AbstractBackgroundAdvances in cancer biology are increasingly dependent on integration of heterogeneous datasets. Large-scale efforts have systematically mapped many aspects of cancer cell biology; however, it remains challenging for individual scientists to effectively integrate and understand this data.ResultsWe have developed a new data retrieval and indexing framework that allows us to integrate publicly available data from different sources and to combine publicly available data with new or bespoke datasets. Our approach, which we have named the cancer data integrator (CanDI), is straightforward to implement, is well documented, and is continuously updated which should enable individual users to take full advantage of efforts to map cancer cell biology. We show that CanDI empowered testable hypotheses of new synthetic lethal gene pairs, genes associated with sex disparity, and immunotherapy targets in cancer.ConclusionsCanDI provides a flexible approach for large-scale data integration in cancer research enabling rapid generation of hypotheses. The CanDI data integrator is available athttps://github.com/GilbertLabUCSF/CanDI. <<<

Florianne O. L. Vehmeijer, Leanne K. Küpers, Gemma C. Sharp, Lucas A. Salas, Samantha Lent, Dereje D. Jima, Gwen Tindula, Sarah Reese, Cancan Qi, Olena Gruzieva, Christian Page, Faisal I. Rezwan, Philip E. Melton, Ellen Nohr, Geòrgia Escaramís, Peter Rzehak, Anni Heiskala, Tong Gong, Samuli T. Tuominen, Lu Gao, Jason P. Ross, Anne P. Starling, John W. Holloway, Paul Yousefi, Gunn Marit Aasvang, Lawrence J. Beilin, Anna Bergström, Elisabeth Binder, Leda Chatzi, Eva Corpeleijn, Darina Czamara, Brenda Eskenazi, Susan Ewart, Natalia Ferre, Veit Grote, Dariusz Gruszfeld, Siri E. Håberg, Cathrine Hoyo, Karen Huen, Robert Karlsson, Inger Kull, Jean-Paul Langhendries, Johanna Lepeule, Maria C. Magnus, Rachel L. Maguire, Peter L. Molloy, Claire Monnereau, Trevor A. Mori, Emily Oken, Katri Räikkönen, Sheryl Rifas-Shiman, Carlos Ruiz-Arenas, Sylvain Sebert, Vilhelmina Ullemar, Elvira Verduci, Judith M. Vonk, Cheng-jian Xu, Ivana V. Yang, Hongmei Zhang, Weiming Zhang, Wilfried Karmaus, Dana Dabelea, Beverly S. Muhlhausler, Carrie V. Breton, Jari Lahti, Catarina Almqvist, Marjo-Riitta Jarvelin, Berthold Koletzko, Martine Vrijheid, Thorkild I. A. Sørensen, Rae-Chi Huang, Syed Hasan Arshad, Wenche Nystad, Erik Melén, Gerard H. Koppelman, Stephanie J. London, Nina Holland, Mariona Bustamante, Susan K. Murphy, Marie-France Hivert, Andrea Baccarelli, Caroline L. Relton, Harold Snieder, Vincent W. V. Jaddoe, Janine F. Felix <<<

AbstractBackgroundDNA methylation has been shown to be associated with adiposity in adulthood. However, whether similar DNA methylation patterns are associated with childhood and adolescent body mass index (BMI) is largely unknown. More insight into this relationship at younger ages may have implications for future prevention of obesity and its related traits.MethodsWe examined whether DNA methylation in cord blood and whole blood in childhood and adolescence was associated with BMI in the age range from 2 to 18 years using both cross-sectional and longitudinal models. We performed meta-analyses of epigenome-wide association studies including up to 4133 children from 23 studies. We examined the overlap of findings reported in previous studies in children and adults with those in our analyses and calculated enrichment.ResultsDNA methylation at three CpGs (cg05937453, cg25212453, and cg10040131), each in a different age range, was associated with BMI at Bonferroni significance,P < 1.06 × 10−7, with a 0.96 standard deviation score (SDS) (standard error (SE) 0.17), 0.32 SDS (SE 0.06), and 0.32 BMI SDS (SE 0.06) higher BMI per 10% increase in methylation, respectively. DNA methylation at nine additional CpGs in the cross-sectional childhood model was associated with BMI at false discovery rate significance. The strength of the associations of DNA methylation at the 187 CpGs previously identified to be associated with adult BMI, increased with advancing age across childhood and adolescence in our analyses. In addition, correlation coefficients between effect estimates for those CpGs in adults and in children and adolescents also increased. Among the top findings for each age range, we observed increasing enrichment for the CpGs that were previously identified in adults (birthPenrichment = 1; childhoodPenrichment = 2.00 × 10−4; adolescencePenrichment = 2.10 × 10−7).ConclusionsThere were only minimal associations of DNA methylation with childhood and adolescent BMI. With the advancing age of the participants across childhood and adolescence, we observed increasing overlap with altered DNA methylation loci reported in association with adult BMI. These findings may be compatible with the hypothesis that DNA methylation differences are mostly a consequence rather than a cause of obesity. <<<