft, Julia, Morrison, Karen E., Ruiz, Luigi, Shaw, Pamela J., Hardy, John, Orrell, Richard W., Sendtner, Michael, Meyer, Thomas, Dion, Patrick A., Calvo, Andrea, Kooyman, Maarten, Başak, Nazli, Gerardi, Francesca, Simone, Isabella L., Kooi, Anneke J. van der, Ratti, Antonia, Ferrandi, Delfina, Fogh, Isabella, Ludolph, Albert C., Moglia, Cristina, Brunetti, Maura, Diamanti, Luca, Barthel, Tabea, Blair, Ian P., Es, Michael A. van, Gallone, Salvatore, Canosa, Antonio, Guerra, Vito, Grassano, Maurizio, Beghi, Ettore, Pupillo, Elisabetta, Logroscino, Giancarlo, Ferrarese, Carlo, Nefussy, Beatrice, Theele, Erik, Rinaldi, Fabrizio, Weishaupt, Jochen H., Kiernan, Matthew C., Barberis, Marco, Osmanovic, Alma, Baloh, Robert H., Nordin, Angelica, Lerner, Yossef, Vito, Nicoletta di, Zabari, Michal, Zoccolella, Stefano, Heverin, Mark, Gotkine, Marc, Guaita, Maria Cristina, Brenner, David, Freischmidt, Axel, Sbaiz, Luca, Benyamin, Beben, Glass, Jonathan D., Landers, John E., Tazelaar, Gijs H. P., Rota, Eugenia, Bensimon, Gilbert, Ilse, Benjamin, Brice, Alexis, Durr, Alexandra, Payan, Christine A. M., Saker-Delye, Safa, Wood, Nicholas W., Gentile, Salvatore, Moisse, Matthieu, Topp, Simon, Henderson, Robert D., Rademakers, Rosa, Perrone, Patrizia, Stubendorff, Beatrice, Brown, Robert H., Restuadi, Restuadi, Tremolizzo, Lucio, Mundi, Ciro, Berg, Leonard H. van den, Passarella, Bruno, Delodovici, Maria Luisa, Furlong, Sarah, Bono, Giorgio, Manera, Umberto, Vasta, Rosario, Bombaci, Alessandro, Meineri, Piero, Mauro, Alessandro, Hannon, Eilis, Casale, Federico, Leone, Maurizio, Shaw, Christopher E., Fuda, Giuseppe, Salamone, Paolina, Mathers, Susan, Baird, Denis, Launaro, Nicola, Marchi, Fabiola de, Veldink, Jan H., Gellera, Cinzia, Salachas, François, Witte, Otto W., Andersen, Peter M., Bertolotto, Antonio, Gionco, Maurizio, Leotta, Daniela, Odddenino, Enrico, Slalom Consortium, Tamma, Filippo, Dotta, Michele, Lauria, Giuseppe, Steinbach, Robert, Imperiale, Daniele, Geda, Claudio, Dolzhenko, Egor, Cavallo, Roberto, Pignatta, Pietro, Groen, Ewout J. N., Cotelli, Maria Sofia, Mattei, Marco de, Calabrese, Gianluigi, Sapio, Alessia di, Giardini, Guido, Hübner, Christian A., Corti, Stefania, Bell, Shaughn, Comi, Giancarlo, Mccombe, Pamela A., Tiloca, Cinzia, Parals Consortium, Gawor, Klara, Peverelli, Silvia, Taroni, Franco, Pensato, Viviana, Castellotti, Barbara, Graff, Caroline, Comi, Giacomo P., Cereda, Cristina, Bo, Roberto del, Boero, Giovanni, Slagen Consortium, Vourc’h, Patrick, Stem Cell Aging Leukemia and Lymphoma (SALL), Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), van Rheenen, Wouter, van der Spek, Rick AA, Bakker, Mark K, van Vugt, Joke JFA, Benyamin, Beben, Veldink, Jan H, SLALOM Consortium, PARALS Consortium, SLAGEN Consortium, SLAP Consortium, van Rheenen, W, van der Spek, R, Bakker, M, van Vugt, J, Hop, P, Zwamborn, R, de Klein, N, Westra, H, Bakker, O, Deelen, P, Shireby, G, Hannon, E, Moisse, M, Baird, D, Restuadi, R, Dolzhenko, E, Dekker, A, Gawor, K, Westeneng, H, Tazelaar, G, van Eijk, K, Kooyman, M, Byrne, R, Doherty, M, Heverin, M, Al Khleifat, A, Iacoangeli, A, Shatunov, A, Ticozzi, N, Cooper-Knock, J, Smith, B, Gromicho, M, Chandran, S, Pal, S, Morrison, K, Shaw, P, Hardy, J, Orrell, R, Sendtner, M, Meyer, T, Basak, N, van der Kooi, A, Ratti, A, Fogh, I, Gellera, C, Lauria, G, Corti, S, Cereda, C, Sproviero, D, D'Alfonso, S, Soraru, G, Siciliano, G, Filosto, M, Padovani, A, Chio, A, Calvo, A, Moglia, C, Brunetti, M, Canosa, A, Grassano, M, Beghi, E, Pupillo, E, Logroscino, G, Nefussy, B, Osmanovic, A, Nordin, A, Lerner, Y, Zabari, M, Gotkine, M, Baloh, R, Bell, S, Vourc'H, P, Corcia, P, Couratier, P, Millecamps, S, Meininger, V, Salachas, F, Mora Pardina, J, Assialioui, A, Rojas-Garcia, R, Dion, P, Ross, J, Ludolph, A, Weishaupt, J, Brenner, D, Freischmidt, A, Bensimon, G, Brice, A, Durr, A, Payan, C, Saker-Delye, S, Wood, N, Topp, S, Rademakers, R, Tittmann, L, Lieb, W, Franke, A, Ripke, S, Braun, A, Kraft, J, Whiteman, D, Olsen, C, Uitterlinden, A, Hofman, A, Rietschel, M, Cichon, S, Nothen, M, Amouyel, P, Traynor, B, Singleton, A, Mitne Neto, M, Cauchi, R, Ophoff, R, Wiedau-Pazos, M, Lomen-Hoerth, C, van Deerlin, V, Grosskreutz, J, Roediger, A, Gaur, N, Jork, A, Barthel, T, Theele, E, Ilse, B, Stubendorff, B, Witte, O, Steinbach, R, Hubner, C, Graff, C, Brylev, L, Fominykh, V, Demeshonok, V, Ataulina, A, Rogelj, B, Koritnik, B, Zidar, J, Ravnik-Glavac, M, Glavac, D, Stevic, Z, Drory, V, Povedano, M, Blair, I, Kiernan, M, Benyamin, B, Henderson, R, Furlong, S, Mathers, S, Mccombe, P, Needham, M, Ngo, S, Nicholson, G, Pamphlett, R, Rowe, D, Steyn, F, Williams, K, Mather, K, Sachdev, P, Henders, A, Wallace, L, de Carvalho, M, Pinto, S, Petri, S, Weber, M, Rouleau, G, Silani, V, Curtis, C, Breen, G, Glass, J, Brown, R, Landers, J, Shaw, C, Andersen, P, Groen, E, van Es, M, Pasterkamp, R, Fan, D, Garton, F, Mcrae, A, Davey Smith, G, Gaunt, T, Eberle, M, Mill, J, Mclaughlin, R, Hardiman, O, Kenna, K, Wray, N, Tsai, E, Runz, H, Franke, L, Al-Chalabi, A, Van Damme, P, van den Berg, L, Veldink, J, Ferrarese, C, Neurology, ANS - Neuroinfection & -inflammation, APH - Methodology, APH - Quality of Care, EURO-NMD, Internal Medicine, Epidemiology, Başak, Ayşe Nazlı (ORCID 0000-0001-9257-3540 & YÖK ID 1512), van Rheenen, W., Van der Spek, R.A.A., Bakker, M.K., van Vugt, J.J.F.A., Hop, P.J., Zwamborn, R.A.J., de Klein, N., Westra, H.J., Bakker, O.B., Deelen, P., Shireby, G., Hannon, E., Moisse, M., Baird, D., Restuadi, R., Dolzhenko, E., Dekker, A.M., Gawor, K., Westeneng, H.J., Tazelaar, G.H.P., van Eijk, K.R., Kooyman, M., Byrne, R.P., Doherty, M., Heverin, M., Al Khleifat, A., Iacoangeli, A., Shatunov, A., Ticozzi, N., Cooper-Knock, J., Smith, B.N., Gromicho, M., Chandran, S., Pal, S., Morrison, K.E., Shaw, P.J., Hardy, J., Orrell, R.W., Sendtner, M., Meyer, T., van der Kooi, A.J., Ratti, A., Fogh, I., Gellera, C., Lauria, G., Corti, S., Cereda, C., Sproviero, D., D'Alfonso, S., Sorarù, G., Siciliano, G., Filosto, M., Padovani, A., Chiò, A., Calvo, A., Moglia, C., Brunetti, M., Canosa, A., Grassano, M., Beghi, E., Pupillo, E., Logroscino, G., Nefussy, B., Osmanovic, A., Nordin, A., Lerner, Y., Zabari, M., Gotkine, M., Baloh, R.H., Bell, S., Vourc'h, P., Corcia, P., Couratier, P., Millecamps, S., Meininger, V., Salachas, F., Mora Pardina, J.S., Assialioui, A., Rojas-García, R., Dion, P.A., Ross, J.P., Ludolph, A.C., Weishaupt, J.H., Brenner, D., Freischmidt, A., Bensimon, G., Brice, A., Durr, A., Payan, C.A.M., Saker-Delye, S., Wood, N.W., Topp, S., Rademakers, R., Tittmann, L., Lieb, W., Franke, A., Ripke, S., Kraft, J.,Whiteman, David C., Olsen, Catherine M., Uitterlinden, A.G., Hofman, A., Rietschel, M., Cichon, S., Nothen, M.M., Amouyel, P., Comi, G., Riva, N., Lunetta, C., Gerardi, F., Cotelli, M.S., Rinaldi, F., Chiveri, L., Guaita, M.C., Perrone, P., Ceroni, M., Diamanti, L., Ferrarese, C., Tremolizzo, L., Delodovici, M.L., Bono, G., Manera, U., Vasta, R., Bombaci, A., Casale, F., Fuda, G., Salamone, P., Iazzolino, B., Peotta, L., Cugnasco, P., De Marco, G., Torrieri, M.C., Palumbo, F., Gallone, S., Barberis, M., Sbaiz, L., Gentile, S., Mauro, A., Mazzini, L., De Marchi, F., Corrado, L., Bertolotto, A., Gionco, M., Leotta, D., Odddenino, E., Imperiale, D., Cavallo, R., Pignatta, P., De Mattei, M., Geda, C., Papurello, D.M., Gusmaroli, G., Comi, C., Labate, C., Ruiz, L., Ferrandi, D., Rota, E., Aguggia, M., Di Vito, N., Meineri, P., Ghiglione, P., Launaro, N., Dotta, M., Di Sapio, A., Giardini, G., Tiloca, C., Peverelli, S., Taroni, F., Pensato, V., Castellotti, B., Comi, G.P., Del Bo, R., Gagliardi, S., Raggi, F., Simoncini, C., Lo Gerfo, A., Inghilleri, M., Ferlini, A., Simone, I.L., Passarella, B., Guerra, V., Zoccolella, S., Nozzoli, C., Mundi, C., Leone, M., Zarrelli, M., Tamma, F., Valluzzi, F., Calabrese, G., Boero, G., Rini, A., Traynor, B.J., Singleton, A.B., Neto, M.M., Cauchi, R.J., Ophoff, R.A., Wiedau-Pazos, M., Lomen-Hoerth, C., van Deerlin, V.M., Grosskreutz, J., Roediger, A., Gaur, N., Jork, A., Barthel, T., Theele, E., Ilse, B., Stubendorff, B., Witte, O.W., Steinbach, R., Hubner, C.A., Graff, C., Brylev, L., Fominykh, V., Demeshonok, V., Ataulina, A., Rogelj, B., Koritnik, B., Zidar, J., Ravnik-Glavac, M., Glavac, D., Stevic, Z., Drory, V., Povedano, M., Blair, I.P., Kiernan, M.C., Benyamin, B., Henderson, R.D., Furlong, S., Mathers, S., McCombe, P.A, Needham, M., Ngo, S.T., Nicholson, G.A., Pamphlett, R., Rowe, D.B., Steyn, F.J., Williams, K.L., Mather, K.A., Sachdev, P.S., Henders, A.K., Wallace, L., de Carvalho, M., Pinto, S., Petri, S., Weber, M., Rouleau, G.A., Silani, V., Curtis, C.J., Breen, G., Glass, J.D., Brown, R.H., Landers, J.E., Shaw, C.E., Andersen, P.M., Groen, E.J.N, van Es, M.A., Pasterkamp, R.J., Fan, D.S., Garton, F.C., McRae, A.F., Smith, G.D., Gaunt, T.R., Eberle, M.A., Mill, J., McLaughlin, R.L., Hardiman, O., Kenna, K.P., Wray, N.R., Tsai, E.L., Runz, H., Franke, L., Al-Chalabi, A., Van Damme, P., van den Berg, L.H., Veldink, J.H., Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM), and School of Medicine

Subjects
Male, Genetics and heredity, amyotrophic lateral sclerosis, Neurologi, Glutamine, Medizin, Genome-wide association study, Disease, SUSCEPTIBILITY, Genome-wide association studies, DISEASE, Genètica mèdica, 0302 clinical medicine, neurodegenerative disease, genome-wide association study, ALS, gene, autophagy, Risk Factors, amyotrophic lateral sclerosi, RNA-Seq, Amyotrophic lateral sclerosis, disease-modifying therapies, blood [Cholesterol], Genetics, Genetics & Heredity, Neurons, 0303 health sciences, Medical genetics, Neurodegenerative diseases, Genome-wide association, Mendelian randomization, Frontotemporal dementia, Hexanucleotide repeat, Mutant SOD1, Metaanalysis, ALS, Susceptibility, Identification, Brain, Amyotrophic Lateral Sclerosis, Cholesterol, Disease Progression, Female, Humans, Mendelian Randomization Analysis, Microsatellite Repeats, Neurodegenerative Diseases, Quantitative Trait Loci, Genome-Wide Association Study, Mutation, MUTANT SOD1, genetics [Amyotrophic Lateral Sclerosis], medicine.anatomical_structure, Neurology, risk factor, metabolism [Neurons], MENDELIAN RANDOMIZATION, nerve cell, Life Sciences & Biomedicine, quantitative trait locu, Biology, 03 medical and health sciences, Amyotrophic lateral sclerosis -- Diagnosis, blood, ddc:570, medicine, degenerative disease, Motor neuron disease, human, Genomes, GENOME-WIDE ASSOCIATION, gene, Gene, metabolism [Glutamine], METAANALYSIS, 030304 developmental biology, Mendelian randomization analysi, Science & Technology, HEXANUCLEOTIDE REPEAT, meta analysi, IDENTIFICATION, metabolism [Amyotrophic Lateral Sclerosis], FRONTOTEMPORAL DEMENTIA, medicine.disease, metabolism [Brain], genetics [Neurodegenerative Diseases], Expression quantitative trait loci, disease exacerbation, Neuron, gemone, genetic, Vesicle-mediated transport, metabolism, Nervous system -- Degeneration, Esclerosi lateral amiotròfica, 030217 neurology & neurosurgery
Abstract

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a lifetime risk of one in 350 people and an unmet need for disease-modifying therapies. We conducted a cross-ancestry genome-wide association study (GWAS) including 29,612 patients with ALS and 122,656 controls, which identified 15 risk loci. When combined with 8,953 individuals with whole-genome sequencing (6,538 patients, 2,415 controls) and a large cortex-derived expression quantitative trait locus (eQTL) dataset (MetaBrain), analyses revealed locus-specific genetic architectures in which we prioritized genes either through rare variants, short tandem repeats or regulatory effects. ALS-associated risk loci were shared with multiple traits within the neurodegenerative spectrum but with distinct enrichment patterns across brain regions and cell types. Of the environmental and lifestyle risk factors obtained from the literature, Mendelian randomization analyses indicated a causal role for high cholesterol levels. The combination of all ALS-associated signals reveals a role for perturbations in vesicle-mediated transport and autophagy and provides evidence for cell-autonomous disease initiation in glutamatergic neurons., Dutch Research Council (NWO); VENI Scheme Grant; VIDI Grant; Prinses Beatrix Spierfonds; Neuromuscular Fellowship Grant; Medical Research Council (MRC); Clinical Infrastructure Award; Epidemiology Unit; Integrative Epidemiology Unit; Canadian Institutes of Health Research; IWT; National Institute on Aging; National Health and Medical Research Council (NHMRC); Enabling Grant; NHMRC/Australian Research Council Strategic Award; NHMRC; NHMRC Centre of Research Excellence Grant; National Health and Medical Research Council of Australia (NHMRC) Research Fellowship; United Kingdom, Medical Research Council; Economic and Social Research Council; European Union (EU); Horizon 2020; European Community's Health Seventh Framework Programme; EuroMOTOR; European Research Council (ERC); Research and Innovation Programme; EScORIAL; ALS Foundation Netherlands; Alzheimer’s Society PhD Studentship; ARSla Funding; Biogen; University of Bristol; Motor Neurone Disease Association (MNDA); NIHR Maudsley Biomedical Research Centre; Dutch Ministry of Education, Culture, and Science; Netherlands Organization for Scientific Research (NWO; BRAINSCAPES); Gravitation Program; ALS Liga België; National Lottery of Belgium; KU Leuven Opening the Future Fund; KU Leuven Funds, “Een Hart voor ALS”, “Laeversfonds voor ALS Onderzoek” and the “Valéry Perrier Race against ALS Fund”; E. von Behring Chair for Neuromuscular and Neurodegenerative Disorders; ALS Liga België; “Live now” Charity Foundation; Moscow ALS palliative Care Service; Canadian Institutes of Health; Research Australia; Ice Bucket Challenge Grant; NIH Intramural Research Programs; FightMND Mid-Career Fellowship; NIHR Senior Investigator; Sheffield NIHR Biomedical Research Centre; Motor Neurone Disease Association; National Institute for Health Research (NIHR) Biomedical Research Centre; Maudsley NHS Foundation Trust; King’s College London; NIHR Senior Investigator Award; Netherlands Organization for Health Research and Development; Vici Scheme; Netherlands Organization for Health Research and Development STRENGTH Project; PPP Allowance

Published
2021

4. Blood-based multivariate methylation risk score for cognitive impairment and dementia.

Author

Koetsier J, Cavill R, Reijnders R, Harvey J, Homann J, Kouhsar M, Deckers K, Köhler S, Eijssen LMT, van den Hove DLA, Demuth I, Düzel S, Smith RG, Smith AR, Burrage J, Walker EM, Shireby G, Hannon E, Dempster E, Frayling T, Mill J, Dobricic V, Johannsen P, Wittig M, Franke A, Vandenberghe R, Schaeverbeke J, Freund-Levi Y, Frölich L, Scheltens P, Teunissen CE, Frisoni G, Blin O, Richardson JC, Bordet R, Engelborghs S, de Roeck E, Martinez-Lage P, Tainta M, Lleó A, Sala I, Popp J, Peyratout G, Verhey F, Tsolaki M, Andreasson U, Blennow K, Zetterberg H, Streffer J, Vos SJB, Lovestone S, Visser PJ, Lill CM, Bertram L, Lunnon K, and Pishva E

Abstract

Introduction: The established link between DNA methylation and pathophysiology of dementia, along with its potential role as a molecular mediator of lifestyle and environmental influences, positions blood-derived DNA methylation as a promising tool for early dementia risk detection., Methods: In conjunction with an extensive array of machine learning techniques, we employed whole blood genome-wide DNA methylation data as a surrogate for 14 modifiable and non-modifiable factors in the assessment of dementia risk in independent dementia cohorts., Results: We established a multivariate methylation risk score (MMRS) for identifying mild cognitive impairment cross-sectionally, independent of age and sex (P = 2.0 × 10 -3 ). This score significantly predicted the prospective development of cognitive impairments in independent studies of Alzheimer's disease (hazard ratio for Rey's Auditory Verbal Learning Test (RAVLT)-Learning = 2.47) and Parkinson's disease (hazard ratio for MCI/dementia   = 2.59)., Discussion: Our work shows the potential of employing blood-derived DNA methylation data in the assessment of dementia risk., Highlights: We used whole blood DNA methylation as a surrogate for 14 dementia risk factors. Created a multivariate methylation risk score for predicting cognitive impairment. Emphasized the role of machine learning and omics data in predicting dementia. The score predicts cognitive impairment development at the population level., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Published
2024
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5. Genetic architecture of epigenetic cortical clock age in brain tissue from older individuals: alterations in CD46 and other loci.

Author

Grodstein F, Lemos B, Yang J, de Paiva Lopes K, Vialle RA, Seyfried N, Wang Y, Shireby G, Hannon E, Thomas A, Brookes K, Mill J, De Jager PL, and Bennett DA

Subjects
Humans, Female, Male, Aged, Aged, 80 and over, Quantitative Trait Loci, Cerebral Cortex metabolism, Brain metabolism, Epigenesis, Genetic, Polymorphism, Single Nucleotide, Aging genetics, Genome-Wide Association Study
Abstract

The cortical epigenetic clock was developed in brain tissue as a biomarker of brain aging. As one way to identify mechanisms underlying aging, we conducted a GWAS of cortical age. We leveraged postmortem cortex tissue and genotyping array data from 694 participants of the Rush Memory and Aging Project and Religious Orders Study (ROSMAP; 11000,000 SNPs), and meta-analysed ROSMAP with 522 participants of Brains for Dementia Research (5,000,000 overlapping SNPs). We confirmed results using eQTL (cortical bulk and single nucleus gene expression), cortical protein levels (ROSMAP), and phenome-wide association studies (clinical/neuropathologic phenotypes, ROSMAP). In the meta-analysis, the strongest association was rs4244620 ( p  = 1.29 × 10 -7 ), which also exhibited FDR-significant cis-eQTL effects for CD46 in bulk and single nucleus (microglia, astrocyte, oligodendrocyte, neuron) cortical gene expression. Additionally, rs4244620 was nominally associated with lower cognition, faster slopes of cognitive decline, and greater Parkinsonian signs (n ~ 1700 ROSMAP with SNP/phenotypic data; all p  ≤ 0.04). In ROSMAP alone, the top SNP was rs4721030 ( p  = 8.64 × 10 -8 ) annotated to TMEM106B and THSD7A . Further, in ROSMAP ( n  = 849), TMEM106B and THSD7A protein levels in cortex were related to many phenotypes, including greater AD pathology and lower cognition (all p  ≤ 0.0007). Overall, we identified converging evidence of CD46 and possibly TMEM106B/THSD7A for potential roles in cortical epigenetic clock age.

Published
2024
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6. Accelerated Pace of Aging in Schizophrenia: Five Case-Control Studies.

Author

Caspi A, Shireby G, Mill J, Moffitt TE, Sugden K, and Hannon E

Subjects
Humans, Case-Control Studies, Female, Male, Adult, Middle Aged, Young Adult, Schizophrenia genetics, DNA Methylation, Aging
Abstract

Background: Schizophrenia is associated with increased risk of developing multiple aging-related diseases, including metabolic, respiratory, and cardiovascular diseases, and Alzheimer's and related dementias, leading to the hypothesis that schizophrenia is accompanied by accelerated biological aging. This has been difficult to test because there is no widely accepted measure of biological aging. Epigenetic clocks are promising algorithms that are used to calculate biological age on the basis of information from combined cytosine-phosphate-guanine sites (CpGs) across the genome, but they have yielded inconsistent and often negative results about the association between schizophrenia and accelerated aging. Here, we tested the schizophrenia-aging hypothesis using a DNA methylation measure that is uniquely designed to predict an individual's rate of aging., Methods: We brought together 5 case-control datasets to calculate DunedinPACE (Pace of Aging Calculated from the Epigenome), a new measure trained on longitudinal data to detect differences between people in their pace of aging over time. Data were available from 1812 psychosis cases (schizophrenia or first-episode psychosis) and 1753 controls. Mean chronological age was 38.9 (SD = 13.6) years., Results: We observed consistent associations across datasets between schizophrenia and accelerated aging as measured by DunedinPACE. These associations were not attributable to tobacco smoking or clozapine medication., Conclusions: Schizophrenia is accompanied by accelerated biological aging by midlife. This may explain the wide-ranging risk among people with schizophrenia for developing multiple different age-related physical diseases, including metabolic, respiratory, and cardiovascular diseases, and dementia. Measures of biological aging could prove valuable for assessing patients' risk for physical and cognitive decline and for evaluating intervention effectiveness., (Copyright © 2023 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Published
2024
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7. Uncertainty quantification of reference-based cellular deconvolution algorithms.

Author

Vellame DS, Shireby G, MacCalman A, Dempster EL, Burrage J, Gorrie-Stone T, Schalkwyk LS, Mill J, and Hannon E

Subjects
Female, Infant, Newborn, Humans, Uncertainty, Computational Biology methods, Epigenomics, DNA Methylation, Algorithms
Abstract

The majority of epigenetic epidemiology studies to date have generated genome-wide profiles from bulk tissues (e.g., whole blood) however these are vulnerable to confounding from variation in cellular composition. Proxies for cellular composition can be mathematically derived from the bulk tissue profiles using a deconvolution algorithm; however, there is no method to assess the validity of these estimates for a dataset where the true cellular proportions are unknown. In this study, we describe, validate and characterize a sample level accuracy metric for derived cellular heterogeneity variables. The CETYGO score captures the deviation between a sample's DNA methylation profile and its expected profile given the estimated cellular proportions and cell type reference profiles. We demonstrate that the CETYGO score consistently distinguishes inaccurate and incomplete deconvolutions when applied to reconstructed whole blood profiles. By applying our novel metric to >6,300 empirical whole blood profiles, we find that estimating accurate cellular composition is influenced by both technical and biological variation. In particular, we show that when using a common reference panel for whole blood, less accurate estimates are generated for females, neonates, older individuals and smokers. Our results highlight the utility of a metric to assess the accuracy of cellular deconvolution, and describe how it can enhance studies of DNA methylation that are reliant on statistical proxies for cellular heterogeneity. To facilitate incorporating our methodology into existing pipelines, we have made it freely available as an R package (https://github.com/ds420/CETYGO).

Published
2023
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8. Epigenetic age acceleration is associated with oligodendrocyte proportions in MSA and control brain tissue.

Author

Murthy M, Shireby G, Miki Y, Viré E, Lashley T, Warner TT, Mill J, and Bettencourt C

Subjects
Humans, Brain metabolism, Gray Matter metabolism, Oligodendroglia metabolism, DNA Methylation, Epigenesis, Genetic, Multiple System Atrophy metabolism
Abstract

Aims: Epigenetic clocks are widely applied as surrogates for biological age in different tissues and/or diseases, including several neurodegenerative diseases. Despite white matter (WM) changes often being observed in neurodegenerative diseases, no study has investigated epigenetic ageing in white matter., Methods: We analysed the performances of two DNA methylation-based clocks, DNAmClock Multi and DNAmClock Cortical , in post-mortem WM tissue from multiple subcortical regions and the cerebellum, and in oligodendrocyte-enriched nuclei. We also examined epigenetic ageing in control and multiple system atrophy (MSA) (WM and mixed WM and grey matter), as MSA is a neurodegenerative disease comprising pronounced WM changes and α-synuclein aggregates in oligodendrocytes., Results: Estimated DNA methylation (DNAm) ages showed strong correlations with chronological ages, even in WM (e.g., DNAmClock Cortical , r = [0.80-0.97], p < 0.05). However, performances and DNAm age estimates differed between clocks and brain regions. DNAmClock Multi significantly underestimated ages in all cohorts except in the MSA prefrontal cortex mixed tissue, whereas DNAmClock Cortical tended towards age overestimations. Pronounced age overestimations in the oligodendrocyte-enriched cohorts (e.g., oligodendrocyte-enriched nuclei, p = 6.1 × 10 -5 ) suggested that this cell type ages faster. Indeed, significant positive correlations were observed between estimated oligodendrocyte proportions and DNAm age acceleration estimated by DNAmClock Cortical (r > 0.31, p < 0.05), and similar trends were obtained with DNAmClock Multi . Although increased age acceleration was observed in MSA compared with controls, no significant differences were detected upon adjustment for possible confounders (e.g., cell-type proportions)., Conclusions: Our findings show that oligodendrocyte proportions positively influence epigenetic age acceleration across brain regions and highlight the need to further investigate this in ageing and neurodegeneration., (© 2022 The Authors. Neuropathology and Applied Neurobiology published by John Wiley & Sons Ltd on behalf of British Neuropathological Society.)

Published
2023
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9. Machine learning-based prediction of cognitive outcomes in de novo Parkinson's disease.

Author

Harvey J, Reijnders RA, Cavill R, Duits A, Köhler S, Eijssen L, Rutten BPF, Shireby G, Torkamani A, Creese B, Leentjens AFG, Lunnon K, and Pishva E

Abstract

Cognitive impairment is a debilitating symptom in Parkinson's disease (PD). We aimed to establish an accurate multivariate machine learning (ML) model to predict cognitive outcome in newly diagnosed PD cases from the Parkinson's Progression Markers Initiative (PPMI). Annual cognitive assessments over an 8-year time span were used to define two cognitive outcomes of (i) cognitive impairment, and (ii) dementia conversion. Selected baseline variables were organized into three subsets of clinical, biofluid and genetic/epigenetic measures and tested using four different ML algorithms. Irrespective of the ML algorithm used, the models consisting of the clinical variables performed best and showed better prediction of cognitive impairment outcome over dementia conversion. We observed a marginal improvement in the prediction performance when clinical, biofluid, and epigenetic/genetic variables were all included in one model. Several cerebrospinal fluid measures and an epigenetic marker showed high predictive weighting in multiple models when included alongside clinical variables., (© 2022. The Author(s).)

Published
2022
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10. A comparison of blood and brain-derived ageing and inflammation-related DNA methylation signatures and their association with microglial burdens.

Author

Stevenson AJ, McCartney DL, Gadd DA, Shireby G, Hillary RF, King D, Tzioras M, Wrobel N, McCafferty S, Murphy L, McColl BW, Redmond P, Taylor AM, Harris SE, Russ TC, McIntosh AM, Mill J, Smith C, Deary IJ, Cox SR, Marioni RE, and Spires-Jones TL

Subjects
Humans, Microglia, Epigenesis, Genetic, Brain, Inflammation genetics, Biomarkers, DNA Methylation, Neurodegenerative Diseases
Abstract

Inflammation and ageing-related DNA methylation patterns in the blood have been linked to a variety of morbidities, including cognitive decline and neurodegenerative disease. However, it is unclear how these blood-based patterns relate to patterns within the brain and how each associates with central cellular profiles. In this study, we profiled DNA methylation in both the blood and in five post mortem brain regions (BA17, BA20/21, BA24, BA46 and hippocampus) in 14 individuals from the Lothian Birth Cohort 1936. Microglial burdens were additionally quantified in the same brain regions. DNA methylation signatures of five epigenetic ageing biomarkers ('epigenetic clocks'), and two inflammatory biomarkers (methylation proxies for C-reactive protein and interleukin-6) were compared across tissues and regions. Divergent associations between the inflammation and ageing signatures in the blood and brain were identified, depending on region assessed. Four out of the five assessed epigenetic age acceleration measures were found to be highest in the hippocampus (β range = 0.83-1.14, p ≤ 0.02). The inflammation-related DNA methylation signatures showed no clear variation across brain regions. Reactive microglial burdens were found to be highest in the hippocampus (β = 1.32, p = 5 × 10 -4 ); however, the only association identified between the blood- and brain-based methylation signatures and microglia was a significant positive association with acceleration of one epigenetic clock (termed DNAm PhenoAge) averaged over all five brain regions (β = 0.40, p = 0.002). This work highlights a potential vulnerability of the hippocampus to epigenetic ageing and provides preliminary evidence of a relationship between DNA methylation signatures in the brain and differences in microglial burdens., (© 2022 The Authors. European Journal of Neuroscience published by Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

Published
2022
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11. DNA methylation signatures of Alzheimer's disease neuropathology in the cortex are primarily driven by variation in non-neuronal cell-types.

Author

Shireby G, Dempster EL, Policicchio S, Smith RG, Pishva E, Chioza B, Davies JP, Burrage J, Lunnon K, Seiler Vellame D, Love S, Thomas A, Brookes K, Morgan K, Francis P, Hannon E, and Mill J

Subjects
DNA Methylation genetics, Epigenesis, Genetic, Humans, Neurofibrillary Tangles genetics, Neurofibrillary Tangles metabolism, Alzheimer Disease metabolism, Neurodegenerative Diseases genetics
Abstract

Alzheimer's disease (AD) is a chronic neurodegenerative disease characterized by the progressive accumulation of amyloid-beta and neurofibrillary tangles of tau in the neocortex. We profiled DNA methylation in two regions of the cortex from 631 donors, performing an epigenome-wide association study of multiple measures of AD neuropathology. We meta-analyzed our results with those from previous studies of DNA methylation in AD cortex (total n = 2013 donors), identifying 334 cortical differentially methylated positions (DMPs) associated with AD pathology including methylomic variation at loci not previously implicated in dementia. We subsequently profiled DNA methylation in NeuN+ (neuronal-enriched), SOX10+ (oligodendrocyte-enriched) and NeuN-/SOX10- (microglia- and astrocyte-enriched) nuclei, finding that the majority of DMPs identified in 'bulk' cortex tissue reflect DNA methylation differences occurring in non-neuronal cells. Our study highlights the power of utilizing multiple measures of neuropathology to identify epigenetic signatures of AD and the importance of characterizing disease-associated variation in purified cell-types., (© 2022. The Author(s).)

Published
2022
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12. Evaluation of nanopore sequencing for epigenetic epidemiology: a comparison with DNA methylation microarrays.

Author

Flynn R, Washer S, Jeffries AR, Andrayas A, Shireby G, Kumari M, Schalkwyk LC, Mill J, and Hannon E

Subjects
CpG Islands genetics, Epigenesis, Genetic genetics, Epigenomics, Humans, DNA Methylation genetics, Nanopore Sequencing
Abstract

Most epigenetic epidemiology to date has utilized microarrays to identify positions in the genome where variation in DNA methylation is associated with environmental exposures or disease. However, these profile less than 3% of DNA methylation sites in the human genome, potentially missing affected loci and preventing the discovery of disrupted biological pathways. Third generation sequencing technologies, including Nanopore sequencing, have the potential to revolutionize the generation of epigenetic data, not only by providing genuine genome-wide coverage but profiling epigenetic modifications direct from native DNA. Here we assess the viability of using Nanopore sequencing for epidemiology by performing a comparison with DNA methylation quantified using the most comprehensive microarray available, the Illumina EPIC array. We implemented a CRISPR-Cas9 targeted sequencing approach in concert with Nanopore sequencing to profile DNA methylation in three genomic regions to attempt to rediscover genomic positions that existing technologies have shown are differentially methylated in tobacco smokers. Using Nanopore sequencing reads, DNA methylation was quantified at 1779 CpGs across three regions, providing a finer resolution of DNA methylation patterns compared to the EPIC array. The correlation of estimated levels of DNA methylation between platforms was high. Furthermore, we identified 12 CpGs where hypomethylation was significantly associated with smoking status, including 10 within the AHRR gene. In summary, Nanopore sequencing is a valid option for identifying genomic loci where large differences in DNAm are associated with a phenotype and has the potential to advance our understanding of the role differential methylation plays in the etiology of complex disease., (© The Author(s) 2022. Published by Oxford University Press.)

Published
2022
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13. Epigenome-wide association study of human frontal cortex identifies differential methylation in Lewy body pathology.

Author

Pihlstrøm L, Shireby G, Geut H, Henriksen SP, Rozemuller AJM, Tunold JA, Hannon E, Francis P, Thomas AJ, Love S, Mill J, van de Berg WDJ, and Toft M

Subjects
Epigenome, Frontal Lobe pathology, Humans, Lewy Bodies metabolism, Methylation, alpha-Synuclein genetics, alpha-Synuclein metabolism, Lewy Body Disease genetics, Parkinson Disease genetics, Parkinson Disease metabolism
Abstract

Parkinson's disease (PD) and dementia with Lewy bodies (DLB) are closely related progressive disorders with no available disease-modifying therapy, neuropathologically characterized by intraneuronal aggregates of misfolded α-synuclein. To explore the role of DNA methylation changes in PD and DLB pathogenesis, we performed an epigenome-wide association study (EWAS) of 322 postmortem frontal cortex samples and replicated results in an independent set of 200 donors. We report novel differentially methylated replicating loci associated with Braak Lewy body stage near TMCC2, SFMBT2, AKAP6 and PHYHIP. Differentially methylated probes were independent of known PD genetic risk alleles. Meta-analysis provided suggestive evidence for a differentially methylated locus within the chromosomal region affected by the PD-associated 22q11.2 deletion. Our findings elucidate novel disease pathways in PD and DLB and generate hypotheses for future molecular studies of Lewy body pathology., (© 2022. The Author(s).)

Published
2022
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14. Author Correction: Common and rare variant association analyses in amyotrophic lateral sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology.

Author

van Rheenen W, van der Spek RAA, Bakker MK, van Vugt JJFA, Hop PJ, Zwamborn RAJ, de Klein N, Westra HJ, Bakker OB, Deelen P, Shireby G, Hannon E, Moisse M, Baird D, Restuadi R, Dolzhenko E, Dekker AM, Gawor K, Westeneng HJ, Tazelaar GHP, van Eijk KR, Kooyman M, Byrne RP, Doherty M, Heverin M, Al Khleifat A, Iacoangeli A, Shatunov A, Ticozzi N, Cooper-Knock J, Smith BN, Gromicho M, Chandran S, Pal S, Morrison KE, Shaw PJ, Hardy J, Orrell RW, Sendtner M, Meyer T, Başak N, van der Kooi AJ, Ratti A, Fogh I, Gellera C, Lauria G, Corti S, Cereda C, Sproviero D, D'Alfonso S, Sorarù G, Siciliano G, Filosto M, Padovani A, Chiò A, Calvo A, Moglia C, Brunetti M, Canosa A, Grassano M, Beghi E, Pupillo E, Logroscino G, Nefussy B, Osmanovic A, Nordin A, Lerner Y, Zabari M, Gotkine M, Baloh RH, Bell S, Vourc'h P, Corcia P, Couratier P, Millecamps S, Meininger V, Salachas F, Mora Pardina JS, Assialioui A, Rojas-García R, Dion PA, Ross JP, Ludolph AC, Weishaupt JH, Brenner D, Freischmidt A, Bensimon G, Brice A, Durr A, Payan CAM, Saker-Delye S, Wood NW, Topp S, Rademakers R, Tittmann L, Lieb W, Franke A, Ripke S, Braun A, Kraft J, Whiteman DC, Olsen CM, Uitterlinden AG, Hofman A, Rietschel M, Cichon S, Nöthen MM, Amouyel P, Traynor BJ, Singleton AB, Mitne Neto M, Cauchi RJ, Ophoff RA, Wiedau-Pazos M, Lomen-Hoerth C, van Deerlin VM, Grosskreutz J, Roediger A, Gaur N, Jörk A, Barthel T, Theele E, Ilse B, Stubendorff B, Witte OW, Steinbach R, Hübner CA, Graff C, Brylev L, Fominykh V, Demeshonok V, Ataulina A, Rogelj B, Koritnik B, Zidar J, Ravnik-Glavač M, Glavač D, Stević Z, Drory V, Povedano M, Blair IP, Kiernan MC, Benyamin B, Henderson RD, Furlong S, Mathers S, McCombe PA, Needham M, Ngo ST, Nicholson GA, Pamphlett R, Rowe DB, Steyn FJ, Williams KL, Mather KA, Sachdev PS, Henders AK, Wallace L, de Carvalho M, Pinto S, Petri S, Weber M, Rouleau GA, Silani V, Curtis CJ, Breen G, Glass JD, Brown RH Jr, Landers JE, Shaw CE, Andersen PM, Groen EJN, van Es MA, Pasterkamp RJ, Fan D, Garton FC, McRae AF, Davey Smith G, Gaunt TR, Eberle MA, Mill J, McLaughlin RL, Hardiman O, Kenna KP, Wray NR, Tsai E, Runz H, Franke L, Al-Chalabi A, Van Damme P, van den Berg LH, and Veldink JH

Published
2022
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15. Common and rare variant association analyses in amyotrophic lateral sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology.

Author

van Rheenen W, van der Spek RAA, Bakker MK, van Vugt JJFA, Hop PJ, Zwamborn RAJ, de Klein N, Westra HJ, Bakker OB, Deelen P, Shireby G, Hannon E, Moisse M, Baird D, Restuadi R, Dolzhenko E, Dekker AM, Gawor K, Westeneng HJ, Tazelaar GHP, van Eijk KR, Kooyman M, Byrne RP, Doherty M, Heverin M, Al Khleifat A, Iacoangeli A, Shatunov A, Ticozzi N, Cooper-Knock J, Smith BN, Gromicho M, Chandran S, Pal S, Morrison KE, Shaw PJ, Hardy J, Orrell RW, Sendtner M, Meyer T, Başak N, van der Kooi AJ, Ratti A, Fogh I, Gellera C, Lauria G, Corti S, Cereda C, Sproviero D, D'Alfonso S, Sorarù G, Siciliano G, Filosto M, Padovani A, Chiò A, Calvo A, Moglia C, Brunetti M, Canosa A, Grassano M, Beghi E, Pupillo E, Logroscino G, Nefussy B, Osmanovic A, Nordin A, Lerner Y, Zabari M, Gotkine M, Baloh RH, Bell S, Vourc'h P, Corcia P, Couratier P, Millecamps S, Meininger V, Salachas F, Mora Pardina JS, Assialioui A, Rojas-García R, Dion PA, Ross JP, Ludolph AC, Weishaupt JH, Brenner D, Freischmidt A, Bensimon G, Brice A, Durr A, Payan CAM, Saker-Delye S, Wood NW, Topp S, Rademakers R, Tittmann L, Lieb W, Franke A, Ripke S, Braun A, Kraft J, Whiteman DC, Olsen CM, Uitterlinden AG, Hofman A, Rietschel M, Cichon S, Nöthen MM, Amouyel P, Traynor BJ, Singleton AB, Mitne Neto M, Cauchi RJ, Ophoff RA, Wiedau-Pazos M, Lomen-Hoerth C, van Deerlin VM, Grosskreutz J, Roediger A, Gaur N, Jörk A, Barthel T, Theele E, Ilse B, Stubendorff B, Witte OW, Steinbach R, Hübner CA, Graff C, Brylev L, Fominykh V, Demeshonok V, Ataulina A, Rogelj B, Koritnik B, Zidar J, Ravnik-Glavač M, Glavač D, Stević Z, Drory V, Povedano M, Blair IP, Kiernan MC, Benyamin B, Henderson RD, Furlong S, Mathers S, McCombe PA, Needham M, Ngo ST, Nicholson GA, Pamphlett R, Rowe DB, Steyn FJ, Williams KL, Mather KA, Sachdev PS, Henders AK, Wallace L, de Carvalho M, Pinto S, Petri S, Weber M, Rouleau GA, Silani V, Curtis CJ, Breen G, Glass JD, Brown RH Jr, Landers JE, Shaw CE, Andersen PM, Groen EJN, van Es MA, Pasterkamp RJ, Fan D, Garton FC, McRae AF, Davey Smith G, Gaunt TR, Eberle MA, Mill J, McLaughlin RL, Hardiman O, Kenna KP, Wray NR, Tsai E, Runz H, Franke L, Al-Chalabi A, Van Damme P, van den Berg LH, and Veldink JH

Subjects
Amyotrophic Lateral Sclerosis metabolism, Brain metabolism, Cholesterol blood, Disease Progression, Female, Glutamine metabolism, Humans, Male, Mendelian Randomization Analysis, Microsatellite Repeats, Neurodegenerative Diseases genetics, Quantitative Trait Loci, RNA-Seq, Risk Factors, Amyotrophic Lateral Sclerosis genetics, Genome-Wide Association Study, Mutation, Neurons metabolism
Abstract

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a lifetime risk of one in 350 people and an unmet need for disease-modifying therapies. We conducted a cross-ancestry genome-wide association study (GWAS) including 29,612 patients with ALS and 122,656 controls, which identified 15 risk loci. When combined with 8,953 individuals with whole-genome sequencing (6,538 patients, 2,415 controls) and a large cortex-derived expression quantitative trait locus (eQTL) dataset (MetaBrain), analyses revealed locus-specific genetic architectures in which we prioritized genes either through rare variants, short tandem repeats or regulatory effects. ALS-associated risk loci were shared with multiple traits within the neurodegenerative spectrum but with distinct enrichment patterns across brain regions and cell types. Of the environmental and lifestyle risk factors obtained from the literature, Mendelian randomization analyses indicated a causal role for high cholesterol levels. The combination of all ALS-associated signals reveals a role for perturbations in vesicle-mediated transport and autophagy and provides evidence for cell-autonomous disease initiation in glutamatergic neurons., (© 2021. The Author(s).)

Published
2021
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16. A meta-analysis of epigenome-wide association studies in Alzheimer's disease highlights novel differentially methylated loci across cortex.

Author

Smith RG, Pishva E, Shireby G, Smith AR, Roubroeks JAY, Hannon E, Wheildon G, Mastroeni D, Gasparoni G, Riemenschneider M, Giese A, Sharp AJ, Schalkwyk L, Haroutunian V, Viechtbauer W, van den Hove DLA, Weedon M, Brokaw D, Francis PT, Thomas AJ, Love S, Morgan K, Walter J, Coleman PD, Bennett DA, De Jager PL, Mill J, and Lunnon K

Subjects
Aged, Aged, 80 and over, Alzheimer Disease pathology, Cohort Studies, CpG Islands, Entorhinal Cortex pathology, Epigenesis, Genetic, Female, Genome-Wide Association Study, Humans, Male, Middle Aged, Prefrontal Cortex pathology, ROC Curve, Temporal Lobe pathology, Alzheimer Disease genetics, Alzheimer Disease metabolism, DNA Methylation, Entorhinal Cortex metabolism, Epigenome, Prefrontal Cortex metabolism, Temporal Lobe metabolism
Abstract

Epigenome-wide association studies of Alzheimer's disease have highlighted neuropathology-associated DNA methylation differences, although existing studies have been limited in sample size and utilized different brain regions. Here, we combine data from six DNA methylomic studies of Alzheimer's disease (N = 1453 unique individuals) to identify differential methylation associated with Braak stage in different brain regions and across cortex. We identify 236 CpGs in the prefrontal cortex, 95 CpGs in the temporal gyrus and ten CpGs in the entorhinal cortex at Bonferroni significance, with none in the cerebellum. Our cross-cortex meta-analysis (N = 1408 donors) identifies 220 CpGs associated with neuropathology, annotated to 121 genes, of which 84 genes have not been previously reported at this significance threshold. We have replicated our findings using two further DNA methylomic datasets consisting of a further >600 unique donors. The meta-analysis summary statistics are available in our online data resource ( www.epigenomicslab.com/ad-meta-analysis/ ).

Published
2021
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17. Epigenome-wide association study of attention-deficit/hyperactivity disorder in adults.

Author

Rovira P, Sánchez-Mora C, Pagerols M, Richarte V, Corrales M, Fadeuilhe C, Vilar-Ribó L, Arribas L, Shireby G, Hannon E, Mill J, Casas M, Ramos-Quiroga JA, Soler Artigas M, and Ribasés M

Subjects
Adult, Child, DNA Methylation, Epigenome, Epigenomics, Genome-Wide Association Study, Humans, Multifactorial Inheritance, Attention Deficit Disorder with Hyperactivity genetics
Abstract

Attention-deficit/hyperactivity disorder (ADHD) is a highly heritable neurodevelopmental disorder that often persists into adulthood. There is growing evidence that epigenetic dysregulation participates in ADHD. Given that only a limited number of epigenome-wide association studies (EWASs) of ADHD have been conducted so far and they have mainly focused on pediatric and population-based samples, we performed an EWAS in a clinical sample of adults with ADHD. We report one CpG site and four regions differentially methylated between patients and controls, which are located in or near genes previously involved in autoimmune diseases, cancer or neuroticism. Our sensitivity analyses indicate that smoking status is not responsible for these results and that polygenic risk burden for ADHD does not greatly impact the signatures identified. Additionally, we show an overlap of our EWAS findings with genetic signatures previously described for ADHD and with epigenetic signatures for smoking behavior and maternal smoking. These findings support a role of DNA methylation in ADHD and emphasize the need for additional efforts in larger samples to clarify the role of epigenetic mechanisms on ADHD across the lifespan.

Published
2020
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