Ostroumova, Evgenia
Mayo Clinic
Centre international de recherche sur le cancer
Citations 2
Investigation of Shared Genetic Risk Factors Between Parkinson's Disease and Cancers
Sugier, Pierre‐Emmanuel , Lucotte, Elise A. , Domenighetti, Cloé , Law, Matthew H. , Iles, Mark M. , Brown, Kevin M. , McKay, James , Hung, Rayjean J., Karimi, Mojgan, Bacq‐Daian, Delphine, Boland, Anne , Kesminiene, Ausrele , Vathaire, Florent de , Guénel, Pascal , Sreelatha, Ashwin Ashok Kumar , Grover, Sandeep , May, Patrick , Radivojkov‐Blagojevic, Milena , Lichtner, Peter , Singleton, Andrew , Hernandez, Dena G., Edsall, Connor , Mellick, George D. , Zimprich, Alexander , Pirker, Walter , Kõks, Sulev, Lesage, Suzanne , Chartier‐Harlin, Marie‐Christine , Brockmann, Kathrin , Deutschländer, Angela , Hadjigeorgiou, G., Simitsi, Athina Maria, Petrucci, Simona , Straniero, Letizia , Brighina, Laura , Ferrarese, Carlo , Annesi, Grazia , Quattrone, Andrea , Nakayama, Akiyoshi , Kim, Yun Joong , Kolber, Pierre, Warrenburg, Bart P.C. van de , Bloem, Bastiaan R. , Aasly, Jan , Toft, Mathias , Ferreira, Joaquim J. , Bardien, Soraya , Tolosa, Eduardo , Ezquerra, Mario , Pástor, Pau , Wirdefeldt, Karin , Ran, Caroline , Puschmann, Andreas , Ygland, Emil , Morrison, Karen , Krainc, Dimitri , Burbulla, Lena F. , Krüger, Rejko , Gasser, Thomas , Sharma, Manu , Hung, Rayjean J. , Schulte, Claudia , Grover, Sandeep , May, Patrick , Bobbili, Dheeraj R , Zimprich, Alexander , Lang, Anthony E , Corvol, Jean-Christophe , Mutez, Eugénie , Brockman, Kathrin , Deutschländer, Angela B , Hadjigeorgiou, Georges M., Stefanis, Leonidas , Valente, Enza Maria , Chung, Sun Ju , Toft, Mathias , Ferreira, Joaquim J , Bardien, Soraya , Tolosa, Eduardo , Ezquerra, Mario , Tan, Manuela , Sharma, Manu , Elbaz, Alexis , Hung, Rayjean J , Puschmann, Andreas , Guénel, Pascal , Law, Matthew H , Iles, Mark M , Pastor, Pau , Koks, Sulev , Domenighetti, Cloé , Amos, Christopher I. , Olaso, Robert , Deleuze, Jean‐François , Lesueur, Fabienne , Ostroumova, Evgenia , Schulte, Claudia , Bobbili, Dheeraj Reddy , Rogaeva, Ekaterina A. , Lang, Anthony E. , Taba, Pille , Brice, Alexis , Corvol, Jean‐Christophe , Mutez, Eugénie , Dardiotis, Efthimios , Simitsi, Athina‐Maria , Valente, Enza Maria , Zecchinelli, Anna , Pezzoli, Gianni , Gagliardi, Monica , Matsuo, Hirotaka , Hattori, Nobutaka , Nishioka, Kenya , Pihlstrøm, Lasse , Guedes, Leonor Correia , Carr, Jonathan , Díez-Fairén, Mónica , Pedersen, Nancy L. , Belin, Andrea Carmine , Clarke, Carl E , Farrer, Matthew J. , Truong, Thérèse , Elbaz, Alexis
Movement Disorders | February 14, 2023 | Volume: 38 | Issue: 4 | Pages: 604-615
Abstract Background Epidemiological studies that examined the association between Parkinson's disease (PD) and cancers led to inconsistent results, but they face a number of methodological difficulties. Objective We used results from genome‐wide association studies (GWASs) to study the genetic correlation between PD and different cancers to identify common genetic risk factors. Methods We used individual data for participants of European ancestry from the Courage‐PD (Comprehensive Unbiased Risk Factor Assessment for Genetics and Environment in Parkinson's Disease; PD, N = 16,519) and EPITHYR (differentiated thyroid cancer, N = 3527) consortia and summary statistics of GWASs from iPDGC (International Parkinson Disease Genomics Consortium; PD, N = 482,730), Melanoma Meta‐Analysis Consortium (MMAC), Breast Cancer Association Consortium (breast cancer), the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (prostate cancer), International Lung Cancer Consortium (lung cancer), and Ovarian Cancer Association Consortium (ovarian cancer) (N comprised between 36,017 and 228,951 for cancer GWASs). We estimated the genetic correlation between PD and cancers using linkage disequilibrium score regression. We studied the association between PD and polymorphisms associated with cancers, and vice versa, using cross‐phenotypes polygenic risk score (PRS) analyses. Results We confirmed a previously reported positive genetic correlation of PD with melanoma (G corr = 0.16 [0.04; 0.28]) and reported an additional significant positive correlation of PD with prostate cancer (G corr = 0.11 [0.03; 0.19]). There was a significant inverse association between the PRS for ovarian cancer and PD (odds ratio [OR] = 0.89 [0.84; 0.94]). Conversely, the PRS of PD was positively associated with breast cancer (OR = 1.08 [1.06; 1.10]) and inversely associated with ovarian cancer (OR = 0.95 [0.91; 0.99]). The association between PD and ovarian cancer was mostly driven by rs183211 located in an intron of the NSF gene (17q21.31). Conclusions We show evidence in favor of a contribution of pleiotropic genes to the association between PD and specific cancers. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.
Design and quality control of large-scale two-sample Mendelian randomization studies
Haycock, Philip , Borges, Maria Carolina , Burrows, Kimberley , Harrison, Sean , Burgess, Stephen , Chang, Xuling , Khankari, Nikhil K. , Tsilidis, Kostas K, Gaunt, Tom R. , Hemani, Gibran , Zheng, Jie , Truong, Thérèse , Law, Matthew H. , Mariosa, Daniela , Hung, Rayjean J, Smith, George Davey , Relton, Caroline L. , Martin, Richard M. , Peters, Ulrike , Rice, Terri, Gallinger, Steve, Cornish, Alex J. , Vijayakrishnan, Jayaram , Wrensch, Margaret , Korat, Andres V Ardisson , Wheeler, Bill, Nilsson, Björn , Smith, Caren E. , Riadi, David, Claus, Elizabeth B. , Hosnijeh, Ng, Irene Oi‐Lin , Passow, Jeanette E, Han, Jiali , Schildkraut, Joellen M. , Wiemels, Joseph L. , Yang, Keming , Wu, Lang , Boutron, Marie-Christine, Iles, Mark M. , Stanulla, Martin , Gaudet, Mia M., Lenha, Mobuchon, Camp, Nicki J, Sham, Pak C. , Brennan, Paul , Jenkins, Robert B. , Diskin, Sharon J. , Berndt, Sonja I. , Tsavachidis, Spiridon, Channock, Stephen J., Galesloot, Tessel E. , Haycock, Philip , Harrison, Sean , Chang, Xuling , Zheng, Jie , Law, Matthew H , Birmann, Brenda M , Mariosa, Daniela , Zheng, Wei , Davey Smith, George , Borges, Maria C , Martin, Richard M , Iles, Mark M , Truong, Therese , Lemaître, Rozenn N. , Westra, Jason , Tsilidis, Kostas K, O’Mara, Tracy A. , Spurdle, Amanda B. , Slager, Susan L. , Birmann, Brenda M. , Hosnijeh, Fatemeh Saberi , Amos, Christopher I. , Hung, Rayjean J, Zheng, Wei , Gunter, Marc J. , Tintle, Nathan , Cheng, Iona C. , Jenkins, Mark A. , Sud, Amit , Johansson, Mattias , Norman, Aaron D. , Klein, Alison P. , Clay‐Gilmour, Alyssa , Franke, André , Heng, Chew‐Kiat , Song, Ci , Ellinghaus, Eva , Ostroumova, Evgenia , Vathaire, Florent de , Cugliari, Giovanni , Matullo, Giuseppe , Cerhan, James R. , Passow, Jeanette E. Eckel, Foo, Jia Nee , Liu, Jianjun , Barnholtz‐Sloan, Jill S. , Maris, John M. , Hemminki, Kari , Kiemeney, Lambertus A. , Ámundadóttir, Laufey T. , Stern, Marc‐Henri , Purdue, Mark P. , Bondy, Melissa L. , Guénel, Pascal , Taylor, Philip R. , Gharahkhani, Puya , Ostrom, Quinn T. , Stolzenberg‐Solomon, Rachael Z. , Dorajoo, Rajkumar , Houlston, Richard S. , Enroth, Stefan , Harrison, Tabitha A. , Gyllensten, Ulf B , Vijai, Joseph , Shi, Yufang , Yang, Wenjian , Lin, Yi , Van Den Eeden, Stephen K
International Journal of Epidemiology | February 11, 2023 | Volume: 52 | Issue: 5 | Pages: 1498-1521
Abstract Background Mendelian randomization (MR) studies are susceptible to metadata errors (e.g. incorrect specification of the effect allele column) and other analytical issues that can introduce substantial bias into analyses. We developed a quality control (QC) pipeline for the Fatty Acids in Cancer Mendelian Randomization Collaboration (FAMRC) that can be used to identify and correct for such errors. Methods We collated summary association statistics from fatty acid and cancer genome-wide association studies (GWAS) and subjected the collated data to a comprehensive QC pipeline. We identified metadata errors through comparison of study-specific statistics to external reference data sets (the National Human Genome Research Institute-European Bioinformatics Institute GWAS catalogue and 1000 genome super populations) and other analytical issues through comparison of reported to expected genetic effect sizes. Comparisons were based on three sets of genetic variants: (i) GWAS hits for fatty acids, (ii) GWAS hits for cancer and (iii) a 1000 genomes reference set. Results We collated summary data from 6 fatty acid and 54 cancer GWAS. Metadata errors and analytical issues with the potential to introduce substantial bias were identified in seven studies (11.6%). After resolving metadata errors and analytical issues, we created a data set of 219 842 genetic associations with 90 cancer types, generated in analyses of 566 665 cancer cases and 1 622 374 controls. Conclusions In this large MR collaboration, 11.6% of included studies were affected by a substantial metadata error or analytical issue. By increasing the integrity of collated summary data prior to their analysis, our protocol can be used to increase the reliability of downstream MR analyses. Our pipeline is available to other researchers via the CheckSumStats package (https://github.com/MRCIEU/CheckSumStats).