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Hilkka Soininen on Muck Rack

Hilkka Soininen

As seen in: Nature, BMJ Open, Alzheimer's Research and Therapy, Flipboard, The Lancet, Alzheimer's & Dementia
Professor emerita, neurology, University of Eastern Finland, Kuopio, Finland.
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Articles

Machine learning in Alzheimer’s disease genetics - Nature Communications

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By Matthew Bracher-Smith, Céline Bellenguez, Peter A Holmans, Betty M. Tijms, Marc Hulsman, Itziar de Rojas, Rafael Campos-Martin, Fahri Küçükali, Oliver Peters, Anja Schneider, Martin Dichgans, Dan Rujescu, Norbert Scherbaum, Steffi G. Riedel-Heller, Lucrezia Hausner, Laura Molina-Porcel, Jens Wiltfang, Stefanie Heilmann-Heimbach, Susanne Moebus, Oriol Dols-Icardo, Fermín Moreno, Jordi Pérez-Tur, Maria Bullido, Victoria Alvarez, Mercè Boada, Pablo García-González, Raquel Puerta, Pablo Mir, Luis M. Real, Jose María García-Alberca, Eloy Rodriguez-Rodriguez, Hilkka Soininen, Sami Heikkinen, Jakub Hort, Jesper Qvist Thomassen, Henne Holstege, Philip Scheltens, Vilmantas Giedraitis, Julie Williams, Philippe Amouyel, Anne Boland, Gaël Nicolas, Carole Dufouil, Florence Pasquier, Stéphanie Debette, Edna Grünblatt, Roberta Ghidoni, Daniela Galimberti, Beatrice Arosio, Patrizia Mecocci, Vincenzo Solfrizzi, Lucilla Parnetti, Alessio Squassina, Michael Wagner, Benedetta Nacmias, Fabrizio Piras, Giacomina Rossi, Patrick Kehoe, Kristel Sleegers, Martin Ingelsson, Rebecca Sims, Ole A. Andreassen, Agustín Ruiz, Alfredo M. Ramirez, Alfredo Ramírez, Ruth Frikke-Schmidt, Najaf Amin, Gennady V Roshchupkin, Jean-Charles Lambert, Kristel Van Steen, Cornelia van Duijn, Tsolaki Magda
| Nature Verified
Abstract Traditional statistical approaches have advanced our understanding of the genetics of complex diseases, yet are limited to linear additive models. Here we applied machine learning (ML) to genome-wide data from 41,686 individuals in the largest European consortium on Alzheimer’s disease (AD) to investigate the effectiveness of various ML algorithms in replicating known findings, discovering novel loci, and predicting individuals at risk.
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Machine learning in Alzheimer’s disease genetics

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By Matthew Bracher-Smith, Federico Melograna, Brittany S. Ulm, Céline Bellenguez, Benjamin Grenier-Boley, Diane Duroux, Peter A Holmans, Betty M. Tijms, Marc Hulsman, Itziar de Rojas, Rafael Campos-Martin, Fahri Küçükali, Oliver Peters, Anja Schneider, Martin Dichgans, Dan Rujescu, Norbert Scherbaum, Jürgen Deckert, Steffi G. Riedel-Heller, Lucrezia Hausner, Laura Molina-Porcel, Emrah Düzel, Timo Grimmer, Jens Wiltfang, Stefanie Heilmann-Heimbach, Susanne Moebus, Thomas Tegos, Nikolaos Scarmeas, Oriol Dols-Icardo, Fermín Moreno, Jordi Pérez-Tur, Maria Bullido, Raquel Sánchez-Valle, Victoria Alvarez, Mercè Boada, Pablo García-González, Raquel Puerta, Pablo Mir, Luis M. Real, Gerard Piñol-Ripoll, Jose María García-Alberca, Eloy Rodriguez-Rodriguez, Hilkka Soininen, Sami Heikkinen, Alexandre de Mendonça, Latchezar Traykov, Jakub Hort, Martin Vyhnálek, Nicolai Sandau, Jesper Qvist Thomassen, Henne Holstege, Inez H.G.B. Ramakers, Frans R Verhey, Philip Scheltens, Caroline Graff, Goran Papenberg, Vilmantas Giedraitis, Julie Williams, Philippe Amouyel, Anne Boland, Jean-Francois Deleuze, Gaël Nicolas, Carole Dufouil, Florence Pasquier, Olivier Hanon, Stéphanie Debette, Edna Grünblatt, Julius Popp, Roberta Ghidoni, Daniela Galimberti, Beatrice Arosio, Patrizia Mecocci, Vincenzo Solfrizzi, Lucilla Parnetti, Alessio Squassina, Lucio Tremolizzo, Barbara Borroni, Michael Wagner, Benedetta Nacmias, Davide Seripa, Innocenzo Rainero, Antonio Daniele, Fabrizio Piras, Giacomina Rossi, Frank Jessen, Patrick Kehoe, Tsolaki Magda, Pascual Sanchez-Juan, Kristel Sleegers, Martin Ingelsson, Mikko Hiltunen, Rebecca Sims, Ole A. Andreassen, Agustín Ruiz, Alfredo M. Ramirez, Alfredo Ramírez, Ruth Frikke-Schmidt, Najaf Amin, Gennady V Roshchupkin, Jean-Charles Lambert, Kristel Van Steen, Cornelia van Duijn, Valentina Escott-Price, Alejo J. Nevado, Atahualpa Castillo, Shima Mehrabian, John van Swieten, Marco Spallazzi, Carlo Masullo
| Flipboard
Scientists just discovered a secret code hidden in your DNA What scientists once dismissed as “junk” DNA may actually be some of the most powerful code in our genome. A new international study reveals that …
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Transferability of European-derived Alzheimer’s disease polygenic risk scores across multiancestry populations - Nature Genetics

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By Aude Nicolas, Richard Sherva, Yoontae Kim, Masataka Kikuchi, Itziar de Rojas, Maria Carolina Dalmasso, Xiaopu Zhou, Yann Le Guen, Maëlenn Guerchet, Céline Bellenguez, Fahri Küçükali, Claudia L. Satizabal, Bernard Fongang, Qiong Yang, Oliver Peters, Anja Schneider, Martin Dichgans, Dan Rujescu, Norbert Scherbaum, Steffi G. Riedel-Heller, Lucrezia Hausner, Laura Molina-Porcel, Jens Wiltfang, Stefanie Heilmann-Heimbach, Susanne Moebus, Oriol Dols-Icardo, Fermín Moreno, Jordi Pérez-Tur, Maria Bullido, Victoria Alvarez, Han Cao, Nancy Y. Ip, Natividad Olivar, Carolina Muchnik, Mercè Boada, Pablo García-González, Raquel Puerta, Pablo Mir, Luis M. Real, Jose María García-Alberca, Eloy Rodriguez-Rodriguez, Hilkka Soininen, Sami Heikkinen, Jakub Hort, Jesper Qvist Thomassen, Henne Holstege, Harro Seelaar, Philip Scheltens, Maria F. Mahecha, Vera Fominykh, Geir Selbæk, Vilmantas Giedraitis, Anne Boland, Teresa Juárez-Cedillo, Lindsay A Farrer, Ellen M. Wijsman, Richard Mayeux, Margaret A. Pericak-Vance, Alison Goate, Badri Vardarajan, Yuk Yee Leung, Clifton L. Dalgard, Gaël Nicolas, David Wallon, Carole Dufouil, Stéphanie Debette, Edna Grünblatt, Bárbara Angel, Sergio Gloger, Paulina Orellana, Christian González-Billault, Cecilia Albala, Perminder S Sachdev, Karen A. Mather, Richard L Hauger, Victoria Merritt, Roberta Ghidoni, Daniela Galimberti, Beatrice Arosio, Patrizia Mecocci, Vincenzo Solfrizzi, Lucilla Parnetti, Alessio Squassina, Benedetta Nacmias, Jenifer S. Yokoyama, Akinori Miyashita, Norikazu Hara, Kouichi Ozaki, Julie Williams, Philippe Amouyel, Andy Saykin, Patrick Kehoe, Cornelia van Duijn, Ruth Frikke-Schmidt, Magda Tsolaki, Tenielle Porter, Simon Laws, Kristel Sleegers, Martin Ingelsson, Sudha Seshadri, Giacomina Rossi, Rebecca Sims, Ole A. Andreassen, Carlos Cruchaga, Valentina Escott-Price, Agustín Ruiz, Kun Ho Lee, Takeshi Ikeuchi, Alfredo M. Ramirez, Alfredo Ramírez, Mark W. Logue
| Nature Verified
Abstract A polygenic score (PGS) for Alzheimer’s disease (AD) was derived recently from data on genome-wide significant loci in European ancestry populations. We applied this PGS to populations in 17 European countries and observed a consistent association with the AD risk, age at onset and cerebrospinal fluid levels of AD biomarkers, independently of apolipoprotein E locus (APOE). This PGS was also associated with the AD risk in many other populations of diverse ancestries.
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