These publications are examples of research made possible with data from CanPath and its regional cohorts.


Association of essential tremor with novel risk loci: A genome-wide association study and meta-analysis

Authors: Calwing Liao, Charles-Etienne Castonguay, Karl Heilbron, Veikko Vuokila, Miranda Medeiros, Gabrielle Houle, Fulya Akçimen, Jay P. Ross, Helene Catoire, Monica Diez-Fairen, Jooeun Kang, Stefanie H. Mueller, Simon L. Girard, Franziska Hopfner, Delia Lorenz, Lorraine N. Clark, Alexandra I. Soto-Beasley, Stephan Klebe, Mark Hallett, Zbigniew K. Wszolek, Manuela Pendziwiat, Oswaldo Lorenzo-Betancor, Klaus Seppi, Daniela Berg, Carles Vilariño-Güell, Ronald B. Postuma, Geneviève Bernard, Nicolas Dupré, Joseph Jankovic, Claudia M. Testa, Owen A. Ross, Thomas Arzberger, Sylvain Chouinard, Elan D. Louis, Paola Mandich, Carmine Vitale, Paolo Barone, Elena García-Martín, Hortensia Alonso-Navarro, José A. G. Agúndez, Félix Javier Jiménez-Jiménez, Pau Pastor, Alex Rajput, Günther Deuschl, Gregor Kuhlenbaümer, Inge A. Meijer, Patrick A. Dion, Guy A. Rouleau, for the 23andMe Research Team

This study revealed five genome-wide significant loci associated with essential tremor (ET), one of the most common movement disorders. The researchers’ findings suggest that common genetic variation partly explains ET’s heritability.

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Polygenic risk scores predict diabetes complications and their response to intensive blood pressure and glucose control

Authors: Johanne Tremblay, Mounsif Haloui, Redha Attaoua, Ramzan Tahir, Camil Hishmih, François Harvey, François-Christophe Marois-Blanchet, Carole Long, Paul Simon, Lara Santucci, Candan Hizel, John Chalmers, Michel Marre, Stephen Harrap, Renata Cífková, Alena Krajčoviechová, David R. Matthews, Bryan Williams, Neil Poulter, Sophia Zoungas, Stephen Colagiuri, Giuseppe Mancia, Diederick E. Grobbee, Anthony Rodgers, Liusheng Liu, Mawussé Agbessi, Vanessa Bruat, Marie-Julie Favé, Michelle P. Harwood, Philip Awadalla, Mark Woodward, Julie G. Hussin & Pavel Hamet

This study assessed whether cardiovascular and renal risk factors combined with the age of onset and duration of diabetes are sufficient predictors of type 2 diabetes. Of the 21,702 participants, 488 participants with type 2 diabetes originated from CanPath. The researchers developed a prediction model to help identify high-risk individuals who could benefit from therapies and treatments.

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