Browsing by Subject "IDENTIFY"

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  • Prokic, Ivana; Lahousse, Lies; de Vries, Maaike; Liu, Jun; Kalaoja, Marita; Vonk, Judith M.; van der Plaat, Diana A.; van Diemen, Cleo C.; van der Spek, Ashley; Zhernakova, Alexandra; Fu, Jingyuan; Ghanbari, Mohsen; Ala-Korpela, Mika; Kettunen, Johannes; Havulinna, Aki S.; Perola, Markus; Salomaa, Veikko; Lind, Lars; Arnlov, Johan; Stricker, Bruno H. C.; Brusselle, Guy G.; Boezen, H. Marike; van Duijn, Cornelia M.; Amin, Najaf (2020)
    Background Chronic obstructive pulmonary disease (COPD) is a common lung disorder characterized by persistent and progressive airflow limitation as well as systemic changes. Metabolic changes in blood may help detect COPD in an earlier stage and predict prognosis. Methods We conducted a comprehensive study of circulating metabolites, measured by proton Nuclear Magnetic Resonance Spectroscopy, in relation with COPD and lung function. The discovery sample consisted of 5557 individuals from two large population-based studies in the Netherlands, the Rotterdam Study and the Erasmus Rucphen Family study. Significant findings were replicated in 12,205 individuals from the Lifelines-DEEP study, FINRISK and the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) studies. For replicated metabolites further investigation of causality was performed, utilizing genetics in the Mendelian randomization approach. Results There were 602 cases of COPD and 4955 controls used in the discovery meta-analysis. Our logistic regression results showed that higher levels of plasma Glycoprotein acetyls (GlycA) are significantly associated with COPD (OR = 1.16,P = 5.6 x 10(- 4)in the discovery and OR = 1.30,P = 1.8 x 10(- 6)in the replication sample). A bi-directional two-sample Mendelian randomization analysis suggested that circulating blood GlycA is not causally related to COPD, but that COPD causally increases GlycA levels. Using the prospective data of the same sample of Rotterdam Study in Cox-regression, we show that the circulating GlycA level is a predictive biomarker of COPD incidence (HR = 1.99, 95%CI 1.52-2.60, comparing those in the highest and lowest quartile of GlycA) but is not significantly associated with mortality in COPD patients (HR = 1.07, 95%CI 0.94-1.20). Conclusions Our study shows that circulating blood GlycA is a biomarker of early COPD pathology.
  • Malyutina, Alina; Majumder, Muntasir Mamun; Wang, Wenyu; Pessia, Alberto; Heckman, Caroline A.; Tang, Jing (2019)
    High-throughput drug screening has facilitated the discovery of drug combinations in cancer. Many existing studies adopted a full matrix design, aiming for the characterization of drug pair effects for cancer cells. However, the full matrix design may be suboptimal as it requires a drug pair to be combined at multiple concentrations in a full factorial manner. Furthermore, many of the computational tools assess only the synergy but not the sensitivity of drug combinations, which might lead to false positive discoveries. We proposed a novel cross design to enable a more cost-effective and simultaneous testing of drug combination sensitivity and synergy. We developed a drug combination sensitivity score (CSS) to determine the sensitivity of a drug pair, and showed that the CSS is highly reproducible between the replicates and thus supported its usage as a robust metric. We further showed that CSS can be predicted using machine learning approaches which determined the top pharmaco-features to cluster cancer cell lines based on their drug combination sensitivity profiles. To assess the degree of drug interactions using the cross design, we developed an S synergy score based on the difference between the drug combination and the single drug dose-response curves. We showed that the S score is able to detect true synergistic and antagonistic drug combinations at an accuracy level comparable to that using the full matrix design. Taken together, we showed that the cross design coupled with the CSS sensitivity and S synergy scoring methods may provide a robust and accurate characterization of both drug combination sensitivity and synergy levels, with minimal experimental materials required. Our experimental-computational approach could be utilized as an efficient pipeline for improving the discovery rate in high-throughput drug combination screening, particularly for primary patient samples which are difficult to obtain.
  • Zagidullin, Bulat; Aldahdooh, Jehad; Zheng, Shuyu; Wang, Wenyu; Wang, Yinyin; Saad, Joseph; Malyutina, Alina; Jafari, Mohieddin; Tanoli, Zia-ur-Rehman; Pessia, Alberto; Tang, Jing (2019)
    Drug combination therapy has the potential to enhance efficacy, reduce dose-dependent toxicity and prevent the emergence of drug resistance. However, discovery of synergistic and effective drug combinations has been a laborious and often serendipitous process. In recent years, identification of combination therapies has been accelerated due to the advances in high-throughput drug screening, but informatics approaches for systems-level data management and analysis are needed. To contribute toward this goal, we created an open-access data portal called DrugComb ( where the results of drug combination screening studies are accumulated, standardized and harmonized. Through the data portal, we provided a web server to analyze and visualize users’ own drug combination screening data. The users can also effectively participate a crowdsourcing data curation effect by depositing their data at DrugComb. To initiate the data repository, we collected 437 932 drug combinations tested on a variety of cancer cell lines. We showed that linear regression approaches, when considering chemical fingerprints as predictors, have the potential to achieve high accuracy of predicting the sensitivity of drug combinations. All the data and informatics tools are freely available in DrugComb to enable a more efficient utilization of data resources for future drug combination discovery.
  • Couch, Fergus J.; Kuchenbaecker, Karoline B.; Michailidou, Kyriaki; Mendoza-Fandino, Gustavo A.; Nord, Silje; Lilyquist, Janna; Olswold, Curtis; Hallberg, Emily; Agata, Simona; Ahsan, Habibul; Aittomäki, Kristiina; Ambrosone, Christine; Andrulis, Irene L.; Anton-Culver, Hoda; Arndt, Volker; Arun, Banu K.; Arver, Brita; Barile, Monica; Barkardottir, Rosa B.; Barrowdale, Daniel; Beckmann, Lars; Beckmann, Matthias W.; Benitez, Javier; Blank, Stephanie V.; Blomqvist, Carl; Bogdanova, Natalia V.; Bojesen, Stig E.; Bolla, Manjeet K.; Bonanni, Bernardo; Brauch, Hiltrud; Brenner, Hermann; Burwinkel, Barbara; Buys, Saundra S.; Caldes, Trinidad; Caligo, Maria A.; Canzian, Federico; Carpenter, Jane; Chang-Claude, Jenny; Chanock, Stephen J.; Chung, Wendy K.; Claes, Kathleen B. M.; Cox, Angela; Cross, Simon S.; Cunningham, Julie M.; Czene, Kamila; Daly, Mary B.; Damiola, Francesca; Darabi, Hatef; de la Hoya, Miguel; Devilee, Peter; Diez, Orland; Ding, Yuan C.; Dolcetti, Riccardo; Domchek, Susan M.; Dorfling, Cecilia M.; dos-Santos-Silva, Isabel; Dumont, Martine; Dunning, Alison M.; Eccles, Diana M.; Ehrencrona, Hans; Ekici, Arif B.; Eliassen, Heather; Ellis, Steve; Fasching, Peter A.; Figueroa, Jonine; Flesch-Janys, Dieter; Foersti, Asta; Fostira, Florentia; Foulkes, William D.; Friebel, Tara; Friedman, Eitan; Frost, Debra; Gabrielson, Marike; Gammon, Marilie D.; Ganz, Patricia A.; Gapstur, Susan M.; Garber, Judy; Gaudet, Mia M.; Gayther, Simon A.; Gerdes, Anne-Marie; Ghoussaini, Maya; Giles, Graham G.; Glendon, Gord; Godwin, Andrew K.; Goldberg, Mark S.; Goldgar, David E.; Gonzalez-Neira, Anna; Greene, Mark H.; Gronwald, Jacek; Guenel, Pascal; Gunter, Marc; Haeberle, Lothar; Haiman, Christopher A.; Hamann, Ute; Hansen, Thomas V. O.; Hart, Steven; Healey, Sue; Heikkinen, Tuomas; Henderson, Brian E.; Herzog, Josef; Hogervorst, Frans B. L.; Hollestelle, Antoinette; Hooning, Maartje J.; Hoover, Robert N.; Hopper, John L.; Humphreys, Keith; Hunter, David J.; Huzarski, Tomasz; Imyanitov, Evgeny N.; Isaacs, Claudine; Jakubowska, Anna; James, Paul; Janavicius, Ramunas; Jensen, Uffe Birk; John, Esther M.; Jones, Michael; Kabisch, Maria; Kar, Siddhartha; Karlan, Beth Y.; Khan, Sofia; Khaw, Kay-Tee; Kibriya, Muhammad G.; Knight, Julia A.; Ko, Yon-Dschun; Konstantopoulou, Irene; Kosma, Veli-Matti; Kristensen, Vessela; Kwong, Ava; Laitman, Yael; Lambrechts, Diether; Lazaro, Conxi; Lee, Eunjung; Le Marchand, Loic; Lester, Jenny; Lindblom, Annika; Lindor, Noralane; Lindstrom, Sara; Liu, Jianjun; Long, Jirong; Lubinski, Jan; Mai, Phuong L.; Makalic, Enes; Malone, Kathleen E.; Mannermaa, Arto; Manoukian, Siranoush; Margolin, Sara; Marme, Frederik; Martens, John W. M.; McGuffog, Lesley; Meindl, Alfons; Miller, Austin; Milne, Roger L.; Miron, Penelope; Montagna, Marco; Mazoyer, Sylvie; Mulligan, Anna M.; Muranen, Taru A.; Nathanson, Katherine L.; Neuhausen, Susan L.; Nevanlinna, Heli; Nordestgaard, Borge G.; Nussbaum, Robert L.; Offit, Kenneth; Olah, Edith; Olopade, Olufunmilayo I.; Olson, Janet E.; Osorio, Ana; Park, Sue K.; Peeters, Petra H.; Peissel, Bernard; Peterlongo, Paolo; Peto, Julian; Phelan, Catherine M.; Pilarski, Robert; Poppe, Bruce; Pylkaes, Katri; Radice, Paolo; Rahman, Nazneen; Rantala, Johanna; Rappaport, Christine; Rennert, Gad; Richardson, Andrea; Robson, Mark; Romieu, Isabelle; Rudolph, Anja; Rutgers, Emiel J.; Sanchez, Maria-Jose; Santella, Regina M.; Sawyer, Elinor J.; Schmidt, Daniel F.; Schmidt, Marjanka K.; Schmutzler, Rita K.; Schumacher, Fredrick; Scott, Rodney; Senter, Leigha; Sharma, Priyanka; Simard, Jacques; Singer, Christian F.; Sinilnikova, Olga M.; Soucy, Penny; Southey, Melissa; Steinemann, Doris; Stenmark-Askmalm, Marie; Stoppa-Lyonnet, Dominique; Swerdlow, Anthony; Szabo, Csilla I.; Tamimi, Rulla; Tapper, William; Teixeira, Manuel R.; Teo, Soo-Hwang; Terry, Mary B.; Thomassen, Mads; Thompson, Deborah; Tihomirova, Laima; Toland, Amanda E.; Tollenaar, Robert A. E. M.; Tomlinson, Ian; Truong, Therese; Tsimiklis, Helen; Teule, Alex; Tumino, Rosario; Tung, Nadine; Turnbull, Clare; Ursin, Giski; van Deurzen, Carolien H. M.; van Rensburg, Elizabeth J.; Varon-Mateeva, Raymonda; Wang, Zhaoming; Wang-Gohrke, Shan; Weiderpass, Elisabete; Weitzel, Jeffrey N.; Whittemore, Alice; Wildiers, Hans; Winqvist, Robert; Yang, Xiaohong R.; Yannoukakos, Drakoulis; Yao, Song; Zamora, M. Pilar; Zheng, Wei; Hall, Per; Kraft, Peter; Vachon, Celine; Slager, Susan; Chenevix-Trench, Georgia; Pharoah, Paul D. P.; Monteiro, Alvaro A. N.; Garcia-Closas, Montserrat; Easton, Douglas F.; Antoniou, Antonis C. (2016)
    Common variants in 94 loci have been associated with breast cancer including 15 loci with genome-wide significant associations (P