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Lea Teutenberg

As seen in: Nature, JAMA Psychiatry
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Articles by Lea Teutenberg

Counteracting the overestimation of effect size in mass-univariate brain-wide association studies using cross-validation

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By Janik Goltermann, Nils Winter, Marius Gruber, Lukas Fisch, Maike Richter, Dominik Grotegerd, Katharina Dohm, Susanne Meinert, Elisabeth Leehr, Joscha Böhnlein, Anna D. Kraus, Katharina Thiel, Alexandra Winter, Kira Flinkenflügel, Ramona Leenings, Carlotta Barkhau, Jan Ernsting, Klaus Berger, Heike Minnerup, Benjamin Straube, Nina Alexander, Hamidreza Jamalabadi, Frederike Stein, Katharina Brosch, Adrian Wroblewski, Florian Thomas-Odenthal, Paula Usemann, Lea Teutenberg, Andreas Jansen, Igor Nenadic, Tilo Kircher, Christian Gaser, Nils Opel, Tim Hahn Verified, Udo Dannlowski, Julia-Katharina Pfarr
| Nature Verified
Abstract Brain-wide association effects are commonly overestimated in psychiatric neuroimaging research, leading to low replicability and generalizability of findings, and ultimately to poor translation to clinical utility. Cross-validation is currently not standardly used in univariate neuroimaging analyses but could pose a potential counteracting measure for this problem.
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Multimodal Machine Learning–Based Prediction of Relapse in Major Depressive Disorder

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By Lea Teutenberg, Nils Winter, Paula Usemann, Frederike Stein, Florian Thomas-Odenthal, Kira Flinkenflügel, Tiana Borgers, Susanne Meinert, Elisabeth Leehr, Dominik Grotegerd, Anne Sophie Hildebrand, Keyvan Mahjoory, Maximilian Konowski, Jennifer Spanagel, Leon Fehse, Dominik Heider, Till F. M. Andlauer, Friederike David, Andreas J. Forstner, Harald Renz, Corinna Bang, Andre Franke, Stephanie Witt, Marcella Rietschel, Fabian Streit, Nina Alexander, Andreas Jansen, Igor Nenadic, Benjamin Straube, Hamidreza Jamalabadi, Udo Dannlowski, Tim Hahn Verified, Tilo Kircher, Sara Papenbrock, Sabrina Teckentrup, Sarah Wellms, Philipp Schöppner
| JAMA Psychiatry Verified
Key Points Question Does machine learning–based integration of multiple data modalities, relative to single data modalities, improve relapse prediction in major depressive disorder? Findings In this prognostic study, depressive relapse within 2 years was predicted among 564 patients with major depressive disorder, with a highest classification accuracy of 64.43%.
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Resilience beyond diagnosis: prospective neural correlates of better-than-expected outcomes in depression

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By Vincent Hammes, Katharina Brosch, Paula Usemann, Friederike David, Hannah Scherer, Christina V Schmitter, Jochen Bauer, Tiana Borgers, Kira Flinkenflügel, Dominik Grotegerd, Elisabeth Leehr, Susanne Meinert, Frederike Stein, Lea Teutenberg, Florian Thomas-Odenthal, Udo Dannlowski, Tim Hahn Verified, Hamidreza Jamalabadi, Andreas Jansen, Robert Miller, Igor Nenadic, Benjamin Straube, Albrecht Stroh, Tilo Kircher, Nina Alexander
| Nature Verified
Abstract Resilience, the ability to adapt positively in the face of adversity, is shaped by combined influences of risk and protective factors. Previous neuroimaging studies on resilience have predominantly focused on single factors, often operationalizing resilience dichotomously as the absence of psychiatric disorders despite adversity.
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The effect of SSRI/SNRI antidepressant treatment on the gut microbiota of patients with major depressive disorder

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By Danique Mulder, Leon Fehse, Nils Winter, Lukas Fisch, Marius Welzel, Corinna Bang, Susanne Meinert, Kira Flinkenflügel, Tiana Borgers, Janik Goltermann, Elisabeth Leehr, Carsten Culmsee, Frederike Stein, Florian Thomas-Odenthal, Paula Usemann, Lea Teutenberg, Igor Nenadic, Benjamin Straube, Nina Alexander, Hamidreza Jamalabadi, Andreas Jansen, Robert Nitsch, Andre Franke, Udo Dannlowski, Tilo Kircher, Dominik Heider, Tim Hahn Verified, Janna N. Vrijsen, Philip van Eijndhoven, Indira Tendolkar, Andreas Reif, Sharmili Edwin Thanarajah, Silke Matura, Alejandro Arias Vasquez, Mirjam Bloemendaal, Eugenia Emile Natasha, Andreas Lügering
| Nature Verified
Abstract The gut microbiome has been linked to major depressive disorder (MDD), yet it remains unclear whether antidepressant treatment influences these associations. This study aimed to clarify the role of serotonin reuptake inhibitors (SSRI/SNRI) in shaping gut microbiome changes observed in MDD.
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Cortical morphometry might predict currently prescribed vs. discontinued medications in bipolar disorder, even after controlling for the cumulative dose effects: An ENIGMA mega-analysis

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By Lydia Fortea, Miguel Ángel Rivas-Fernández, Aleix Solanes, Sinead King, Leila Nabulsi, Martin Alda, Nina Alexander, Jochen Bauer, Francesco Benedetti, Tiana Borgers, Beatrice Bravi, Irene Bollettini, Erick J. Canales-Rodriguez, Dara M. Cannon, Udo Dannlowski, Annabella Di Giorgio, Kira Flinkenflügel, Paola Fuentes-Claramonte, Lisa Furlong, Ian H. Gotlib, Melissa Green, Dominik Grotegerd, Tim Hahn Verified, Tomas Hajek, Diego Hidalgo-Mazzei, Fleur M Howells, Hamidreza Jamalabadi, Andreas Jansen, James A. Karantonis, Andriana Karuk, Tilo Kircher, Elisabeth Leehr, Yanghee Im, Sean R. McWhinney, Susanne Meinert, Igor Nenadic, Andrea Pfennig, Sara Poletti, Edith Pomarol-Clotet, Yann Quidé, Susan L Rossell, Matthew D. Sacchet, Raymond Salvador, Fabio Sambataro, Salvador Sarró, Freda Scheffler, Kang Hee Sim, Dan Stein, Frederike Stein, Benjamin Straube, Henk S. Temmingh, Florian Thomas-Odenthal, Sophia I. Thomopoulos, Tamsyn Van Rheenen, Enric Vilajosana, Ling-Li Zeng, Ole A. Andreassen, Eduard Vieta, Paul Thompson, Colm McDonald, Joaquim Radua, Bartholomeus C. M. Haarman, Melody J. Y. Kang, Elisa MT Melloni, Lea Teutenberg, Christopher R. K. Ching
| Nature Verified
Abstract Recent research suggests that brain anatomy may help identify the most effective pharmacological treatment for each individual with bipolar disorder and reduce trial-and-error prescribing. We aimed to investigate whether brain anatomy predicts whether a medication is currently prescribed or has been discontinued, as a proxy for treatment effectiveness.
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