Utility of in vivo metabolomics to support read-across for UVCB substances under REACH

被引:0
|
作者
H. Kamp
N. Aygun Kocabas
F. Faulhammer
N. Synhaeve
E. Rushton
B. Flick
V. Giri
S. Sperber
L. G. Higgins
M. G. Penman
B. van Ravenzwaay
M. Rooseboom
机构
[1] BASF Metabolome Solutions GmbH,
[2] TotalEnergies Refining & Chemicals,undefined
[3] Shell Global Solution International B.V,undefined
[4] BASF SE,undefined
[5] ExxonMobil,undefined
[6] LyondellBasell,undefined
[7] Environmental Sciences Consulting,undefined
[8] LOA C/O Penman Consulting Ltd,undefined
[9] NUVISAN ICB GmbH,undefined
[10] Toxicology,undefined
来源
Archives of Toxicology | 2024年 / 98卷
关键词
UVCB; Read-across; Metabolomics; REACH; New approach methodologies (NAMs); Chemical grouping;
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中图分类号
学科分类号
摘要
Structure-based grouping of chemicals for targeted testing and read-across is an efficient way to reduce resources and animal usage. For substances of unknown or variable composition, complex reaction products, or biological materials (UVCBs), structure-based grouping is virtually impossible. Biology-based approaches such as metabolomics could provide a solution. Here, 15 steam-cracked distillates, registered in the EU through the Lower Olefins Aromatics Reach Consortium (LOA), as well as six of the major substance constituents, were tested in a 14-day rat oral gavage study, in line with the fundamental elements of the OECD 407 guideline, in combination with plasma metabolomics. Beyond signs of clinical toxicity, reduced body weight (gain), and food consumption, pathological investigations demonstrated the liver, thyroid, kidneys (males only), and hematological system to be the target organs. These targets were confirmed by metabolome pattern recognition, with no additional targets being identified. While classical toxicological parameters did not allow for a clear distinction between the substances, univariate and multivariate statistical analysis of the respective metabolomes allowed for the identification of several subclusters of biologically most similar substances. These groups were partly associated with the dominant (> 50%) constituents of these UVCBs, i.e., indene and dicyclopentadiene. Despite minor differences in clustering results based on the two statistical analyses, a proposal can be made for the grouping of these UVCBs. Both analyses correctly clustered the chemically most similar compounds, increasing the confidence that this biological approach may provide a solution for the grouping of UVCBs.
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页码:755 / 768
页数:13
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