TY - JOUR
T1 - Quantitative comparison of DNA methylation assays for biomarker development and clinical applications
AU - BLUEPRINT consortium
AU - Bock, Christoph
AU - Halbritter, Florian
AU - Carmona, Francisco J.
AU - Tierling, Sascha
AU - Datlinger, Paul
AU - Assenov, Yassen
AU - Berdasco, María
AU - Bergmann, Anke K.
AU - Booher, Keith
AU - Busato, Florence
AU - Campan, Mihaela
AU - Dahl, Christina
AU - Dahmcke, Christina M.
AU - Diep, Dinh
AU - Fernández, Agustín F.
AU - Gerhauser, Clarissa
AU - Haake, Andrea
AU - Heilmann, Katharina
AU - Holcomb, Thomas
AU - Hussmann, Dianna
AU - Ito, Mitsuteru
AU - Kläver, Ruth
AU - Kreutz, Martin
AU - Kulis, Marta
AU - Lopez, Virginia
AU - Nair, Shalima S.
AU - Paul, Dirk S.
AU - Plongthongkum, Nongluk
AU - Qu, Wenjia
AU - Queirós, Ana C.
AU - Reinicke, Frank
AU - Sauter, Guido
AU - Schlomm, Thorsten
AU - Statham, Aaron
AU - Stirzaker, Clare
AU - Strogantsev, Ruslan
AU - Urdinguio, Rocío G.
AU - Walter, Kimberly
AU - Weichenhan, Dieter
AU - Weisenberger, Daniel J.
AU - Beck, Stephan
AU - Clark, Susan J.
AU - Esteller, Manel
AU - Ferguson-Smith, Anne C.
AU - Fraga, Mario F.
AU - Guldberg, Per
AU - Hansen, Lise Lotte
AU - Laird, Peter W.
AU - Martín-Subero, José I.
AU - Nygren, Anders O.H.
N1 - Funding Information:
We thank J. Hadler, T. Penz, C. Lo Porto, B. Schmitt, M. Bähr, M. Helf, O. Mücke, N. Mazaleyrat, C.V. Wong, T.E. Kjeldsen, A. Janosch, P. Dhami, E. Flores and H. Gohlke for technical assistance, and H. Stunnenberg as well as the scientific advisory board of BLUEPRINT for their advice and support. This work was performed in the context of the BLUEPRINT project (European Union's Seventh Framework Programme grant agreement 282510), which funded the study logistics and the integrative data analysis. The assay costs were paid by the contributing laboratories using institutional funds and the following grants: BBSRC BB/G020930/1, BBSRC BB/G020930/1, BMBF 01KU1001A, BMBF 01KU1002A, BMBF 01KU1216F, EU-FP7 282510, FWF I 1575-B19, NHMRC 1063559, NHMRC 1088144 and the DKFZ Graduate School.
Publisher Copyright:
© 2016 Nature America, Inc. All rights reserved.
PY - 2016/7/1
Y1 - 2016/7/1
N2 - DNA methylation patterns are altered in numerous diseases and often correlate with clinically relevant information such as disease subtypes, prognosis and drug response. With suitable assays and after validation in large cohorts, such associations can be exploited for clinical diagnostics and personalized treatment decisions. Here we describe the results of a community-wide benchmarking study comparing the performance of all widely used methods for DNA methylation analysis that are compatible with routine clinical use. We shipped 32 reference samples to 18 laboratories in seven different countries. Researchers in those laboratories collectively contributed 21 locus-specific assays for an average of 27 predefined genomic regions, as well as six global assays. We evaluated assay sensitivity on low-input samples and assessed the assays' ability to discriminate between cell types. Good agreement was observed across all tested methods, with amplicon bisulfite sequencing and bisulfite pyrosequencing showing the best all-round performance. Our technology comparison can inform the selection, optimization and use of DNA methylation assays in large-scale validation studies, biomarker development and clinical diagnostics.
AB - DNA methylation patterns are altered in numerous diseases and often correlate with clinically relevant information such as disease subtypes, prognosis and drug response. With suitable assays and after validation in large cohorts, such associations can be exploited for clinical diagnostics and personalized treatment decisions. Here we describe the results of a community-wide benchmarking study comparing the performance of all widely used methods for DNA methylation analysis that are compatible with routine clinical use. We shipped 32 reference samples to 18 laboratories in seven different countries. Researchers in those laboratories collectively contributed 21 locus-specific assays for an average of 27 predefined genomic regions, as well as six global assays. We evaluated assay sensitivity on low-input samples and assessed the assays' ability to discriminate between cell types. Good agreement was observed across all tested methods, with amplicon bisulfite sequencing and bisulfite pyrosequencing showing the best all-round performance. Our technology comparison can inform the selection, optimization and use of DNA methylation assays in large-scale validation studies, biomarker development and clinical diagnostics.
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U2 - 10.1038/nbt.3605
DO - 10.1038/nbt.3605
M3 - Article
C2 - 27347756
AN - SCOPUS:84978435580
SN - 1087-0156
VL - 34
SP - 726
EP - 737
JO - Biotechnology
JF - Biotechnology
IS - 7
ER -