@article{ArltBiehlTayloretal.2011, author = {Arlt, Wiebke and Biehl, Michael and Taylor, Angela E. and Hahner, Stefanie and Lib{\´e}, Rossella and Hughes, Beverly A. and Schneider, Petra and Smith, David J. and Stiekema, Han and Krone, Nils and Porfiri, Emilio and Opocher, Giuseppe and Bertherat, Jer{\^o}me and Mantero, Franco and Allolio, Bruno and Terzolo, Massimo and Nightingale, Peter and Shackleton, Cedric H. L. and Bertagna, Xavier and Fassnacht, Martin and Stewart, Paul M.}, title = {Urine Steroid Metabolomics as a Biomarker Tool for Detecting Malignancy in Adrenal Tumors}, series = {The Journal of Clinical Endocrinology \& Metabolism}, volume = {96}, journal = {The Journal of Clinical Endocrinology \& Metabolism}, number = {12}, doi = {10.1210/jc.2011-1565}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-154682}, pages = {3775 -- 3784}, year = {2011}, abstract = {Context: Adrenal tumors have a prevalence of around 2\% in the general population. Adrenocortical carcinoma (ACC) is rare but accounts for 2-11\% of incidentally discovered adrenal masses. Differentiating ACC from adrenocortical adenoma (ACA) represents a diagnostic challenge in patients with adrenal incidentalomas, with tumor size, imaging, and even histology all providing unsatisfactory predictive values. Objective: Here we developed a novel steroid metabolomic approach, mass spectrometry-based steroid profiling followed by machine learning analysis, and examined its diagnostic value for the detection of adrenal malignancy. Design: Quantification of 32 distinct adrenal derived steroids was carried out by gas chromatography/mass spectrometry in 24-h urine samples from 102 ACA patients (age range 19-84 yr) and 45 ACC patients (20-80 yr). Underlying diagnosis was ascertained by histology and metastasis in ACC and by clinical follow-up [median duration 52 (range 26-201) months] without evidence of metastasis in ACA. Steroid excretion data were subjected to generalized matrix learning vector quantization (GMLVQ) to identify the most discriminative steroids. Results: Steroid profiling revealed a pattern of predominantly immature, early-stage steroidogenesis in ACC. GMLVQ analysis identified a subset of nine steroids that performed best in differentiating ACA from ACC. Receiver-operating characteristics analysis of GMLVQ results demonstrated sensitivity = specificity = 90\% (area under the curve = 0.97) employing all 32 steroids and sensitivity = specificity = 88\% (area under the curve = 0.96) when using only the nine most differentiating markers. Conclusions: Urine steroid metabolomics is a novel, highly sensitive, and specific biomarker tool for discriminating benign from malignant adrenal tumors, with obvious promise for the diagnostic work-up of patients with adrenal incidentalomas.}, language = {en} } @article{HudsonNewboldContuetal.2014, author = {Hudson, Lawrence N. and Newbold, Tim and Contu, Sara and Hill, Samantha L. L. and Lysenko, Igor and De Palma, Adriana and Phillips, Helen R. P. and Senior, Rebecca A. and Bennett, Dominic J. and Booth, Hollie and Choimes, Argyrios and Correia, David L. P. and Day, Julie and Echeverria-Londono, Susy and Garon, Morgan and Harrison, Michelle L. K. and Ingram, Daniel J. and Jung, Martin and Kemp, Victoria and Kirkpatrick, Lucinda and Martin, Callum D. and Pan, Yuan and White, Hannah J. and Aben, Job and Abrahamczyk, Stefan and Adum, Gilbert B. and Aguilar-Barquero, Virginia and Aizen, Marcelo and Ancrenaz, Marc and Arbelaez-Cortes, Enrique and Armbrecht, Inge and Azhar, Badrul and Azpiroz, Adrian B. and Baeten, Lander and B{\´a}ldi, Andr{\´a}s and Banks, John E. and Barlow, Jos and Bat{\´a}ry, P{\´e}ter and Bates, Adam J. and Bayne, Erin M. and Beja, Pedro and Berg, Ake and Berry, Nicholas J. and Bicknell, Jake E. and Bihn, Jochen H. and B{\"o}hning-Gaese, Katrin and Boekhout, Teun and Boutin, Celine and Bouyer, Jeremy and Brearley, Francis Q. and Brito, Isabel and Brunet, J{\"o}rg and Buczkowski, Grzegorz and Buscardo, Erika and Cabra-Garcia, Jimmy and Calvino-Cancela, Maria and Cameron, Sydney A. and Cancello, Eliana M. and Carrijo, Tiago F. and Carvalho, Anelena L. and Castro, Helena and Castro-Luna, Alejandro A. and Cerda, Rolando and Cerezo, Alexis and Chauvat, Matthieu and Clarke, Frank M. and Cleary, Daniel F. R. and Connop, Stuart P. and D'Aniello, Biagio and da Silva, Pedro Giovani and Darvill, Ben and Dauber, Jens and Dejean, Alain and Diek{\"o}tter, Tim and Dominguez-Haydar, Yamileth and Dormann, Carsten F. and Dumont, Bertrand and Dures, Simon G. and Dynesius, Mats and Edenius, Lars and Elek, Zolt{\´a}n and Entling, Martin H. and Farwig, Nina and Fayle, Tom M. and Felicioli, Antonio and Felton, Annika M. and Ficetola, Gentile F. and Filgueiras, Bruno K. C. and Fonte, Steve J. and Fraser, Lauchlan H. and Fukuda, Daisuke and Furlani, Dario and Ganzhorn, J{\"o}rg U. and Garden, Jenni G. and Gheler-Costa, Carla and Giordani, Paolo and Giordano, Simonetta and Gottschalk, Marco S. and Goulson, Dave and Gove, Aaron D. and Grogan, James and Hanley, Mick E. and Hanson, Thor and Hashim, Nor R. and Hawes, Joseph E. and H{\´e}bert, Christian and Helden, Alvin J. and Henden, John-Andr{\´e} and Hern{\´a}ndez, Lionel and Herzog, Felix and Higuera-Diaz, Diego and Hilje, Branko and Horgan, Finbarr G. and Horv{\´a}th, Roland and Hylander, Kristoffer and Horv{\´a}th, Roland and Isaacs-Cubides, Paola and Ishitani, Mashiro and Jacobs, Carmen T. and Jaramillo, Victor J. and Jauker, Birgit and Jonsell, Matts and Jung, Thomas S. and Kapoor, Vena and Kati, Vassiliki and Katovai, Eric and Kessler, Michael and Knop, Eva and Kolb, Annette and K{\"o}r{\"o}si, {\`A}d{\´a}m and Lachat, Thibault and Lantschner, Victoria and Le F{\´e}on, Violette and LeBuhn, Gretchen and L{\´e}gar{\´e}, Jean-Philippe and Letcher, Susan G. and Littlewood, Nick A. and L{\´o}pez-Quintero, Carlos A. and Louhaichi, Mounir and L{\"o}vei, Gabor L. and Lucas-Borja, Manuel Esteban and Luja, Victor H. and Maeto, Kaoru and Magura, Tibor and Mallari, Neil Aldrin and Marin-Spiotta, Erika and Marhall, E. J. P. and Mart{\´i}nez, Eliana and Mayfield, Margaret M. and Mikusinski, Gregorz and Milder, Jeffery C. and Miller, James R. and Morales, Carolina L. and Muchane, Mary N. and Muchane, Muchai and Naidoo, Robin and Nakamura, Akihiro and Naoe, Shoji and Nates-Parra, Guiomar and Navarerete Gutierrez, Dario A. and Neuschulz, Eike L. and Noreika, Norbertas and Norfolk, Olivia and Noriega, Jorge Ari and N{\"o}ske, Nicole M. and O'Dea, Niall and Oduro, William and Ofori-Boateng, Caleb and Oke, Chris O. and Osgathorpe, Lynne M. and Paritsis, Juan and Parrah, Alejandro and Pelegrin, Nicol{\´a}s and Peres, Carlos A. and Persson, Anna S. and Petanidou, Theodora and Phalan, Ben and Philips, T. Keith and Poveda, Katja and Power, Eileen F. and Presley, Steven J. and Proen{\c{c}}a, V{\^a}nia and Quaranta, Marino and Quintero, Carolina and Redpath-Downing, Nicola A. and Reid, J. Leighton and Reis, Yana T. and Ribeiro, Danilo B. and Richardson, Barbara A. and Richardson, Michael J. and Robles, Carolina A. and R{\"o}mbke, J{\"o}rg and Romero-Duque, Luz Piedad and Rosselli, Loreta and Rossiter, Stephen J. and Roulston, T'ai H. and Rousseau, Laurent and Sadler, Jonathan P. and S{\´a}fi{\´a}n, Szbolcs and Salda{\~n}a-V{\´a}squez, Romeo A. and Samneg{\aa}rd, Ulrika and Sch{\"u}epp, Christof and Schweiger, Oliver and Sedlock, Jodi L. and Shahabuddin, Ghazala and Sheil, Douglas and Silva, Fernando A. B. and Slade, Eleanor and Smith-Pardo, Allan H. and Sodhi, Navjot S. and Somarriba, Eduardo J. and Sosa, Ram{\´o}n A. and Stout, Jane C. and Struebig, Matthew J. and Sung, Yik-Hei and Threlfall, Caragh G. and Tonietto, Rebecca and T{\´o}thm{\´e}r{\´e}sz, B{\´e}la and Tscharntke, Teja and Turner, Edgar C. and Tylianakis, Jason M. and Vanbergen, Adam J. and Vassilev, Kiril and Verboven, Hans A. F. and Vergara, Carlos H. and Vergara, Pablo M. and Verhulst, Jort and Walker, Tony R. and Wang, Yanping and Watling, James I. and Wells, Konstans and Williams, Christopher D. and Willig, Michael R. and Woinarski, John C. Z. and Wolf, Jan H. D. and Woodcock, Ben A. and Yu, Douglas W. and Zailsev, Andreys and Collen, Ben and Ewers, Rob M. and Mace, Georgina M. and Purves, Drew W. and Scharlemann, J{\"o}rn P. W. and Pervis, Andy}, title = {The PREDICTS database: a global database of how local terrestrial biodiversity responds to human impacts}, series = {Ecology and Evolution}, volume = {4}, journal = {Ecology and Evolution}, number = {24}, doi = {10.1002/ece3.1303}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-114425}, pages = {4701 - 4735}, year = {2014}, abstract = {Biodiversity continues to decline in the face of increasing anthropogenic pressures such as habitat destruction, exploitation, pollution and introduction of alien species. Existing global databases of species' threat status or population time series are dominated by charismatic species. The collation of datasets with broad taxonomic and biogeographic extents, and that support computation of a range of biodiversity indicators, is necessary to enable better understanding of historical declines and to project - and avert - future declines. We describe and assess a new database of more than 1.6 million samples from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world. The database contains measurements taken in 208 (of 814) ecoregions, 13 (of 14) biomes, 25 (of 35) biodiversity hotspots and 16 (of 17) megadiverse countries. The database contains more than 1\% of the total number of all species described, and more than 1\% of the described species within many taxonomic groups - including flowering plants, gymnosperms, birds, mammals, reptiles, amphibians, beetles, lepidopterans and hymenopterans. The dataset, which is still being added to, is therefore already considerably larger and more representative than those used by previous quantitative models of biodiversity trends and responses. The database is being assembled as part of the PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems - ). We make site-level summary data available alongside this article. The full database will be publicly available in 2015.}, language = {en} } @article{RauSchmittBergetal.2018, author = {Rau, Monika and Schmitt, Johannes and Berg, Thomas and Kremer, Andreas E. and Stieger, Bruno and Spanaus, Katharina and Bengsch, Bertram and Romero, Marta R. and Marin, Jose J. and Keitel, Verena and Klinker, Hartwig and Tony, Hans-Peter and M{\"u}llhaupt, Beat and Geier, Andreas}, title = {Serum IP-10 levels and increased DPPIV activity are linked to circulating CXCR3+ T cells in cholestatic HCV patients}, series = {PLoS ONE}, volume = {13}, journal = {PLoS ONE}, number = {12}, doi = {10.1371/journal.pone.0208225}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-177674}, pages = {e0208225}, year = {2018}, abstract = {Background \& aims Serum interferon-gamma-inducible protein-10 (IP-10) is elevated in cholestatic liver diseases and predicts response to antiviral therapy in patients with chronic hepatitis C virus (HCV) infection. Dipeptidylpeptidase 4 (DPPIV) cleaves active IP-10 into an inactive form, which inhibits recruitment of CXCR3+ T cells to the liver. In this study the link between IP-10 levels, DPPIV activity in serum and CXCR3+ T cells is analysed in cholestatic and non-cholestatic liver patients. Methods In serum DPPIV activity (by enzymatic assay), IP-10 (by ELISA) and bile acids (BA) (by enzymatic assay) were analysed in 229 naive HCV genotype (GT) 1 patients and in 16 patients with cholestatic liver disease. In a prospective follow-up (FU) cohort of 27 HCV GT 1 patients peripheral CD3+CXCR3+, CD4+CXCR3+ and CD8+CXCR3+ cells were measured by FACS. Results In 229 HCV patients serum IP-10 levels correlated positively to DPPIV serum activity. Higher IP-10 levels and DPPIV activity were detected in cholestatic and in cirrhotic HCV patients. Increased IP-10 serum levels were associated with therapeutic non-response to antiviral treatment with pegylated-interferon and ribavirin. In the HCV FU cohort elevated IP-10 serum levels and increased BA were associated with higher frequencies of peripheral CD3+CXCR3+, CD4+CXCR3+ and CD8+CXCR3+ T cells. Positive correlation between serum IP-10 levels and DPPIV activity was likewise validated in patients with cholestatic liver diseases. Conclusions A strong correlation between elevated serum levels of IP-10 and DPPIV activity was seen in different cholestatic patient groups. Furthermore, in cholestatic HCV patients a functional link to increased numbers of peripheral CXCR3+ immune cells could be observed. The source of DPPIV release in cholestatic patients remains open.}, language = {en} } @article{OkadaRotenbergKevanetal.2013, author = {Okada, Michio and Rotenberg, Eli and Kevan, S. D. and Sch{\"a}fer, J. and Ujfalussy, Balazs and Stocks, G. Malcolm and Genatempo, B. and Bruno, E. and Plummer, E. W.}, title = {Evolution of the electronic structure in \(Mo_{1-x}Re_x\) alloys}, series = {New Journal of Physics}, volume = {15}, journal = {New Journal of Physics}, number = {093010}, issn = {1367-2630}, doi = {10.1088/1367-2630/15/9/093010}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-122993}, year = {2013}, abstract = {We report a detailed experimental and theoretical study of the electronic structure of \(Mo_{1-x}Re_x\) random alloys. We have measured electronic band dispersions for clean and hydrogen-covered \(Mo_{1-x}Re_x\) ( 110) with x = 0-0.25 using angle-resolved photoemission spectroscopy. Our results suggest that the bulk and most surface electronic bands shift relative to the Fermi level systematically and approximately rigidly with Re concentration. We distinguish and quantify two contributions to these shifts: a raise of the Fermi energy and an increase of the overall bandwidth. Alloy bands calculated using the first-principles Korringa-Kohn-Rostoker coherent-potential-approximation method accurately predict both of these effects. As derived from the rigid band model, the Fermi energy shift is inversely related to the bulk density of states in this energy region. Using our results, we also characterize an electronic topological transition of the bulk Fermi surface and relate this to bulk transport properties. Finally, we distinguish effects beyond the rigid band approximation: a highly surface-localized state and a composition-dependent impact of the spin-orbit interaction.}, language = {en} } @article{AntoniouKuchenbaeckerSoucyetal.2012, author = {Antoniou, Antonis C. and Kuchenbaecker, Karoline B. and Soucy, Penny and Beesley, Jonathan and Chen, Xiaoqing and McGuffog, Lesley and Lee, Andrew and Barrowdale, Daniel and Healey, Sue and Sinilnikova, Olga M. and Caligo, Maria A. and Loman, Niklas and Harbst, Katja and Lindblom, Annika and Arver, Brita and Rosenquist, Richard and Karlsson, Per and Nathanson, Kate and Domchek, Susan and Rebbeck, Tim and Jakubowska, Anna and Lubinski, Jan and Jaworska, Katarzyna and Durda, Katarzyna and Zlowowcka-Perłowska, Elżbieta and Osorio, Ana and Dur{\´a}n, Mercedes and Andr{\´e}s, Raquel and Ben{\´i}tez, Javier and Hamann, Ute and Hogervorst, Frans B. and van Os, Theo A. and Verhoef, Senno and Meijers-Heijboer, Hanne E. J. and Wijnen, Juul and Garcia, Encarna B. G{\´o}mez and Ligtenberg, Marjolijn J. and Kriege, Mieke and Coll{\´e}e, Margriet and Ausems, Margreet G. E. M. and Oosterwijk, Jan C. and Peock, Susan and Frost, Debra and Ellis, Steve D. and Platte, Radka and Fineberg, Elena and Evans, D. Gareth and Lalloo, Fiona and Jacobs, Chris and Eeles, Ros and Adlard, Julian and Davidson, Rosemarie and Cole, Trevor and Cook, Jackie and Paterson, Joan and Douglas, Fiona and Brewer, Carole and Hodgson, Shirley and Morrison, Patrick J. and Walker, Lisa and Rogers, Mark T. and Donaldson, Alan and Dorkins, Huw and Godwin, Andrew K. and Bove, Betsy and Stoppa-Lyonnet, Dominique and Houdayer, Claude and Buecher, Bruno and de Pauw, Antoine and Mazoyer, Sylvie and Calender, Alain and L{\´e}on{\´e}, M{\´e}lanie and Bressac-de Paillerets, Brigitte and Caron, Olivier and Sobol, Hagay and Frenay, Marc and Prieur, Fabienne and Ferrer, Sandra Fert and Mortemousque, Isabelle and Buys, Saundra and Daly, Mary and Miron, Alexander and Terry, Mary Beth and Hopper, John L. and John, Esther M. and Southey, Melissa and Goldgar, David and Singer, Christian F. and Fink-Retter, Anneliese and Muy-Kheng, Tea and Geschwantler Kaulich, Daphne and Hansen, Thomas V. O. and Nielsen, Finn C. and Barkardottir, Rosa B. and Gaudet, Mia and Kirchhoff, Tomas and Joseph, Vijai and Dutra-Clarke, Ana and Offit, Kenneth and Piedmonte, Marion and Kirk, Judy and Cohn, David and Hurteau, Jean and Byron, John and Fiorica, James and Toland, Amanda E. and Montagna, Marco and Oliani, Cristina and Imyanitov, Evgeny and Isaacs, Claudine and Tihomirova, Laima and Blanco, Ignacio and Lazaro, Conxi and Teul{\´e}, Alex and Del Valle, J. and Gayther, Simon A. and Odunsi, Kunle and Gross, Jenny and Karlan, Beth Y. and Olah, Edith and Teo, Soo-Hwang and Ganz, Patricia A. and Beattie, Mary S. and Dorfling, Cecelia M. and Jansen van Rensburg, Elizabeth and Diez, Orland and Kwong, Ava and Schmutzler, Rita K. and Wappenschmidt, Barbara and Engel, Christoph and Meindl, Alfons and Ditsch, Nina and Arnold, Norbert and Heidemann, Simone and Niederacher, Dieter and Preisler-Adams, Sabine and Gadzicki, Dorothea and Varon-Mateeva, Raymonda and Deissler, Helmut and Gehrig, Andrea and Sutter, Christian and Kast, Karin and Fiebig, Britta and Sch{\"a}fer, Dieter and Caldes, Trinidad and de la Hoya, Miguel and Nevanlinna, Heli and Muranen, Taru A. and Lesp{\´e}rance, Bernard and Spurdle, Amanda B. and Neuhausen, Susan L. and Ding, Yuan C. and Wang, Xianshu and Fredericksen, Zachary and Pankratz, Vernon S. and Lindor, Noralane M. and Peterlongo, Paulo and Manoukian, Siranoush and Peissel, Bernard and Zaffaroni, Daniela and Bonanni, Bernardo and Bernard, Loris and Dolcetti, Riccardo and Papi, Laura and Ottini, Laura and Radice, Paolo and Greene, Mark H. and Loud, Jennifer T. and Andrulis, Irene L. and Ozcelik, Hilmi and Mulligan, Anna Marie and Glendon, Gord and Thomassen, Mads and Gerdes, Anne-Marie and Jensen, Uffe B. and Skytte, Anne-Bine and Kruse, Torben A. and Chenevix-Trench, Georgia and Couch, Fergus J. and Simard, Jacques and Easton, Douglas F.}, title = {Common variants at 12p11, 12q24, 9p21, 9q31.2 and in ZNF365 are associated with breast cancer risk for BRCA1 and/or BRCA2 mutation carriers}, series = {Breast Cancer Research}, volume = {14}, journal = {Breast Cancer Research}, number = {R33}, organization = {CIMBA; SWE-BRCA; HEBON; EMBRACE; GEMO Study Collaborators; kConFab Investigators}, doi = {10.1186/bcr3121}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-130449}, year = {2012}, abstract = {Introduction: Several common alleles have been shown to be associated with breast and/or ovarian cancer risk for BRCA1 and BRCA2 mutation carriers. Recent genome-wide association studies of breast cancer have identified eight additional breast cancer susceptibility loci: rs1011970 (9p21, CDKN2A/B), rs10995190 (ZNF365), rs704010 (ZMIZ1), rs2380205 (10p15), rs614367 (11q13), rs1292011 (12q24), rs10771399 (12p11 near PTHLH) and rs865686 (9q31.2). Methods: To evaluate whether these single nucleotide polymorphisms (SNPs) are associated with breast cancer risk for BRCA1 and BRCA2 carriers, we genotyped these SNPs in 12,599 BRCA1 and 7,132 BRCA2 mutation carriers and analysed the associations with breast cancer risk within a retrospective likelihood framework. Results: Only SNP rs10771399 near PTHLH was associated with breast cancer risk for BRCA1 mutation carriers (per-allele hazard ratio (HR) = 0.87, 95\% CI: 0.81 to 0.94, P-trend = 3 x 10\(^{-4}\)). The association was restricted to mutations proven or predicted to lead to absence of protein expression (HR = 0.82, 95\% CI: 0.74 to 0.90, P-trend = 3.1 x 10\(^{-5}\), P-difference = 0.03). Four SNPs were associated with the risk of breast cancer for BRCA2 mutation carriers: rs10995190, P-trend = 0.015; rs1011970, P-trend = 0.048; rs865686, 2df P = 0.007; rs1292011 2df P = 0.03. rs10771399 (PTHLH) was predominantly associated with estrogen receptor (ER)-negative breast cancer for BRCA1 mutation carriers (HR = 0.81, 95\% CI: 0.74 to 0.90, P-trend = 4 x 10\(^{-5}\)) and there was marginal evidence of association with ER- negative breast cancer for BRCA2 mutation carriers (HR = 0.78, 95\% CI: 0.62 to 1.00, P-trend = 0.049). Conclusions: The present findings, in combination with previously identified modifiers of risk, will ultimately lead to more accurate risk prediction and an improved understanding of the disease etiology in BRCA1 and BRCA2 mutation carriers.}, language = {en} } @article{ManchiaAdliAkulaetal.2013, author = {Manchia, Mirko and Adli, Mazda and Akula, Nirmala and Arda, Raffaella and Aubry, Jean-Michel and Backlund, Lena and Banzato, Claudio E. M. and Baune, Bernhard T. and Bellivier, Frank and Bengesser, Susanne and Biernacka, Joanna M. and Brichant-Petitjean, Clara and Bui, Elise and Calkin, Cynthia V. and Cheng, Andrew Tai Ann and Chillotti, Caterina and Cichon, Sven and Clark, Scott and Czerski, Piotr M. and Dantas, Clarissa and Del Zompo, Maria and DePaulo, J. Raymond and Detera-Wadleigh, Sevilla D. and Etain, Bruno and Falkai, Peter and Fris{\´e}n, Louise and Frye, Mark A. and Fullerton, Jan and Gard, S{\´e}bastien and Garnham, Julie and Goes, Fernando S. and Grof, Paul and Gruber, Oliver and Hashimoto, Ryota and Hauser, Joanna and Heilbronner, Urs and Hoban, Rebecca and Hou, Liping and Jamain, St{\´e}phane and Kahn, Jean-Pierre and Kassem, Layla and Kato, Tadafumi and Kelsoe, John R. and Kittel-Schneider, Sarah and Kliwicki, Sebastian and Kuo, Po-Hsiu and Kusumi, Ichiro and Laje, Gonzalo and Lavebratt, Catharina and Leboyer, Marion and Leckband, Susan G. and L{\´o}pez Jaramillo, Carlos A. and Maj, Mario and Malafosse, Alain and Martinsson, Lina and Masui, Takuya and Mitchell, Philip B. and Mondimore, Frank and Monteleone, Palmiero and Nallet, Audrey and Neuner, Maria and Nov{\´a}k, Tom{\´a}s and O'Donovan, Claire and {\"O}sby, Urban and Ozaki, Norio and Perlis, Roy H. and Pfennig, Andrea and Potash, James B. and Reich-Erkelenz, Daniela and Reif, Andreas and Reininghaus, Eva and Richardson, Sara and Rouleau, Guy A. and Rybakowski, Janusz K. and Schalling, Martin and Schofield, Peter R. and Schubert, Oliver K. and Schweizer, Barbara and Seem{\"u}ller, Florian and Grigoroiu-Serbanescu, Maria and Severino, Giovanni and Seymour, Lisa R. and Slaney, Claire and Smoller, Jordan W. and Squassina, Alessio and Stamm, Thomas and Steele, Jo and Stopkova, Pavla and Tighe, Sarah K. and Tortorella, Alfonso and Turecki, Gustavo and Wray, Naomi R. and Wright, Adam and Zandi, Peter P. and Zilles, David and Bauer, Michael and Rietschel, Marcella and McMahon, Francis J. and Schulze, Thomas G. and Alda, Martin}, title = {Assessment of Response to Lithium Maintenance Treatment in Bipolar Disorder: A Consortium on Lithium Genetics (ConLiGen) Report}, series = {PLoS ONE}, volume = {8}, journal = {PLoS ONE}, number = {6}, doi = {10.1371/journal.pone.0065636}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-130938}, pages = {e65636}, year = {2013}, abstract = {Objective: The assessment of response to lithium maintenance treatment in bipolar disorder (BD) is complicated by variable length of treatment, unpredictable clinical course, and often inconsistent compliance. Prospective and retrospective methods of assessment of lithium response have been proposed in the literature. In this study we report the key phenotypic measures of the "Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder" scale currently used in the Consortium on Lithium Genetics (ConLiGen) study. Materials and Methods: Twenty-nine ConLiGen sites took part in a two-stage case-vignette rating procedure to examine inter-rater agreement [Kappa (\(\kappa\))] and reliability [intra-class correlation coefficient (ICC)] of lithium response. Annotated first-round vignettes and rating guidelines were circulated to expert research clinicians for training purposes between the two stages. Further, we analyzed the distributional properties of the treatment response scores available for 1,308 patients using mixture modeling. Results: Substantial and moderate agreement was shown across sites in the first and second sets of vignettes (\(\kappa\) = 0.66 and \(\kappa\) = 0.54, respectively), without significant improvement from training. However, definition of response using the A score as a quantitative trait and selecting cases with B criteria of 4 or less showed an improvement between the two stages (\(ICC_1 = 0.71\) and \(ICC_2 = 0.75\), respectively). Mixture modeling of score distribution indicated three subpopulations (full responders, partial responders, non responders). Conclusions: We identified two definitions of lithium response, one dichotomous and the other continuous, with moderate to substantial inter-rater agreement and reliability. Accurate phenotypic measurement of lithium response is crucial for the ongoing ConLiGen pharmacogenomic study.}, language = {en} }