Mariosa, Daniela
Mayo Clinic
International Agency for Research on Cancer, World Health Organization, Lyon, France.
Citations 2
Causal relationships between risk of venous thromboembolism and 18 cancers: a bidirectional Mendelian randomization analysis
Cornish, Naomi , Haycock, Philip , Brenner, Hermann , Figueiredo, Jane C. , Galesloot, Tessel E. , Grant, Robert C. , Mariosa, Daniela , McKay, James , Pai, Rish K. , Pellatt, Andrew J. , Samadder, N. Jewel , Shi, Jianxin , Trégouët, David‐Alexandre , Voegele, Catherine , Thirlwell, Chrissie, Langdon, Ryan , Mariosa, Daniela , Pai, Rish, Thirlwell, Chrissie , Haycock, Philip , Brenner, Hermann , Pellatt, Andrew J , Johansson, Mattias , Thibord, Florian , Mumford, Andrew David
International Journal of Epidemiology | December 4, 2023 | Volume: 53 | Issue: 1 | Pages: No page available
Abstract Background People with cancer experience high rates of venous thromboembolism (VTE). Risk of subsequent cancer is also increased in people experiencing their first VTE. The causal mechanisms underlying this association are not completely understood, and it is unknown whether VTE is itself a risk factor for cancer. Methods We used data from large genome-wide association study meta-analyses to perform bidirectional Mendelian randomization analyses to estimate causal associations between genetic liability to VTE and risk of 18 different cancers. Results We found no conclusive evidence that genetic liability to VTE was causally associated with an increased incidence of cancer, or vice versa. We observed an association between liability to VTE and pancreatic cancer risk [odds ratio for pancreatic cancer: 1.23 (95% confidence interval: 1.08–1.40) per log-odds increase in VTE risk, P = 0.002]. However, sensitivity analyses revealed this association was predominantly driven by a variant proxying non-O blood group, with inadequate evidence to suggest a causal relationship. Conclusions These findings do not support the hypothesis that genetic liability to VTE is a cause of cancer. Existing observational epidemiological associations between VTE and cancer are therefore more likely to be driven by pathophysiological changes which occur in the setting of active cancer and anti-cancer treatments. Further work is required to explore and synthesize evidence for these mechanisms.
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).