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Classification of Developmental Toxicants in a Human iPSC Transcriptomics-Based Test

Anna Cherianidou, Florian Seidel, Franziska Kappenberg, Nadine Dreser, Jonathan Blum, Tanja Waldmann, Nils Blüthgen, Johannes Meisig, Katrin Madjar, Margit Henry, Tamara Rotshteyn, Rosemarie Marchan, Karolina Edlund, Marcel Leist, Jörg Rahnenführer, Agapios Sachinidis, and Jan G. Hengstler (13 April 2022).

doi.org/10.1021/acs.chemrestox.1c00392

The assessment of the potential for developmental toxicity in drugs is usually based on in vivo testing, and thus comes with high costs and high number of required animals. Here, the hiPSC-based UKK2 in vitro test, using genome-wide expression profiles, is proposed. Two classifiers were considered, where the cross-validated AUC for the considered set of 23 compounds that are known to cause developmental toxicity (teratogens) and 16 non-teratogens was 0.96, when including information about cytotoxicity to the l1-penalized logistic regression-based classifier.

Evaluation of tree-based statistical learning methods for constructing genetic risk scores.

Lau M, Wigmann C, Kress S, Schikowski T, Schwender H. BMC Bioinformatics 23, 97 (21 March 2022).

doi.org/10.1186/s12859-022-04634-w

Genetic risk scores are a valuable tool for assessing individual disease risks and uncovering biological mechanisms. Thus far, mainly linear construction approaches not considering gene-gene interactions are employed. In simulations and a real data application, we show that tree-based approaches based on random forests and logic regression are able to yield superior genetic risk score models.

Influence of bile acids on the cytotoxicity of chemicals in cultivated human hepatocytes.

Tim Brecklinghaus, Wiebke Albrecht, Franziska Kappenberg, Julia Duda, Mian Zhangc, Iain Gardner, Rosemarie Marchan, Ahmed Ghallaba, Özlem Demirci Turgunbayera, Jörg Rahnenführer, Jan G.Hengstler 2022 March 6:105344

doi:10.1016/j.tiv.2022.105344

Bile acids are known to influence the susceptibility of hepatocytes to chemicals. Cytotoxicity of 18 compounds with known hepatotoxicity status was assessed with and without the addition of a Bile acids mix. EC10 values of 7 compounds were notably decreased by the Bile acids, and notably increased for 5 compounds. No improvement of the separation between hepatotoxic and non-hepatotoxic compounds, assessed by a recently introduced method, could be observed.

Model selection characteristics when using MCP-Mod for dose-response gene expression data.

Duda J, Kappenberg F, Rahnenführer J. 2022 February 20; 202000250

doi: 10.1002/bimj.202000250

Advances in genomics bring forward increasingly large omics data sets, such that even concentration-resolved gene expression data are available. We transfer well established dose-response theory from clinical research to toxicological gene expression data.

Multiple-Comparison-Procedure and Modeling (MCP-Mod) is a relatively new dose-response modeling technique developed for Phase II clinical dose-finding trials that accounts for model uncertainty. By applying MCP-Mod on a concentration-resolved gene expression data set, we find that commonly assumed monotonicity is not adequate and model uncertainty should be considered.

The hepatocyte export carrier inhibition assay improves the separation of hepatotoxic from non-hepatotoxic compounds.

Brecklinghaus T, Albrecht W, Kappenberg F, Duda J, Vartak N, Edlund K, Marchan R, Ghallab A, Cadenas C, Günther G, Leist M,Zhang M, Gardner I, Reinders J, Russel FG, Foster AJ, Williams DP, Damle-Vartak A, Grandits M, Ecker G, Kittana N, Rahnenführer J,Hengstler JG.Chem Biol Interact. 2021 Oct 27;351:109728.

doi: 10.1016/j.cbi.2021.109728.

The risk of drug-induced liver injury has recently been addressed by a new method aimed at distinguishing between hepatotoxic and non-hepatotoxic compounds, based on the determination of alert concentration from toxicological data. In this work, a new biological assay was used to calculate the alert concentration. Data from this assay were modeled in a flexible manner using the MCP-Mod (Multiple Comparison Procedure and Modeling) method to determine different alert concentrations, resulting in improved discrimination between hepatotoxic and non-hepatotoxic compounds.

Spatio-Temporal Multiscale Analysis of Western Diet-Fed Mice Reveals a Translationally Relevant Sequence of Events during NAFLD Progression.

Ghallab A, Myllys M, Friebel A, Duda J, Edlund K, Halilbasic E, Vucur M, Hobloss Z, Brackhagen L, Begher-Tibbe B, Hassan R, Burke M, Genc E, Frohwein LJ, Hofmann U, Holland CH, González D, Keller M, Seddek AL, Abbas T, Mohammed ESI, Teufel A, Itzel T, Metzler S, Marchan R, Cadenas C, Watzl C, Nitsche MA, Kappenberg F, Luedde T, Longerich T, Rahnenführer J, Hoehme S, Trauner M, Hengstler JG. Cells. 2021 Sep 23;10(10):2516.

doi: 10.3390/cells10102516.

Non-alcoholic fatty liver disease (NAFLD) is a chronic liver disease that afftects more than one billion people worldwide with an increasing incidence. We analyze mice that are fed a fast-food style 'Western-Diet' (WD), a well-known contributor ot human NAFLD. This work is the first time-resolved study of NAFLD in the sense that pathophysiological and transcriptomical changes of the mice relative to 9 different feeding durations with WD are analyzed.

A series of key events that occur with prolonged WD, such as lipid droplet formation and hepatocellular cancer, were identified. These key events recapitulate many features of human disease and offer a basis for the identification of therapeutic targets.