Inhibition, Intestinal FXR

60-35-5

DLFVBJFMPXGRIB-UHFFFAOYSA-N

Acetamide

Acetamid acetamida Acetic acid amide Acetimidic acid Ethanamide Ethanimidic acid Methanecarboxamide NSC 25945

DTXSID7020005

103-90-2

RZVAJINKPMORJF-UHFFFAOYSA-N

Acetaminophen

4-Acetamidophenol APAP Paracetamol 4-hydroxyacetanilide Acetamide, N-(4-hydroxyphenyl)- 4-(Acetylamino)phenol 4-(N-Acetylamino)phenol 4-Acetaminophenol 4'-Hydroxyacetanilide Abensanil Acetagesic Acetalgin ACETAMIDE, N-(4-HYDROXYPHENYL) Acetaminofen Acetanilide, 4'-hydroxy- ACETANILIDE, 4-HYDROXY- Algotropyl Alvedon Anaflon Apamide Banesin Ben-u-ron Bickie-mol Biocetamol Cetadol Citramon P Claratal Clixodyne Dafalgan Daphalgan Dial-a-gesic Disprol Doliprane Dolprone Dymadon Efferalgan Endophy Febrilex Febrilix Febro-Gesic Febrolin Fepanil Finimal Gattaphen T Gelocatil Gutte Enteric Homoolan Jin Gang Lestemp Liquagesic Lonarid Lyteca Syrup Minoset Momentum N-(4-Hydroxyphenyl)acetamide N-Acetyl-4-aminophenol N-Acetyl-4-hydroxyaniline N-Acetyl-p-aminophenol Napafen Naprinol Nobedon NSC 109028 NSC 3991 Ortensan p-(Acetylamino)phenol p-Aceaminophenol Pacemol p-Acetamidophenol p-Acetoaminophen P-ACETYLAMINOPHENOL Paldesic panadeine Panadol Panadol Actifast Panadol Extend Panaleve Panasorb Panodil Paracetamol DC Paracetamole Parageniol Paramol Paraspen Parelan Pasolind N Perfalgan Phenaphen Phendon p-Hydroxyacetanilide Prodafalgan Puerxitong Pyrinazine Resfenol Resprin Rhodapop NCR Salzone Tabalgin Tachipirina Tempanal Tralgon Tylenol TylolHot Valadol Valgesic Vermidon Vick Pyrena

DTXSID2020006

968-81-0

VGZSUPCWNCWDAN-UHFFFAOYSA-N

Acetohexamide

Benzenesulfonamide, 4-acetyl-N-[(cyclohexylamino)carbonyl]- 1-(p-Acetylbenzenesulfonyl)-3-cyclohexylurea 1-[(p-Acetylphenyl)sulfonyl]-3-cyclohexylurea Acetohexamid acetohexamida Dimelin Dimelor Dymelor Gamadiabet Hypoglicil Metaglucina Minoral N-(p-Acetylphenylsulfonyl)-N'-cyclohexylurea Ordimel Tsiklamid Urea, 1-[(p-acetylphenyl)sulfonyl]-3-cyclohexyl-

DTXSID7020007

67-66-3

HEDRZPFGACZZDS-UHFFFAOYSA-N

Chloroform

Trichloromethane Methane, trichloro- CARBON TRICHLORIDE Chloroforme cloroformo Formyl trichloride Methane trichloride Methane,trichloro- NSC 77361 Trichloroform UN 1888

DTXSID1020306

110-00-9

YLQBMQCUIZJEEH-UHFFFAOYSA-N

Furan

Divinylene oxide furanne Furfuran Oxacyclopentadiene Tetrole UN 2389

DTXSID6020646

7429-90-5

XAGFODPZIPBFFR-UHFFFAOYSA-N

AZDRQVAHHNSJOQ-UHFFFAOYSA-N

Aluminum

Aisin Metal Fiber Al 050P-H24 ALC Fine Alcan XI 1391 Almi-Paste SSP 303AR Aloxal 3010 Alpaste 00-0506 Alpaste 0100M Alpaste 0100MA Alpaste 0100M-C Alpaste 0200M Alpaste 0200T Alpaste 0230M Alpaste 0230T Alpaste 0241M Alpaste 0300M Alpaste 0500M Alpaste 0539X Alpaste 0620MS Alpaste 0625TS Alpaste 0638-70C Alpaste 0700M Alpaste 0780M Alpaste 0900M Alpaste 100M Alpaste 100MS Alpaste 100MSR Alpaste 1100M Alpaste 1100MA Alpaste 1100N Alpaste 1100NA Alpaste 1109MA Alpaste 1109MC Alpaste 1200M Alpaste 1200T Alpaste 1260MS Alpaste 1500MA Alpaste 1700NL Alpaste 1810YL Alpaste 1830YL Alpaste 1900M Alpaste 1900XS Alpaste 1950M Alpaste 1950N Alpaste 210N Alpaste 2172EA Alpaste 2173 Alpaste 240T Alpaste 241M Alpaste 417 Alpaste 46-046 Alpaste 4-621 Alpaste 4919 Alpaste 50-63 Alpaste 50-635 Alpaste 51-148B Alpaste 51-231 Alpaste 5205N Alpaste 5207N Alpaste 52-509 Alpaste 52-568 Alpaste 5301N Alpaste 5302N Alpaste 53-119 Alpaste 5422NS Alpaste 54-452 Alpaste 54-497 Alpaste 54-542 Alpaste 55-516 Alpaste 55-519 Alpaste 55-574 Alpaste 5620NS Alpaste 5630NS Alpaste 5640NS Alpaste 56-501 Alpaste 5650NS Alpaste 5653NS Alpaste 5654NS Alpaste 5680N Alpaste 5680NS Alpaste 60-600 Alpaste 60-760 Alpaste 60-768 Alpaste 62-356 Alpaste 6340NS Alpaste 6370NS Alpaste 6390NS Alpaste 640NS Alpaste 65-388 Alpaste 66NLB Alpaste 710N Alpaste 7130N Alpaste 7160N Alpaste 7160NS Alpaste 725N Alpaste 740NS Alpaste 7430NS Alpaste 7580NS Alpaste 7620NS Alpaste 7640NS Alpaste 7670M Alpaste 7670NS Alpaste 7675NS Alpaste 7679NS Alpaste 7680N Alpaste 7680NS Alpaste 76840NS Alpaste 7730N Alpaste 7770N Alpaste 7830N Alpaste 8004 Alpaste 8080N Alpaste 8260NAR Alpaste 891K Alpaste 91-0562 Alpaste 92-0592 Alpaste 93-0595 Alpaste 93-0647 Alpaste 94-2315 Alpaste 95-0570 Alpaste 96-0635 Alpaste 96-2104 Alpaste 97-0510 Alpaste 97-0534 Alpaste AW 520B Alpaste AW 612 Alpaste AW 9800 Alpaste F 795 Alpaste FM 7680K Alpaste FX 440 Alpaste FX 910 Alpaste FZ 0534 Alpaste FZU 40C Alpaste G Alpaste HR 8801 Alpaste HS 2 Alpaste J Alpaste K 9800 Alpaste MC 666 Alpaste MC 707 Alpaste MF 20 Alpaste MG 01 Alpaste MG 1000 Alpaste MG 1300 Alpaste MG 500 Alpaste MG 600 Alpaste MH 6601 Alpaste MH 8801 Alpaste MH 9901 Alpaste MR 7000 Alpaste MR 9000 Alpaste MS 630 Alpaste N 1700NL Alpaste NS 7670 Alpaste O 100N Alpaste O 2130 Alpaste O 300M Alpaste P 0100 Alpaste P 1950 Alpaste S Alpaste SAP 110 Alpaste SAP 414P Alpaste SAP 550N Alpaste SCR 5070 Alpaste TCR 2020 Alpaste TCR 2060 Alpaste TCR 2070 Alpaste TCR 3010 Alpaste TCR 3030 Alpaste TCR 3040 Alpaste TCR 3130 Alpaste TD 200T Alpaste UF 500 Alpaste WB 0230 Alpaste WD 500 Alpaste WJP-U 75C Alpaste WX 0630 Alpaste WX 7830 Alpaste WXA 7640 Alpaste WXM 0630 Alpaste WXM 0650 Alpaste WXM 0660 Alpaste WXM 1415 Alpaste WXM 1440 Alpaste WXM 5422 Alpaste WXM 760b Alpaste WXM 7640 Alpaste WXM 7675 Alpaste WXM-T 60B Alpaste WXM-U 75 Alpaste WXM-U 75C Altop X Aluchrome Ultrafin Super Alumat 1600 Alumet H 30 aluminio Aluminium Aluminium Flake Aluminum 27 Aluminum atom Aluminum element Aluminum Flake PCF 7620 Aluminum granules ALUMINUM METAL/GRANULE ALUMINUM PASTE ALUMINUM PIGMENT ALUMINUM TURNINGS Alumi-paste 640NS Alumipaste 91-0562 Alumipaste 98-1822T Alumipaste AW 620 Alumipaste CR 300 Alumipaste GX 180A Alumipaste GX 201A Alumipaste HR 7000 Alumipaste HR 850 Alumipaste MG 11 Alumipaste MH 8801 Aquamet NPW 2900 Aquapaste 205-5 Aquasilver LPW Astroflake 40 Astroflake Black N 020 Astroflake Black N 070 Astroflake LG 40 Astroflake LG 70 Astroflake Silver N 040 Astroshine NJ 1600 Astroshine T 8990 Atomizalumi VA 200 C.I. PIGMENT METAL 1 Chromal IV Chromal X Decomet 1001/10 Decomet 2018/10 Decomet High Gloss Al 1002/10 Ecka AS 081 Eckart 9155 Eterna Brite 301-1 Eterna Brite 601-1 Eterna Brite 651-1 Eterna Brite EBP 251PA Eterna Brite Primier 251PA Ferro FX 53-038 Friend Color F 500GR-W Friend Color F 500WT Friend Color F 700RE-W Friend Color F 701RE-W Hi Print 60T High Print 60T Hisparkle HS 2 Hydro Paste 8726 Hydrolac WHH 2153 Hydrolan 3560 Hydrolux Reflexal 100 Hydroshine WS 1001 JISA 51010P Kryal Z Lansford 243 LE Sheet 800 Leafing Alpaste LG-H Silver 25 Lunar Al-V 95 Metallux 161 Metallux 2154 Metallux 2192 Metalure Metalure 55350 Metalure L 55350 Metalure L 59510 Metalure W 2001 Metapor Metasheen 1800 Metasheen HR 0800 Metasheen KM 100 Metasheen KM 1000 Metasheen Slurry 1807 Metasheen Slurry 1811 Metasheen Slurry KM 100 Metax G Metax S Mirror Glow 1000 Mirror Glow 600 Mirrorsheen Noral Aluminium Noral Ink Grade Aluminium Obron 10890 Offset FM 4500 Puratronic Reflexal 145 Reynolds 400 Reynolds 4-301 Reynolds 4-591 Reynolds 667 SAP 260PW-HS SAP-FM 4010 SBC 516-20Z Scotchcal 7755SE Serumekku Setanium 50MIS-H8 Siberline ET 2025 Siberline ST 21030E1 Silvar A Silver VT 522 Silverline SSP 353 Silvex 793-20C Sparkle Silver 3141ST Sparkle Silver 3500 Sparkle Silver 3641 Sparkle Silver 5000AR Sparkle Silver 516AR Sparkle Silver 5242AR Sparkle Silver 5245AR Sparkle Silver 5271AR Sparkle Silver 5500 Sparkle Silver 5745 Sparkle Silver 7000AR Sparkle Silver 7005AR Sparkle Silver 7500 Sparkle Silver 960-25E1 Sparkle Silver E 1745AR Sparkle Silver L 1526AR Sparkle Silver Premier 751 Sparkle Silver SS 3130 Sparkle Silver SS 5242AR Sparkle Silver SS 5588 Sparkle Silver SSP 132AR Special PCR 507 Splendal 6001BG Spota Mobil 801 SSP 760-20C Stapa Aloxal PM 2010 Stapa Aloxal PM 3010 Stapa Aloxal PM 4010 Stapa Hydrolac BG 8n.1 Stapa Hydrolac BGH Chromal X Stapa Hydrolac PM Chromal VIII Stapa Hydrolac W 60NL Stapa Hydrolac WH 16 Stapa Hydrolac WH 66NL Stapa Hydrolux 2192 Stapa Hydrolux 8154 Stapa IL Hydrolan 2192-55900G Stapa Metallic R 607 Stapa Metallux 1050 Stapa Metallux 211 Stapa Metallux 212 Stapa Metallux 2196 Stapa Metallux 274 Stapa Mobilux 181 Stapa Offset 3000 Stapa PV 10 Stapa VP 46432G Starbrite 2100 Super Fine 18000 Super Fine 22000 Supramex 2022 Toyo Aluminum 02-0005 Toyo Aluminum 93-3040 Transmet K 102HE Tufflake 3645 Tufflake 5843 UN 1396 US Aluminum 809 Valimet H 2 Valimet H 3 White Silver 7080N White Silver 7130N

DTXSID3040273

7440-43-9

BDOSMKKIYDKNTQ-UHFFFAOYSA-N

Cadmium

Cadimium CADMIUM BLUE CADMIUM, IN PLATTEN, STANGEN, BROCKEN,KOERNER

DTXSID1023940

7439-97-6

QSHDDOUJBYECFT-UHFFFAOYSA-N

Mercury

Liquid silver Mercure MERCURIC METAL TRIPLE DISTILLED mercurio Mercury element Quecksilber Quicksilver UN 2024 UN 2809

DTXSID1024172

7440-61-1

JFALSRSLKYAFGM-UHFFFAOYSA-N

Uranium

Uranium, isotope of mass 238 238U Element UN 2979 (DOT) Uranium I

DTXSID1042522

7440-38-2

RQNWIZPPADIBDY-UHFFFAOYSA-N

Arsenic

As Arsenic black ARSENIC METAL arsenico Grey arsenic UN 1558

DTXSID4023886

7440-22-4

BQCADISMDOOEFD-UHFFFAOYSA-N

Silver

Ag Nanopaste NPS-J 90 Ag Sphere 2 Ag-C-GS Algaedyn Arctic Silver 3 Argentum Astroflake 5 Carey Lea silver Colloidal silver Dotite XA 208 Du Pont 4943 ECM 100AF4810 Enlight 600 Enlight silver plate 600 Epinall Finesphere SVND 102 Fordel DC FP 5369-502 Jelcon SH 1 Jungindai Takasago 300 KS (metal) LCP 1-19SFS Metz 3000-1 Nanomelt AGC-A Nanomelt Ag-XA 301 Nanomelt Ag-XF 301 Nanomelt Ag-XF 301H Nanopaste NPS-J 90 Perfect Silver Puff Silver X 1200 RT 1710S-C1 SD (metal) Shell Silver Silbest E 20 Silbest F 20 Silbest J 18 Silbest TC 12 Silbest TC 20E Silbest TC 25A Silbest TCG 1 Silbest TCG 7 Silcoat AgC 103 Silcoat AgC 2011 Silcoat AgC 209 Silcoat AgC 2190 Silcoat AgC 222 Silcoat AgC 2411 Silcoat AgC 74T Silcoat AgC-A Silcoat AgC-AO Silcoat AgC-B Silcoat AgC-BO Silcoat AgC-D Silcoat AgC-G Silcoat AgC-GS Silcoat AgC-L Silcoat AgC-O Silcoat GS Silcoat RF 200 Silflake 135 Silsphere 514 Silver atom Silver element Silver Flake 1 Silver Flake 25 Silver Flake 52 Silver Flake 7A SILVER FLAKES Silver metal Silvest TCG 11N Technic 299 Technic 450 Techno Alpha 175

DTXSID4024305

7439-96-5

PWHULOQIROXLJO-UHFFFAOYSA-N

Manganese

Colloidal manganese Cutaval Manganese element Manganese fulleride Manganese metal alloy Manganese-55 manganeso

DTXSID2024169

7440-02-0

PXHVJJICTQNCMI-UHFFFAOYSA-N

Nickel

Carbonyl 255 Carbonyl Ni 123 Carbonyl Ni 283 Carbonyl Nickel 123 Carbonyl Nickel 283 Carbonyl Nickel 287 Cerac N 2003 CNS 10 Micron Exmet 4 Ni X-4/0 Fibrex P Incofoam Nickel element NICKEL ROUND ANODES Nicrobraz LM:BNi 2 Ni-Flake 95 Novamet 123 Novamet 4SP Novamet 4SP10 Novamet 525 Novamet CNS 400 Novamet HCA 1 Novamet NI 255 Raney nickel Raney nickel 2800 UN 1325 UN 2881

DTXSID2020925

7440-66-6

HCHKCACWOHOZIP-UHFFFAOYSA-N

Zinc

Zn Asarco L 15 C.I. Pigment Black 16 Merrillite NC-Zinc Rheinzink Stapa TE Zinc AT UF (metal) UN 1436 Zinc dust Zinc Dust 3 Zinc Dust 500 mesh Zinc Dust LS 2 Zinc Dust MCS Zinc Flakes GTT ZINC METAL ZINC MOSSY ZINC STRIP ZINC, MOSSY Zincsalt GTT

DTXSID7035012

CL:0000073

CL barrier epithelial cell

GO:0019915

GO lipid storage

MP:0003674

MP oxidative stress

WIKI disrupted

WIKI increased

Sars-CoV-2 Virus from the coronaviridae family related to SARS-CoV, 229E, NL63, OC43, HKU1 and MERS.

Transmitted by aerosols

2021-02-23T04:50:40

2022-09-09T05:09:36

Acetaminophen

2016-11-29T18:42:26

Chloroform

2016-11-29T18:42:27

furan

2020-05-01T14:35:22

Platinum

2022-02-04T14:36:54

Aluminum

2022-02-04T14:42:11

Cadmium

2017-10-25T08:33:12

Mercury

2016-11-29T18:42:19

Uranium

2021-08-05T14:28:50

Arsenic

2021-04-27T00:15:21

Silver

2022-02-03T11:20:11

Manganese

2022-02-04T14:47:23

Nickel

2022-02-04T14:47:59

Zinc

2022-02-04T15:05:00

nanoparticles

2016-12-21T09:40:06

WCS_9606

common toxicological species human

WikiUser_28

Vertebrates

WikiUser_26

ApacheUser rodents

9606

NCBI Homo sapiens

Inhibition, Intestinal FXR

FXR inhibition

Molecular

AOPWiki 2026-04-22T21:50:00

2026-04-22T21:50:00

Ileal FGF15/FGF19 secretion, decreased

Decreased FGF15/FGF19

Cellular

AOPWiki 2026-04-22T21:57:53

2026-04-22T21:57:53

Intestinal barrier, disruption

Disruption of the intestinal barrier

Organ

A proper definition (and related ontology) of the intestinal barrier and permeability would benefit the understanding of this biological event central in many diseases. However, it is generally accepted that the intestinal barrier is a multilayer system encompassing : - a chemical barrier able to detoxify bacterial endotoxins, - a mucus layer providing a physical barrier against bacteria, - an one-cell-thick epithelial layer which physical barrier function is ensured by epithelial cell integrity and by tight junction proteins (occludins, claudins and zonulins), adherence junctions and desmosomes 2,4,5 - the cellular immune system present in the lamina propria underlying the epithelial cell layer - the antibacterial proteins secreted by the specialized intestinal epithelial cells or the Paneth cells. Together with the chemical barrier of the mucosal layer and the cellular immune system, the intestinal epithelial cell layer has actually two barrier functions:1–3 <ol style="list-style-type:lower-roman"> <li style="text-align:justify">It acts as a physical barrier against external factors (pathogens, toxins), </li> <li style="text-align:justify">It acts as a selective barrier by regulating the absorption of essential dietary nutrients and  ions, meaning their transport from the lumen into the blood.</li> </ol> Intestinal permeability6 describes the movement of molecules across the intestinal barrier from the lumen to the blood (Figure 1), and as such, is the measurable feature of the intestinal barrier. <img alt="" src="https://aopwiki.org/system/dragonfly/production/2022/01/05/9m0b6q2aex_Intestinal_permeability_wiki.png" style="height:508px; width:1103px" /> Figure 1. Created with Biorender.com Molecules can cross the epithelium via paracellular or transcellular route. Transcellular permeability encompass passive diffusion from the apical to the basal side (from the lumen to the blood), vesicle-mediated transcytosis and uptake mediated by a membrane receptor. Paracellular permeability is regulated by the tight junctions between adjacent cells and by the integrity of the epithelium. Alteration or disruption of one or more layers of the intestinal barrier leads to increased intestinal permeability, also called intestinal hyperpermeability or “leaky gut”, enhancing the transport of pathogens, toxins (such as lipopolysaccharides), undigested nutrients and the translocation of bacteria of the gut microbiota from the intestinal lumen into the systemic circulation3.

The definition of intestinal permeability being relatively broad includes altered paracellular route, regulated by TJ proteins, transcellular routes involving membrane transporters and channels, and endocytic mechanisms. Paracellular intestinal permeability can be assessed in vivo via different molecules and via putatiive blood biomarkers and ex vivo in Ussing chambers combining electrophysiology and probes of different molecular sizes. The latter is still the gold standard technique for assessing the epithelial barrier function, whereas in vivo techniques are also broadly used despite limitations (doi: <a href="https://doi.org/10.3389%2Ffnut.2021.717925" rel="noopener noreferrer" target="_blank">10.3389/fnut.2021.717925)</a>. In humans. Virtually all in vivo methods to assess paracellular intestinal permeability rely on the urinary excretion of orally ingested probes. Several markers, including different sizes of PEG, 51CrEDTA, and especially sugars have been used, each with advantages and disadvantages (doi: <a href="https://doi.org/10.3389%2Ffnut.2021.717925" rel="noopener noreferrer" target="_blank">10.3389/fnut.2021.717925)</a>. Intestinal Permeability Assessment (IPA) directly measures the ability of two non-metabolized sugar molecules (lactulose and mannitol) to permeate the small intestinal barrier by paracellular passage (sign of perturbed TJ-lactulose) or by transcellular passage (giving information of the whole epithelial absorptive area-mannitol), respectively. The patient drinks a premeasured amount of those sugars and 6h after, the ratio of Lactulose/Mannitol levels is measured in the urine 11. Levels in plasma/serum or in feces of: <ul> <li style="text-align:justify">Markers of epithelial cell damage, such as intestinal fatty acid binding protein (FABP)</li> <li style="text-align:justify">Markers of tight junction alterations, such as zonulin levels (doi: <a class="id-link" href="https://doi.org/10.1080/21688370.2016.1251384" rel="noopener" target="_blank">10.1080/21688370.2016.1251384</a>) </li> <li style="text-align:justify">Microbial translocation, such as peptidoglycans and lipopolysaccharides (LPS) and gut microbiota alteration.</li> </ul> In vitro systems12 Transepithelial electrical resistance (TEER) or the Lucifer Yellow (LY) leakage assay are techniques to measure barrier integrity and permeability of a cell layer13. Caco-2 cells are human epithelial colorectal adenocarcinoma cells with a structure and function similar to the differentiated small intestinal epithelial cells (e.g. exhibit microvilli). Caco-2 cells can be plated in wells as monolayers14,11. Other cell lines can be used, such as intestinal epithelial cells (IEC) or primary epithelial cells from human intestinal biopsies12. Co-culturing of enterocyte-like cells with immune cells in three-dimensional structure and within a microfluidic gut-on-chip has been shown to reflect better the physiology of the gut epithelium. Epi-IntestinalTM is an example of 3D human primary cell-based organotypic small intestinal model which allows evaluation of TEER and LY leakage assay (doi: <a href="https://doi.org/10.1007%2Fs11095-018-2362-0" rel="noopener noreferrer" target="_blank">10.1007/s11095-018-2362-0). </a> In vivo system In mice, one way to study intestinal paracellular permeability is by measuring the ability of fluorescein isothiocyanate (FITC)-dextran to cross from the lumen into the blood. After gavaging mice with FITC-dextran, the concentrations are measured in collected serum samples (doi: <a class="id-link" href="https://doi.org/10.3791/57032" rel="noopener" target="_blank">10.3791/57032</a>).

Human

UBERON:0000160

UBERON intestine

Not Specified Male Not Specified Female

Not Specified

All life stages

Not Specified

1.            Chelakkot, C., Ghim, J. & Ryu, S. H. Mechanisms regulating intestinal barrier integrity and its pathological implications. Exp. Mol. Med. 50, (2018). 2.            Groschwitz, K. R. & Hogan, S. P. Intestinal barrier function: Molecular regulation and disease pathogenesis. J. Allergy Clin. Immunol. 124, 3–20 (2009). 3.            Ghosh, S. S., Wang, J., Yannie, P. J. & Ghosh, S. Intestinal barrier dysfunction, LPS translocation, and disease development. J. Endocr. Soc. 4, 1–15 (2020). 4.            Sturgeon, C. & Fasano, A. Zonulin, a regulator of epithelial and endothelial barrier functions, and its involvement in chronic inflammatory diseases. Tissue Barriers 4, 1–19 (2016). 5.            Sturgeon, C., Lan, J. & Fasano, A. Zonulin transgenic mice show altered gut permeability and increased morbidity/mortality in the DSS colitis model. Ann N Y Acad Sci 1397, 130–142 (2017). 6.            Bischoff, S. C. et al. Intestinal permeability - a new target for disease prevention and therapy. BMC Gastroenterol. 14, 1–25 (2014). 7.            Qiu, W. et al. PUMA-mediated intestinal epithelial apoptosis contributes to ulcerative colitis in humans and mice. J. Clin. Invest. 121, 1722–1732 (2011). 8.            Hering, N. A., Fromm, M. & Schulzke, J. D. Determinants of colonic barrier function in inflammatory bowel disease and potential therapeutics. J. Physiol. 590, 1035–1044 (2012). 9.            Giron, L. B. et al. Plasma Markers of Disrupted Gut Permeability in Severe COVID-19 Patients. medRxiv 2020.11.13.20231209 (2021). 10.          Prasad, R. et al. Plasma microbiome in COVID-19 subjects: an indicator of gut barrier defects and dysbiosis Ram. BioRxiv (2021). 11.          Aguirre Valadez, J. M. et al. Intestinal permeability in a patient with liver cirrhosis. Ther. Clin. Risk Manag. 12, 1729–1748 (2016). 12.          Fedi, A. et al. In vitro models replicating the human intestinal epithelium for absorption and metabolism studies: A systematic review. J. Control. Release 335, 247–268 (2021). 13.          Lea, T. Epithelial Cell Models; General Introduction. in The Impact of Food Bioactives on Health: in vitro and ex vivo models (eds. Verhoeckx, K. et al.) 95–102 (Springer International Publishing, 2015). doi:10.1007/978-3-319-16104-4_9 14.          Li, B. R. et al. In Vitro and In Vivo Approaches to Determine Intestinal Epithelial Cell Permeability. J. Vis. Exp. 1–6 (2018). doi:10.3791/57032 15.          Ayehunie, S. et al. Human Primary Cell-Based Organotypic Microtissues for Modeling Small Intestinal Drug Absorption Seyoum. Pharm. Res. 35, 72 (2019). AOPWiki 2021-09-01T08:35:10

2025-04-27T13:31:37

Hepatic SHP, decreased

Cellular

AOPWiki 2026-04-22T22:24:40

2026-04-22T22:24:40

Hepatic CYP7A1, increased

Cellular

AOPWiki 2026-04-22T22:26:54

2026-04-22T22:26:54

Disrupted Lipid Storage

Cellular

This Key Event describes the disruption of normal lipid storage in liver cells.  Disruption of lipid storage and transport can be identified by excess accumulation of fatty acids or other lipids in the liver or altered ratios of expected lipid species which can ultimately lead to liver steatosis (Ipsen et al. 2018).  An example of an event that can cause disrupted lipid storage is the binding of stressor ligands to the PPAR isoforms with either agonist or antagonist interactions which can lead to effects on lipid storage and transport (Dixon et al. 2021).  PPARγ over expression results in promotes storage of lipids in the liver and thus exacerbates hepatic steatosis (Yu et al. 2003; Patsouris et al. 2006).  Conversely, deletion of PPARα resulted in an increased liver lipid (Patsouris et al. 2006).  Wang et al. (2003) demonstrated that PPARβ/δ deficient mice had increased obesity which, while potentially not a function of improper lipid storage, underpins the importance of all PPAR isoforms in proper lipid homeostasis.  Evidence of disruption of lipogenesis at the transcriptional level has also been observed across multiple studies using PFAS as the stressor (Tse et al. 2016; Cui et al. 2017; Huck et al. 2018; Liu et al. 2019; Martinez 2019; Yi et al. 2019; Louisse et al. 2020; Wang et al. 2022a).

There are numerous methodologies available for measuring disrupted lipid storage in the liver cells.  Fatty acids and other lipid species can be measure directly or measured globally using lipidomic methodologies (Wang et al. 2022; Albers et al. 2024), and histopathology can confirm lipid deposits in liver sections (Huck et al. 2018; Wang et al. 2022).  Also, targeted or global gene expression analyses can reveal disruptions in key genes responsible for proper lipid storage and transport (Tse et al. 2016; Yi et al. 2019; Louisse et al. 2020).

The conservation of PPAR molecular structure and function among vertebrates (Gust et al 2020) indicates this key event is likely to be conserved among this broad phylogenetic group.  Furthermore, PPAR isoforms play a crucial role in lipid metabolism across representative vertebrate species.  However, given that species to species variation does exist in structure and specific function, it is important to exercise care when looking to extrapolate across species.

UBERON:0002107

UBERON liver

CL:0000255

CL eukaryotic cell

High Male Moderate Female

Moderate

Embryo

High

Juvenile

High

Adult, reproductively mature

High

Albers, J., Mylroie, J., Kimble, A., Steward, C., Chapman, K., Wilbanks, M., Perkins, E. and Garcia-Reyero, N., 2024. Per-and Polyfluoroalkyl Substances: Impacts on Morphology, Behavior and Lipid Levels in Zebrafish Embryos. Toxics, 12(3), p.192. Cui, Y., Lv, S., Liu, J., Nie, S., Chen, J., Dong, Q., Huang, C. and Yang, D., 2017. Chronic perfluorooctanesulfonic acid exposure disrupts lipid metabolism in zebrafish. Human & experimental toxicology, 36(3), pp.207-217. Dixon, E.D., Nardo, A.D., Claudel, T. and Trauner, M., 2021. The role of lipid sensing nuclear receptors (PPARs and LXR) and metabolic lipases in obesity, diabetes and NAFLD. Genes, 12(5), p.645. Huck, I., Beggs, K. and Apte, U., 2018. Paradoxical Protective Effect of Perfluorooctanesulfonic Acid Against High-Fat Diet–Induced Hepatic Steatosis in Mice. International journal of toxicology, 37(5), pp.383-392. Ipsen, D.H., Lykkesfeldt, J. and Tveden-Nyborg, P., 2018. Molecular mechanisms of hepatic lipid accumulation in non-alcoholic fatty liver disease. Cellular and molecular life sciences, 75, pp.3313-3327. Liu, S., Yang, R., Yin, N., Wang, Y.L. and Faiola, F., 2019. Environmental and human relevant PFOS and PFOA doses alter human mesenchymal stem cell self-renewal, adipogenesis and osteogenesis. Ecotoxicology and environmental safety, 169, pp.564-572. <a name="_Hlk167282313">Louisse, J., Rijkers, D., Stoopen, G., Janssen, A., Staats, M., Hoogenboom, R., Kersten, S. and Peijnenburg, A., 2020. Perfluorooctanoic acid (PFOA), perfluorooctane sulfonic acid (PFOS), and perfluorononanoic acid (PFNA) increase triglyceride levels and decrease cholesterogenic gene expression in human HepaRG liver cells. Archives of toxicology, 94(9), pp.3137-3155.</a> Martínez, R., Navarro-Martín, L., Luccarelli, C., Codina, A.E., Raldúa, D., Barata, C., Tauler, R. and Piña, B., 2019. Unravelling the mechanisms of PFOS toxicity by combining morphological and transcriptomic analyses in zebrafish embryos. Science of the Total Environment, 674, pp.462-471. Patsouris, D., Reddy, J.K., Müller, M. and Kersten, S., 2006. Peroxisome proliferator-activated receptor α mediates the effects of high-fat diet on hepatic gene expression. Endocrinology, 147(3), pp.1508-1516. Tse, W.K.F., Li, J.W., Tse, A.C.K., Chan, T.F., Ho, J.C.H., Wu, R.S.S., Wong, C.K.C. and Lai, K.P., 2016. Fatty liver disease induced by perfluorooctane sulfonate: Novel insight from transcriptome analysis. Chemosphere, 159, pp.166-177. Wang, Y.X., Lee, C.H., Tiep, S., Ruth, T.Y., Ham, J., Kang, H. and Evans, R.M., 2003. Peroxisome-proliferator-activated receptor δ activates fat metabolism to prevent obesity. Cell, 113(2), pp.159-170. Wang, Q., Huang, J., Liu, S., Wang, C., Jin, Y., Lai, H. and Tu, W., 2022. Aberrant hepatic lipid metabolism associated with gut microbiota dysbiosis triggers hepatotoxicity of novel PFOS alternatives in adult zebrafish. Environment International, 166, p.107351. Yi, S., Chen, P., Yang, L. and Zhu, L., 2019. Probing the hepatotoxicity mechanisms of novel chlorinated polyfluoroalkyl sulfonates to zebrafish larvae: Implication of structural specificity. Environment international, 133, p.105262. Yu, S., Matsusue, K., Kashireddy, P., Cao, W.Q., Yeldandi, V., Yeldandi, A.V., Rao, M.S., Gonzalez, F.J. and Reddy, J.K., 2003. Adipocyte-specific gene expression and adipogenic steatosis in the mouse liver due to peroxisome proliferator-activated receptor γ1 (PPARγ1) overexpression. Journal of Biological Chemistry, 278(1), pp.498-505. AOPWiki 2024-05-08T10:54:12

2024-05-23T13:39:06

Increase, Oxidative Stress

Molecular

Oxidative stress is defined as an imbalance in the production of reactive oxygen species (ROS) and antioxidant defenses. High levels of oxidizing free radicals can be very damaging to cells and molecules within the cell.  As a result, the cell has important defense mechanisms to protect itself from ROS. For example, Nrf2 is a transcription factor and master regulator of the oxidative stress response. During periods of oxidative stress, Nrf2-dependent changes in gene expression are important in regaining cellular homeostasis (Nguyen, et al., 2009) and can be used as indicators of the presence of oxidative stress in the cell.  In addition to the directly damaging actions of ROS, cellular oxidative stress also changes cellular activities on a molecular level. Redox sensitive proteins have altered physiology in the presence and absence of ROS, which is caused by the oxidation of sulfhydryls to disulfides on neighboring amino acids (Antelmann & Helmann 2011). Importantly Keap1, the negative regulator of Nrf2, is regulated in this manner (Itoh, et al. 2010).  ROS also undermine the mitochondrial defense system from oxidative damage. The antioxidant systems consist of superoxide dismutase, catalase, glutathione peroxidase and glutathione reductase, as well as antioxidants such as α-tocopherol and ubiquinol, or antioxidant vitamins and minerals including vitamin E, C, carotene, lutein, zeaxanthin, selenium, and zinc (Fletcher, 2010). The enzymes, vitamins and minerals catalyze the conversion of ROS to non-toxic molecules such as water and O2. However, these antioxidant systems are not perfect and endogenous metabolic processes and/or exogenous oxidative influences can trigger cumulative oxidative injuries to the mitochondria, causing a decline in their functionality and efficiency, which further promotes cellular oxidative stress (Balasubramanian, 2000; Ganea & Harding, 2006; Guo et al., 2013; Karimi et al., 2017).   However, an emerging viewpoint suggests that ROS-induced modifications may not be as detrimental as previously thought, but rather contribute to signaling processes (Foyer et al., 2017).    Sources of ROS Production  Direct Sources: Direct sources involve the deposition of energy onto water molecules, breaking them into active radical species. When ionizing radiation hits water, it breaks it into hydrogen (H*) and hydroxyl (OH*) radicals by destroying its bonds. The hydrogen will create hydroxyperoxyl free radicals (HO2*) if oxygen is available, which can then react with another of itself to form hydrogen peroxide (H2O2) and more O2 (Elgazzar and Kazem, 2015). Antioxidant mechanisms are also affected by radiation, with catalase (CAT) and peroxidase (POD) levels rising as a result of exposure (Seen et al. 2018; Ahmad et al. 2021).   Indirect Sources: An indirect source of ROS is the mitochondria, which is one of the primary producers in eukaryotic cells (Powers et al., 2008).  As much as 2% of the electrons that should be going through the electron transport chain in the mitochondria escape, allowing them an opportunity to interact with surrounding structures. Electron-oxygen reactions result in free radical production, including the formation of hydrogen peroxide (H2O2) (Zhao et al., 2019). The electron transport chain, which also creates ROS, is activated by free adenosine diphosphate (ADP), O2, and inorganic phosphate (Pi) (Hargreaves et al. 2020; Raimondi et al. 2020; Vargas-Mendoza et al. 2021). The first and third complexes of the transport chain are the most relevant to mammalian ROS production (Raimondi et al., 2020). The mitochondria has its own set of DNA and it is a prime target of oxidative damage (Guo et al., 2013). ROS is also produced through nicotinamide adenine dinucleotide phosphate oxidase (Nox) stimulation, an event commenced by angiotensin II, a product/effector of the renin-angiotensin system (Nguyen Dinh Cat et al. 2013; Forrester et al. 2018). Other ROS producers include xanthine oxidase, immune cells (macrophage, neutrophils, monocytes, and eosinophils), phospholipase A2 (PLA2), monoamine oxidase (MAO), and carbon-based nanomaterials (Powers et al. 2008; Jacobsen et al. 2008; Vargas-Mendoza et al. 2021).

Oxidative Stress: Direct measurement of ROS is difficult because ROS are unstable. The presence of ROS can be assayed indirectly by measurement of cellular antioxidants, or by ROS-dependent cellular damage. Listed below are common methods for detecting the KE, however there may be other comparable methods that are not listed  <ul> <li>Detection of ROS by chemiluminescence (https://www.sciencedirect.com/science/article/abs/pii/S0165993606001683) </li> <li>Detection of ROS by chemiluminescence is also described in OECD TG 495 to assess phototoxic potential. </li> <li>Glutathione (GSH) depletion. GSH can be measured by assaying the ratio of reduced to oxidized glutathione (GSH:GSSG) using a commercially available kit (e.g., http://www.abcam.com/gshgssg-ratio-detection-assay-kit-fluorometric-green- ab138881.html). </li> <li>TBARS. Oxidative damage to lipids can be measured by assaying for lipid peroxidation using TBARS (thiobarbituric acid reactive substances) using a commercially available kit. </li> <li>8-oxo-dG. Oxidative damage to nucleic acids can be assayed by measuring 8-oxo-dG adducts (for which there are a number of ELISA based commercially available kits),or HPLC, described in Chepelev et al. (Chepelev, et al. 2015). </li> </ul>    Molecular Biology: Nrf2. Nrf2’s transcriptional activity is controlled post-translationally by oxidation of Keap1. Assay for Nrf2 activity include:  <ul> <li>Immunohistochemistry for increases in Nrf2 protein levels and translocation into the nucleus Western blot for increased Nrf2 protein levels </li> <li>Western blot of cytoplasmic and nuclear fractions to observe translocation of Nrf2 protein from the cytoplasm to the nucleus qPCR of Nrf2 target genes (e.g., Nqo1, Hmox-1, Gcl, Gst, Prx, TrxR, Srxn), or by commercially available pathway-based qPCR array (e.g., oxidative stress array from SABiosciences) </li> <li>Whole transcriptome profiling by microarray or RNA-seq followed by pathway analysis (in IPA, DAVID, metacore, etc.) for enrichment of the Nrf2 oxidative stress response pathway (e.g., Jackson et al. 2014) </li> <li>OECD TG422D describes an ARE-Nrf2 Luciferase test method </li> </ul> In general, there are a variety of commercially available colorimetric or fluorescent kits for detecting Nrf2 activation. <table border="1"> <tbody> <tr> <td> Assay Type & Measured Content  </td> <td> Description  </td> <td> Dose Range Studied  </td> <td> Assay Characteristics (Length/Ease of use/Accuracy)  </td> </tr> <tr> <td> ROS  Formation in the Mitochondria assay (Shaki et al., 2012)  </td> <td> “The mitochondrial ROS measurement was performed flow cytometry using DCFH-DA. Briefly, isolated kidney mitochondria were incubated with UA (0, 50, 100 and 200 µM) in respiration buffer containing (0.32 mM sucrose, 10mM Tris, 20 mM Mops, 50 µM EGTA, 0.5 mM MgCl2, 0.1 mM KH2PO4 and 5 mM sodium succinate) [32]. In the interval times of 5, 30 and 60 min following the UA addition, a sample was taken and DCFH-DA was added (final concentration, 10 µM) to mitochondria and was then incubated for 10 min.Uranyl acetate-induced ROS generation in isolated kidney mitochondria were determined through the flow cytometry (Partec, Deutschland) equipped with a 488-nm argon ion laser and supplied with the Flomax software and the signals were obtained using a 530-nm bandpass filter (FL-1 channel). Each determination is based on the mean fluorescence intensity of 15,000 counts.”    </td> <td> 0, 50,100 and 200 µM of Uranyl Acetate    </td> <td>  Long/ Easy High accuracy    </td> </tr> <tr> <td> Mitochondrial Antioxidant Content Assay Measuring GSH content (Shaki et al., 2012)    </td> <td> “GSH content was determined using DTNB as the indicator and spectrophotometer method for the isolated mitochondria. The mitochondrial fractions (0.5 mg protein/ml) were incubated with various concentrations of uranyl acetate for 1 h at 30 °C and then 0.1 ml of mitochondrial fractions was added into 0.1 mol/l of phosphate buffers and 0.04% DTNB in a total volume of 3.0 ml (pH 7.4). The developed yellow color was read at 412 nm on a spectrophotometer (UV-1601 PC, Shimadzu, Japan). GSH content was expressed as µg/mg protein.”  </td> <td> 0, 50,  100, or  200 µM  Uranyl Acetate  </td> <td>   </td> </tr> <tr> <td> H2O2 Production Assay Measuring H2O2 Production in isolated mitochondria (Heyno et al., 2008)    </td> <td> “Effect of CdCl2 and antimycin A (AA) on H2O2 production in isolated mitochondria from potato. H2O2 production was measured as scopoletin oxidation. Mitochondria were incubated for 30 min in the measuring buffer  (see the Materials and Methods) containing 0.5 mM succinate as an electron donor and 0.2 µM mesoxalonitrile 3‐chlorophenylhydrazone (CCCP) as an uncoupler, 10 U horseradish peroxidase and 5 µM scopoletin.”   </td> <td> 0, 10, 30  µM Cd2+     2 µM antimycin A  </td> <td>   </td> </tr> <tr> <td> Flow Cytometry ROS & Cell Viability (Kruiderig et al., 1997)    </td> <td> “For determination of ROS, samples taken at the indicated time points were directly transferred to FACScan tubes. Dih123 (10 mM, final concentration) was added and cells were incubated at 37°C in a humidified atmosphere (95% air/5% CO2) for 10 min. At t 5 9, propidium iodide (10 mM, final concentration) was added, and cells were analyzed by flow cytometry at 60 ml/min. Nonfluorescent Dih123 is cleaved by ROS to fluorescent R123 and detected by the FL1 detector as described above for Dc (Van de Water 1995)”“For determination of ROS, samples taken at the indicated time points were directly transferred to FACScan tubes. Dih123 (10 mM, final concentration) was added and cells were incubated at 37°C in a humidified atmosphere (95% air/5% CO2) for 10 min. At t 5 9, propidium iodide (10 mM, final concentration) was added, and cells were analyzed by flow cytometry at 60 ml/min. Nonfluorescent Dih123 is cleaved by ROS to fluorescent R123 and detected by the FL1 detector as described above for Dc (Van de Water 1995)”  </td> <td>   </td> <td>           Strong/easy medium  </td> </tr> <tr> <td> DCFH-DA  Assay Detection of hydrogen peroxide production (Yuan et al.,  2016)  </td> <td> Intracellular ROS production was measured using DCFH-DA as a probe. Hydrogen peroxide oxidizes DCFH to DCF. The probe is hydrolyzed intracellularly to DCFH carboxylate anion. No direct reaction with H2O2 to form fluorescent production.    </td> <td> 0-400  µM  </td> <td> Long/ Easy High accuracy  </td> </tr> <tr> <td> H2-DCF-DAAssay Detection of superoxide production (Thiebault etal., 2007)    </td> <td> This dye is a stable nonpolar compound which diffuses readily into the cells and yields H2-DCF. Intracellular OH or ONOO- react with H2-DCF when cells contain peroxides, to form the highly fluorescent compound DCF, which effluxes the cell. Fluorescence intensity of DCF is measured using a fluorescence spectrophotometer.  </td> <td> 0–600  µM  </td> <td> Long/ Easy High accuracy  </td> </tr> <tr> <td> CM-H2DCFDA  Assay (Eruslanov  & Kusmartsev, 2009)  </td> <td> The dye (CM-H2DCFDA) diffuses into the cell and is cleaved by esterases, the thiol reactive chlormethyl group reacts with intracellular glutathione which can be detected using flow cytometry.  </td> <td>   </td> <td> Long/Easy/ High Accuracy  </td> </tr> </tbody> </table>   <table border="1"> <tbody> <tr> <td> Method of Measurement   </td> <td> References   </td> <td> Description   </td> <td colspan="2"> OECD-Approved Assay  </td> </tr> <tr> <td> Chemiluminescence   </td> <td> (Lu, C. et al., 2006;   Griendling, K. K., et al., 2016)  </td> <td> ROS can induce electron transitions in molecules, leading to electronically excited products. When the electrons transition back to ground state, chemiluminescence is emitted and can be measured. Reagents such as luminol and lucigenin are commonly used to amplify the signal.   </td> <td colspan="2"> No    </td> </tr> <tr> <td> Spectrophotometry   </td> <td> (Griendling, K. K., et al., 2016)  </td> <td> NO has a short half-life. However, if it has been reduced to nitrite (NO2-), stable azocompounds can be formed via the Griess Reaction, and further measured by spectrophotometry.   </td> <td colspan="2"> No  </td> </tr> <tr> <td> Direct or Spin Trapping-Based electron paramagnetic resonance (EPR) Spectroscopy   </td> <td> (Griendling, K. K., et al., 2016)  </td> <td> The unpaired electrons (free radicals) found in ROS can be detected with EPR and is known as electron paramagnetic resonance. A variety of spin traps can be used.   </td> <td colspan="2"> No  </td> </tr> <tr> <td> Nitroblue Tetrazolium Assay   </td> <td> (Griendling, K. K., et al., 2016)  </td> <td> The Nitroblue Tetrazolium assay is used to measure O2.− levels. O2.− reduces nitroblue tetrazolium (a yellow dye) to formazan (a blue dye), and can be measured at 620 nm.   </td> <td colspan="2"> No  </td> </tr> <tr> <td> Fluorescence analysis of dihydroethidium (DHE) or Hydrocyans   </td> <td> (Griendling, K. K., et al., 2016)  </td> <td> Fluorescence analysis of DHE is used to measure O2.− levels.  O2.− is reduced to O2 as DHE is oxidized to 2-hydroxyethidium, and this reaction can be measured by fluorescence. Similarly, hydrocyans can be oxidized by any ROS, and measured via fluorescence.   </td> <td colspan="2"> No  </td> </tr> <tr> <td> Amplex Red Assay   </td> <td> (Griendling, K. K., et al., 2016)  </td> <td> Fluorescence analysis to measure extramitochondrial or extracellular H2O2 levels. In the presence of horseradish peroxidase and H2O2, Amplex Red is oxidized to resorufin, a fluorescent molecule measurable by plate reader.   </td> <td colspan="2"> No  </td> </tr> <tr> <td> Dichlorodihydrofluorescein Diacetate (DCFH-DA)   </td> <td> (Griendling, K. K., et al., 2016)  </td> <td> An indirect fluorescence analysis to measure intracellular H2O2 levels.  H2O2 interacts with peroxidase or heme proteins, which further react with DCFH, oxidizing it to dichlorofluorescein (DCF), a fluorescent product.   </td> <td colspan="2"> No  </td> </tr> <tr> <td> HyPer Probe   </td> <td> (Griendling, K. K., et al., 2016)  </td> <td> Fluorescent measurement of intracellular H2O2 levels. HyPer is a genetically encoded fluorescent sensor that can be used for in vivo and in situ imaging.   </td> <td colspan="2"> No  </td> </tr> <tr> <td> Cytochrome c Reduction Assay   </td> <td> (Griendling, K. K., et al., 2016)  </td> <td> The cytochrome c reduction assay is used to measure O2.− levels. O O2.− is reduced to O2 as ferricytochrome c is oxidized to ferrocytochrome c, and this reaction can be measured by an absorbance increase at 550 nm.   </td> <td colspan="2"> No  </td> </tr> <tr> <td> Proton-electron double-resonance imaging (PEDRI)   </td> <td> (Griendling, K. K., et al., 2016)  </td> <td> The redox state of tissue is detected through nuclear magnetic resonance/magnetic resonance imaging, with the use of a nitroxide spin probe or biradical molecule.   </td> <td colspan="2"> No              </td> </tr> <tr> <td> Glutathione (GSH) depletion   </td> <td> (Biesemann, N. et al., 2018)   </td> <td> A downstream target of the Nrf2 pathway is involved in GSH synthesis. As an indication of oxidation status, GSH can be measured by assaying the ratio of reduced to oxidized glutathione (GSH:GSSG) using a commercially available kit (e.g., <a href="http://www.abcam.com/gshgssg-ratio-detection-assay-kit-fluorometric-green-ab138881.html" rel="noreferrer noopener" target="_blank">http://www.abcam.com/gshgssg-ratio-detection-assay-kit-fluorometric-green-ab138881.html</a>).    </td> <td colspan="2"> No  </td> </tr> <tr> <td> Thiobarbituric acid reactive substances (TBARS)   </td> <td> (Griendling, K. K., et al., 2016)  </td> <td> Oxidative damage to lipids can be measured by assaying for lipid peroxidation with TBARS using a commercially available kit.    </td> <td colspan="2"> No  </td> </tr> <tr> <td> Protein oxidation (carbonylation)  </td> <td> (Azimzadeh et al., 2017; Azimzadeh et al., 2015; Ping et al., 2020)  </td> <td> Can be determined with ELISA or a commercial assay kit. Protein oxidation can indicate the level of oxidative stress.  </td> <td colspan="2"> No  </td> </tr> <tr> <td> Seahorse XFp Analyzer  </td> <td> Leung et al. 2018  </td> <td> The Seahorse XFp Analyzer provides information on mitochondrial function, oxidative stress, and metabolic dysfunction of viable cells by measuring respiration (oxygen consumption rate; OCR) and extracellular pH (extracellular acidification rate; ECAR).  </td> <td> No  </td> </tr> </tbody> </table>   Molecular Biology: Nrf2. Nrf2’s transcriptional activity is controlled post-translationally by oxidation of Keap1. Assays for Nrf2 activity include:   <table border="1"> <tbody> <tr> <td> Method of Measurement   </td> <td> References   </td> <td> Description   </td> <td> OECD-Approved Assay  </td> </tr> <tr> <td> Immunohistochemistry   </td> <td> (Amsen, D., de Visser, K. E., and Town, T., 2009)  </td> <td> Immunohistochemistry for increases in Nrf2 protein levels and translocation into the nucleus    </td> <td> No  </td> </tr> <tr> <td> qPCR   </td> <td> (Forlenza et al., 2012)  </td> <td> qPCR of Nrf2 target genes (e.g., Nqo1, Hmox-1, Gcl, Gst, Prx, TrxR, Srxn), or by commercially available pathway-based qPCR array (e.g., oxidative stress array from SABiosciences)   </td> <td> No  </td> </tr> <tr> <td> Whole transcriptome profiling via microarray or via RNA-seq followed by a pathway analysis  </td> <td> (Jackson, A. F. et al., 2014)  </td> <td> Whole transcriptome profiling by microarray or RNA-seq followed by pathway analysis (in IPA, DAVID, metacore, etc.) for enrichment of the Nrf2 oxidative stress response pathway  </td> <td> No  </td> </tr> </tbody> </table>

Taxonomic applicability: Occurrence of oxidative stress is not species specific.   Life stage applicability: Occurrence of oxidative stress is not life stage specific.  Sex applicability: Occurrence of oxidative stress is not sex specific.  Evidence for perturbation by prototypic stressor: There is evidence of the increase of oxidative stress following perturbation from a variety of stressors including exposure to ionizing radiation and altered gravity (Bai et al., 2020; Ungvari et al., 2013; Zhang et al., 2009).

High Mixed

High

All life stages

High High

Ahmad, S. et al. (2021), “60Co-γ Radiation Alters Developmental Stages of Zeugodacus cucurbitae (Diptera: Tephritidae) Through Apoptosis Pathways Gene Expression”, Journal Insect Science, Vol. 21/5, Oxford University Press, Oxford, <a href="https://doi.org/10.1093/jisesa/ieab080" rel="noreferrer noopener" target="_blank">https://doi.org/10.1093/jisesa/ieab080</a>  Antelmann, H. and J. D. Helmann (2011), “Thiol-based redox switches and gene regulation.”, Antioxidants & Redox Signaling, Vol. 14/6, Mary Ann Leibert Inc., Larchmont, <a href="https://doi.org/10.1089/ars.2010.3400" rel="noreferrer noopener" target="_blank">https://doi.org/10.1089/ars.2010.3400</a>  Amsen, D., de Visser, K. E., and Town, T. (2009), “Approaches to determine expression of inflammatory cytokines”, in Inflammation and Cancer, Humana Press, Totowa, <a href="https://doi.org/10.1007/978-1-59745-447-6_5" rel="noreferrer noopener" target="_blank">https://doi.org/10.1007/978-1-59745-447-6_5</a>   Azimzadeh, O. et al. 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Kazem. (2015), “Chapter 23: Biological effects of ionizing radiation” in The Pathophysiologic Basis of Nuclear Medicine, Springer, New York, pp. 540-548  Eruslanov, E., & Kusmartsev, S. (2010). Identification of ROS using oxidized DCFDA and flow-cytometry. Methods in molecular biology ,N.J.,  Vol. 594,  https://doi.org/10.1007/978-1-60761-411-1_4  Fletcher, A. E (2010), “Free radicals, antioxidants and eye diseases: evidence from epidemiological studies on cataract and age-related macular degeneration”, Ophthalmic Research, Vol. 44, Karger International, Basel, <a href="https://doi.org/10.1159/000316476.%22%20/t%20%22_blank" rel="noreferrer noopener" target="_blank">https://doi.org/10.1159/000316476.</a>   Forlenza, M. et al. (2012), “The use of real-time quantitative PCR for the analysis of cytokine mRNA levels” in Cytokine Protocols, Springer, New York, https://doi.org/10.1007/978-1-61779-439-1_2   Forrester, S.J. et al. (2018), “Angiotensin II Signal Transduction: An Update on Mechanisms of Physiology and Pathophysiology”, Physiological Reviews, Vol. 98/3, American Physiological Society, Rockville, <a href="https://doi.org/10.1152/physrev.00038.201" rel="noreferrer noopener" target="_blank">https://doi.org/10.1152/physrev.00038.201</a>  Foyer, C. H., A. V. Ruban, and G. Noctor (2017), “Viewing oxidative stress through the lens of oxidative signalling rather than damage”, Biochemical Journal, Vol. 474/6, Portland Press, England, https://doi.org/10.1042/BCJ20160814  Ganea, E. and J. J. Harding (2006), “Glutathione-related enzymes and the eye”, Current eye research, Vol. 31/1, Informa, London, <a href="https://doi.org/10.1080/02713680500477347.%22%20/t%20%22_blank" rel="noreferrer noopener" target="_blank">https://doi.org/10.1080/02713680500477347.</a>   Griendling, K. K. et al. (2016), “Measurement of reactive oxygen species, reactive nitrogen species, and redox-dependent signaling in the cardiovascular system: a scientific statement from the American Heart Association”, Circulation research, Vol. 119/5, Lippincott Williams & Wilkins, Philadelphia, <a href="https://doi.org/10.1161/RES.0000000000000110" rel="noreferrer noopener" target="_blank">https://doi.org/10.1161/RES.0000000000000110</a>   Guo, C. et al. (2013), “Oxidative stress, mitochondrial damage and neurodegenerative diseases”, Neural regeneration research, Vol. 8/21, Publishing House of Neural Regeneration Research, China, <a href="https://doi.org/10.3969/j.issn.1673-5374.2013.21.009" rel="noreferrer noopener" target="_blank">https://doi.org/10.3969/j.issn.1673-5374.2013.21.009</a>  Hargreaves, M., and L. L. Spriet (2020), “Skeletal muscle energy metabolism during exercise.”, Nature Metabolism, Vol. 2, Nature Portfolio, London, <a href="https://doi.org/10.1038/s42255-020-0251-4" rel="noreferrer noopener" target="_blank">https://doi.org/10.1038/s42255-020-0251-4</a>  Hladik, D. and S. Tapio (2016), “Effects of ionizing radiation on the mammalian brain”, Mutation Research/Reviews in Mutation Research, Vol. 770, Elsevier, Amsterdam, <a href="https://doi.org/10.1016/j.mrrev.2016.08.003" rel="noreferrer noopener" target="_blank">https://doi.org/10.1016/j.mrrev.2016.08.003</a>  Itoh, K., J. Mimura and M. Yamamoto (2010), “Discovery of the negative regulator of Nrf2, Keap1: a historical overview”, Antioxidants & Redox Signaling, Vol. 13/11, Mary Ann Leibert Inc., Larchmont, <a href="https://doi.org/10.1089/ars.2010.3222" rel="noreferrer noopener" target="_blank">https://doi.org/10.1089/ars.2010.3222</a>   Jackson, A.F. et al. (2014), “Case study on the utility of hepatic global gene expression profiling in the risk assessment of the carcinogen furan.”, Toxicology and Applied Pharmacology, Vol. 274/11, Elsevier, Amsterdam, <a href="https://doi.org/10.1016/j.taap.2013.10.019" rel="noreferrer noopener" target="_blank">https://doi.org/10.1016/j.taap.2013.10.019</a>  Jacobsen, N.R. et al. (2008), “Genotoxicity, cytotoxicity, and reactive oxygen species induced by single-walled carbon nanotubes and C60 fullerenes in the FE1-MutaTM Mouse lung epithelial cells”, Environmental and Molecular Mutagenesis, Vol. 49/6, John Wiley & Sons, Inc., Hoboken, <a href="https://doi.org/10.1002/em.20406" rel="noreferrer noopener" target="_blank">https://doi.org/10.1002/em.20406</a>  Karimi, N. et al. (2017), “Radioprotective effect of hesperidin on reducing oxidative stress in the lens tissue of rats”, International Journal of Pharmaceutical Investigation, Vol. 7/3, Phcog Net, Bengaluru, <a href="https://doi.org/10.4103/jphi.JPHI_60_17.%E2%80%AF" rel="noreferrer noopener" target="_blank">https://doi.org/10.4103/jphi.JPHI_60_17. </a>  Leung, D.T.H., and Chu, S. (2018), “Measurement of Oxidative Stress: Mitochondrial Function Using the Seahorse System” In: Murthi, P., Vaillancourt, C. (eds) Preeclampsia. Methods in Molecular Biology, vol 1710. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7498-6_22  Lu, C., G. Song, and J. Lin (2006), “Reactive oxygen species and their chemiluminescence-detection methods”, TrAC Trends in Analytical Chemistry, Vol. 25/10, Elsevier, Amsterdam, <a href="https://doi.org/10.1016/j.trac.2006.07.007" rel="noreferrer noopener" target="_blank">https://doi.org/10.1016/j.trac.2006.07.007</a>  Nguyen Dinh Cat, A. et al. (2013), “Angiotensin II, NADPH oxidase, and redox signaling in the vasculature”, Antioxidants & redox signaling, Vol. 19/10, Mary Ann Liebert, Larchmont, <a href="https://doi.org/10.1089/ars.2012.4641" rel="noreferrer noopener" target="_blank">https://doi.org/10.1089/ars.2012.4641</a>  Ping, Z. et al. (2020), “Oxidative Stress in Radiation-Induced Cardiotoxicity”, Oxidative Medicine and Cellular Longevity, Vol. 2020, Hindawi, <a href="https://doi.org/10.1155/2020/3579143" rel="noreferrer noopener" target="_blank">https://doi.org/10.1155/2020/3579143</a>  Powers, S.K. and M.J. Jackson. (2008), “Exercise-Induced Oxidative Stress: Cellular Mechanisms and Impact on Muscle Force Production”, Physiological Reviews, Vol. 88/4, American Physiological Society, Rockville, <a href="https://doi.org/10.1152/physrev.00031.2007" rel="noreferrer noopener" target="_blank">https://doi.org/10.1152/physrev.00031.2007</a>  Raimondi, V., F. Ciccarese and V. Ciminale. (2020), “Oncogenic pathways and the electron transport chain: a dangeROS liason”, British Journal of Cancer, Vol. 122/2, Nature Portfolio, London, <a href="https://doi.org/10.1038/s41416-019-0651-y" rel="noreferrer noopener" target="_blank">https://doi.org/10.1038/s41416-019-0651-y</a>  Seen, S. and L. Tong. (2018), “Dry eye disease and oxidative stress”, Acta Ophthalmologica, Vol. 96/4, John Wiley & Sons, Inc., Hoboken, <a href="https://doi.org/10.1111/aos.13526" rel="noreferrer noopener" target="_blank">https://doi.org/10.1111/aos.13526</a>  Ungvari, Z. et al. (2013), “Ionizing Radiation Promotes the Acquisition of a Senescence-Associated Secretory Phenotype and Impairs Angiogenic Capacity in Cerebromicrovascular Endothelial Cells: Role of Increased DNA Damage and Decreased DNA Repair Capacity in Microvascular Radiosensitivity”, The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, Vol. 68/12, Oxford University Press, Oxford, <a href="https://doi.org/10.1093/gerona/glt057." rel="noreferrer noopener" target="_blank">https://doi.org/10.1093/gerona/glt057.</a>     Vargas-Mendoza, N. et al. (2021), “Oxidative Stress, Mitochondrial Function and Adaptation to Exercise: New Perspectives in Nutrition”, Life, Vol. 11/11, Multidisciplinary Digital Publishing Institute, Basel, <a href="https://doi.org/10.3390/life11111269" rel="noreferrer noopener" target="_blank">https://doi.org/10.3390/life11111269</a>  Wang, H. et al. (2019), “Radiation-induced heart disease: a review of classification, mechanism and prevention”, International Journal of Biological Sciences, Vol. 15/10, Ivyspring International Publisher, Sydney, <a href="https://doi.org/10.7150/ijbs.35460" rel="noreferrer noopener" target="_blank">https://doi.org/10.7150/ijbs.35460</a>   Zhang, R. et al. (2009), “Blockade of AT1 receptor partially restores vasoreactivity, NOS expression, and superoxide levels in cerebral and carotid arteries of hindlimb unweighting rats”, Journal of applied physiology, Vol. 106/1, American Physiological Society, Rockville, <a href="https://doi.org/10.1152/japplphysiol.01278.2007" rel="noreferrer noopener" target="_blank">https://doi.org/10.1152/japplphysiol.01278.2007</a>.  Zhao, R. Z. et al. (2019), “Mitochondrial electron transport chain, ROS generation and uncoupling”, International journal of molecular medicine, Vol. 44/1, Spandidos Publishing Ltd., Athens, <a href="https://doi.org/10.3892/ijmm.2019.4188" rel="noreferrer noopener" target="_blank">https://doi.org/10.3892/ijmm.2019.4188</a>  AOPWiki 2017-05-30T13:58:17

2026-02-11T07:05:27

Increase, Steatohepatitis

Organ

Steatohepatitis is characterized by hepatic steatosis accompanied by hepatocellular injury and lobular inflammation. It represents a pathological progression beyond simple steatosis and is a defining feature of metabolic dysfunction–associated steatohepatitis (MASH). Histologically, steatohepatitis includes: <ul> <li> Macrovesicular steatosis </li> <li> Hepatocyte ballooning degeneration </li> <li> Lobular inflammatory cell infiltration </li> <li> Mallory–Denk bodies (in some cases) </li> <li> Variable degrees of perisinusoidal fibrosis </li> </ul>

<h3>1. Histopathology (Primary Method)</h3> <ul> <li> Hematoxylin and eosin (H&E) staining </li> <li> NAFLD Activity Score (NAS) </li> <li> Steatosis–Activity–Fibrosis (SAF) scoring system </li> <li> Assessment of: <ul> <li> Steatosis grade </li> <li> Ballooning degeneration </li> <li> Lobular inflammation </li> </ul> </li> </ul> Histological scoring systems are considered the gold standard for detection. <h3>2. Serum Biomarkers</h3> <ul> <li> Elevated ALT (alanine aminotransferase) </li> <li> Elevated AST (aspartate aminotransferase) </li> <li> Inflammatory cytokines (TNF-α, IL-6) </li> </ul> Biochemical markers provide supportive but not definitive evidence. <h3>3. Molecular Markers</h3> <ul> <li> Increased expression of inflammatory genes (e.g., TNF-α, MCP-1) </li> <li> Markers of hepatocyte injury (e.g., cytokeratin-18 fragments) </li> </ul> <h3>4. Imaging (Clinical Context)</h3> <ul> <li> MRI-PDFF (steatosis quantification) </li> <li> Elastography (for associated fibrosis) </li> </ul> However, histology remains required for definitive diagnosis of steatohepatitis.

Steatohepatitis is a well-defined pathological entity in humans and is reproducibly induced in rodent models of metabolic dysfunction and lipotoxic stress. The KE is most applicable to: <ul> <li> Mammalian species with comparable hepatic architecture </li> <li> Conditions involving chronic metabolic stress </li> <li> Adult or metabolically mature organisms </li> </ul> The weight of evidence for this KE is strong due to consistent clinical and experimental characterization.

UBERON:0002107

UBERON liver

High Unspecific

High

All life stages

High AOPWiki 2017-11-13T12:47:00

2026-02-24T09:13:44

<upstream-id>64dbfb35-f342-4b45-983b-d48d133ad034</upstream-id> <downstream-id>0861009b-18c3-4832-bf9d-121808cfe4dc</downstream-id>

AOPWiki 2026-04-23T00:56:02

2026-04-23T00:56:02

Intestinal FXR inhibition leading to steatohepatitis via gut‑liver axis dysregulation

Intestinal FXR inhibition to steatohepatitis

Jung-Hwa Oh

Jung-Hwa Oh1,  Mi-Sun Choi1, Ga-Won Lee1, Soojin Kim1, Mi-Young Son2 1Korea Institute of Toxicology, 141 Gajeong-ro, Yuseong-gu, Daejeon, 34114, Republic of Korea 2 Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, 34141, Republic of Korea.

BY-SA

2.8

Steatohepatitis is the inflammatory form of steatotic liver disease and a major driver of progressive liver damage, fibrosis and hepatocellular carcinoma. The gut‑liver axis, and particularly bile acid–farnesoid X receptor (FXR) signalling, plays a central role in the development of steatohepatitis, but an AOP formalising the causal sequence from intestinal FXR inhibition to steatohepatitis has not been available. This AOP describes how inhibition of intestinal FXR, mainly as a consequence of bile acid pool dysregulation and gut dysbiosis, can lead to steatohepatitis through disruption of gut‑liver axis signalling. The molecular initiating event (MIE) is inhibition of FXR transcriptional activity in ileal enterocytes due to reduced availability of potent endogenous FXR agonists (for example chenodeoxycholic acid) and altered bile acid composition. This leads to decreased transcription and secretion of FGF15/FGF19 from the ileum (KE1), reduced expression of ileal bile acid transporters such as IBABP and OSTα/β (KE2), and disruption of enterohepatic bile acid circulation. Accumulation of cytotoxic bile acids and loss of FXR‑mediated epithelial defence contribute to intestinal barrier dysfunction (KE3), increasing translocation of microbial products into the portal circulation. On the hepatic side of the gut‑liver axis, reduced FGF15/FGF19 signalling and diminished hepatic FXR activity lower SHP expression and derepress CYP7A1 and CYP8B1 (KE4), thereby increasing bile acid synthesis, while down‑regulation of BSEP and MRP2 (KE5) impairs bile acid efflux and leads to intrahepatic bile acid retention. These bile acid‑driven perturbations promote hepatic lipid accumulation (steatosis) through activation of SREBP‑1c and reduced fatty acid β‑oxidation (KE6). Lipid overload and bile acid toxicity provoke oxidative and endoplasmic reticulum stress (KE7), which, together with increased influx of bacterial products and loss of FXR’s anti‑inflammatory activity, facilitate NF‑κB activation and hepatic inflammation (KE8). The pathway culminates in steatohepatitis as the adverse outcome, defined histologically by steatosis, lobular inflammation and hepatocyte ballooning, with or without fibrosis. In humans, this condition corresponds clinically to metabolic dysfunction‑associated steatohepatitis (MASH) and is usually associated with impaired liver function and increased risk of progression to cirrhosis and hepatocellular carcinoma. The overall weight of evidence for this AOP is moderate‑to‑strong, supported by intestinal and hepatic FXR knockout models, pharmacological modulation of FXR, multi‑omics analyses of FXR‑dependent gene networks and clinical data showing dysregulation of the FXR–FGF19 gut‑liver axis in steatotic liver disease. Steatohepatitis develops in the setting of steatotic liver disease when lipid overload is accompanied by hepatocellular injury and inflammation. Over the past decade, research has highlighted that this transition is strongly influenced by the gut–liver axis rather than by hepatic mechanisms alone. Intestinal FXR, highly expressed in the ileum, is a central regulator of bile acid composition, FGF15/FGF19 secretion and intestinal barrier function, all of which shape hepatic exposure to bile acids and microbial products. Dysregulation of this signalling axis has been repeatedly associated with steatosis, steatohepatitis and fibrosis in experimental models and in humans. This AOP focuses specifically on perturbations of intestinal FXR within the gut–liver axis as a biologically plausible and translationally relevant driver of steatohepatitis, with the aim of providing a structured mechanistic framework that can support assay development, IATA design and regulatory interpretation, without attempting to cover all possible causes or pathways leading to this liver outcome.

The development of this AOP followed a targeted, expert‑guided literature strategy rather than a formal systematic review. The starting point was domain knowledge that intestinal FXR–FGF15/FGF19 signalling, bile acid homeostasis, intestinal barrier integrity and hepatic lipid/inflammatory responses are central components of the gut–liver axis in steatotic liver disease. Based on this, we first outlined a tentative causal chain from intestinal FXR inhibition to steatohepatitis and used it to define candidate key events and key event relationships. Literature searches were then conducted primarily in PubMed and major publisher databases using combinations of terms such as “intestinal FXR”, “ileal FXR”, “FXR FGF19 gut‑liver axis”, “FXR bile acids steatohepatitis/MASH/MASLD”, “FGF19 CYP7A1”, “SHP CYP7A1”, “BSEP FXR”, “intestinal barrier FXR”, and “gut–liver axis liver inflammation”. Titles and abstracts were screened to identify studies that directly addressed intestinal FXR–FGF15/FGF19 signalling, gut–liver axis dysfunction, or hepatic consequences of FXR modulation. Full texts from relevant animal, in vitro and clinical studies were then examined to extract information on potential KEs (e.g. FGF19 decrease, bile acid transport changes, steatosis, inflammation) and on the strength and direction of KERs (e.g. FXR→FGF19→CYP7A1). As specific KEs and KERs were drafted, additional focused searches were used to fill gaps on measurement methods, temporal concordance and essentiality (for example “FGF19 ELISA bile acid synthesis”, “FXR knockout steatohepatitis”, “FXR agonist obeticholic acid FGF19 liver outcomes”). Throughout, events were defined at a level that allows reuse in other AOPs (e.g. generic “hepatic steatosis” and “hepatic inflammation”), while FXR‑ and gut–liver axis–specific details are captured in the KER descriptions. This pragmatic, keyword‑driven strategy is intended to provide a transparent evidence base that is sufficiently robust for regulatory discussion and for re‑use of individual KEs/KERs in related AOPs and IATA.

Steatohepatitis represents a clinically recognized and pathologically defined stage of metabolic dysfunction–associated steatotic liver disease (MASLD), characterized by hepatic steatosis accompanied by hepatocellular injury and inflammation. It is a critical transition point between reversible metabolic steatosis and progressive, potentially irreversible liver pathology, including fibrosis, cirrhosis, and hepatocellular carcinoma. As such, an increase in steatohepatitis severity constitutes a biologically meaningful and adverse health outcome. <h2>Human Health Relevance</h2> Steatohepatitis (formerly NASH; now MASH under MASLD nomenclature) is associated with: <ul> <li> Increased risk of liver fibrosis progression </li> <li> Elevated liver-related morbidity and mortality </li> <li> Increased risk of hepatocellular carcinoma </li> <li> Higher overall cardiometabolic mortality </li> </ul> Histologically confirmed steatohepatitis is a strong predictor of disease progression compared to simple steatosis. Therefore, regulatory concern is substantially higher once inflammatory and hepatocellular injury components are present. <h2>Scientific Basis for Domain of Applicability</h2> <h3>Taxonomic Applicability</h3> The adverse outcome is highly relevant to mammals, particularly humans, due to conserved hepatic architecture, lipid metabolism, inflammatory signaling, and fibrogenic pathways. Rodent models (e.g., high-fat diet, Western diet, glucocorticoid exposure models) reliably reproduce key histopathological features of steatohepatitis, including: <ul> <li> Steatosis with hepatocyte ballooning </li> <li> Lobular inflammation </li> <li> Early perisinusoidal fibrosis </li> </ul> This cross-species concordance supports high biological plausibility within Mammalia. <h3>Life Stage Applicability</h3> The adverse outcome is most relevant in adolescent and adult life stages, where metabolic systems are fully developed and chronic exposure conditions can lead to progressive disease. While pediatric MASLD exists, the majority of mechanistic and regulatory evidence derives from adult populations and adult rodent models. <h3>Sex Applicability</h3> Steatohepatitis occurs in both males and females. Sex differences in susceptibility and progression rate have been reported, likely reflecting hormonal influences on lipid metabolism and inflammation. However, the pathological entity and its progression mechanisms are conserved across sexes. <h2>Weight of Evidence for Adversity</h2> The weight of evidence supporting steatohepatitis as an adverse outcome is strong based on: <ol> <li> Clinical Evidence <ul> <li> Histologically confirmed steatohepatitis predicts fibrosis progression and mortality. </li> <li> Longitudinal human studies demonstrate increased liver-related outcomes compared to simple steatosis. </li> </ul> </li> <li> Pathophysiological Evidence <ul> <li> Hepatocyte ballooning reflects cellular injury and cytoskeletal disruption. </li> <li> Inflammatory infiltration drives sustained tissue damage and fibrogenesis. </li> <li> Cytokine and TGF-β signaling link inflammation directly to fibrosis progression. </li> </ul> </li> <li> Consistency Across Models <ul> <li> Reproducible induction in multiple rodent models. </li> <li> Mechanistic concordance between experimental systems and human disease. </li> </ul> </li> <li> Irreversibility Consideration <ul> <li> While early steatohepatitis may be partially reversible, sustained inflammation significantly increases the probability of irreversible fibrosis. </li> </ul> </li> </ol> <h2>Regulatory Relevance</h2> An increase in steatohepatitis severity represents: <ul> <li> A clear adverse effect at the organ level </li> <li> A progression beyond adaptive metabolic perturbation </li> <li> A disease-defining pathological state recognized in clinical practice </li> </ul> From a regulatory perspective, this adverse outcome is relevant for: <ul> <li> Hazard identification </li> <li> Chronic toxicity assessment </li> <li> Endocrine and metabolic disruptor evaluation </li> <li> Integration into adverse outcome pathways supporting chemical prioritization </li> </ul> Because steatohepatitis is a well-defined diagnostic and pathological entity with established clinical consequences, it provides a robust anchor for AOP-based risk assessment frameworks.

adjacent

Low

High

This AOP is considered most applicable to mammalian species with a conserved bile acid–FXR–FGF15/FGF19 axis, in particular humans and rodents. In humans, intestinal FXR–FGF19 signalling and gut–liver axis dysfunction have been linked to steatotic liver disease and steatohepatitis in multiple clinical and translational studies, supporting direct human relevance. Rodent models (especially mouse) provide strong mechanistic support through tissue‑specific Fxr knockout strains and diet‑induced steatohepatitis, which closely recapitulate key features of the pathway. Sex‑specific differences have not emerged as a dominant determinant of the described mechanism, and the AOP is therefore considered applicable to both males and females. With respect to life stage, the AOP is most clearly supported for late juvenile and adult life stages, in which hepatic metabolic capacity and bile acid circulation are fully developed; applicability to early developmental stages is currently less certain and would require additional evidence. The Weight of Evidence (WoE) for the overall AOP is judged as moderate‑to‑strong. Biological plausibility of the central causal chain—intestinal FXR inhibition → reduced ileal FGF15/FGF19 → altered hepatic bile acid synthesis and transport → hepatic steatosis, stress and inflammation → steatohepatitis—is high, as each of these links is grounded in well‑characterised physiology of bile acid–FXR signalling and the gut–liver axis. Intestinal FGF15/FGF19 and multiple bile acid transporters are direct transcriptional targets of FXR, and the negative feedback of FGF15/FGF19 on hepatic CYP7A1 is well established. FXR agonist and antagonist studies, along with intestinal and hepatic Fxr knockout models, provide strong experimental evidence for essentiality of key events related to FXR signalling, bile acid homeostasis, lipid accumulation and inflammation. Human data, while inherently more correlative, consistently show dysregulation of FXR–FGF19 signalling, bile acid profiles and gut–liver barrier function in patients with steatotic liver disease and steatohepatitis, lending translational support to the AOP. Some uncertainties remain, particularly regarding quantitative dose–response and temporal relationships between individual KEs in humans, the contribution of co‑occurring metabolic stressors (such as obesity, insulin resistance and dietary patterns), and the relative importance of intestinal versus hepatic FXR perturbation across different exposure scenarios. Nonetheless, the available evidence is sufficient to support regulatory applications that rely on qualitative or semi‑quantitative understanding of mechanism, such as: (1) priority setting for chemicals that perturb intestinal FXR or bile acid homeostasis; (2) design of testing strategies and integrated approaches to testing and assessment (IATA) focusing on FXR–FGF19 signalling, bile acid profiles, intestinal barrier function and hepatic steatosis/inflammation; and (3) mechanism‑based interpretation of nonclinical and clinical data for substances targeting FXR or the gut–liver axis. The modular definition of KEs (e.g., hepatic steatosis, hepatic inflammation) and their KERs also facilitates reuse within a broader AOP network for steatotic liver disease, enhancing the value of this AOP as a building block for future regulatory frameworks. This AOP is primarily applicable to mammalian species in which the bile acid–FXR–FGF15/FGF19 signalling axis and gut–liver anatomical/physiological organisation are conserved. <ul> <li> Taxa <ul> <li> Human (Homo sapiens): Intestinal FXR–FGF19 signalling, enterohepatic bile acid circulation, and gut–liver axis dysfunction have all been documented in human steatotic liver disease and steatohepatitis. Therefore, the AOP is directly relevant to human health risk assessment. </li> <li> Rodents (especially mouse, Mus musculus): Most mechanistic evidence (intestinal and hepatic Fxr knockout models, diet‑induced steatohepatitis, FXR agonist/antagonist studies) comes from mice, where FGF15 is the functional orthologue of human FGF19. The qualitative sequence of key events is considered conserved between mouse and human, although quantitative aspects may differ. </li> <li> Application to other mammals (e.g. rat) is plausible where a comparable FXR–FGF15/FGF19–bile acid axis exists, but specific evidence may be more limited. </li> </ul> </li> <li> Sex Available data do not indicate a fundamentally different FXR–FGF15/FGF19–gut‑liver mechanism between males and females. Both sexes develop steatosis and steatohepatitis in relevant models, and both exhibit FXR–FGF19 dysregulation in clinical and experimental settings. The AOP is therefore considered applicable to both males and females, while acknowledging that quantitative susceptibility (e.g. threshold, rate of progression) may differ between sexes in specific models. </li> <li> Life stage The AOP is best supported for late juvenile and adult stages, in which: <ul> <li> hepatic metabolic capacity is fully developed, </li> <li> enterohepatic circulation of bile acids is established, and </li> <li> diet‑ and obesity‑related metabolic stress can realistically contribute to steatosis and steatohepatitis. Evidence in early developmental stages (neonatal/infant) is more limited, and the role of intestinal FXR and bile acid signalling may differ due to developmental changes in bile acid metabolism and microbiota. Thus, applicability to very early life stages should be considered with caution and may require additional data. </li> </ul> </li> <li> Other biological context <ul> <li> The AOP assumes a functional gut–liver axis with intact portal circulation and enterohepatic bile acid cycling; conditions that fundamentally alter this (e.g. major surgical shunts, absence of bile flow) may fall outside the domain of straightforward applicability. </li> <li> The AOP is most relevant under metabolic stress conditions (over‑nutrition, obesity, insulin resistance) that favour hepatic fat accumulation, since these provide the context in which intestinal FXR perturbation and gut–liver axis dysregulation are most likely to drive progression to steatohepatitis. </li> </ul> </li> </ul>

Overall, the essentiality of the key events (KEs) in this AOP is supported by a combination of direct intervention studies (genetic and pharmacological manipulation of FXR and its core targets) and indirect correlation data (degree of KE modulation vs severity of downstream KEs and steatohepatitis). Essentiality is strongest for KEs directly controlled by FXR (FGF15/FGF19, hepatic SHP/CYP7A1, BSEP) and somewhat weaker, though still supported, for more distal tissue‑level events (intestinal barrier dysfunction, oxidative stress, inflammation). <h2>MIE – Intestinal FXR, inhibition</h2> Essentiality: High (direct evidence) <ul> <li> Intestinal FXR–deficient mice (e.g. FxrΔIE) show reduced ileal FGF15/FGF19 expression, increased hepatic bile acid synthesis, exacerbated steatosis and steatohepatitis compared with wild‑type animals under the same dietary challenge. </li> <li> Conversely, pharmacological activation of intestinal FXR with gut‑restricted agonists (e.g. fexaramine, or orally administered obeticholic acid with strong intestinal action) increases FGF15/FGF19, normalises bile acid synthesis and attenuates hepatic steatosis and inflammation. </li> <li> These gain‑ and loss‑of‑function data indicate that preventing intestinal FXR activation (the MIE) reliably worsens, and enhancing it improves, multiple downstream KEs and the AO. </li> </ul> <h2>KE1 – Ileal FGF15/FGF19 secretion, decreased</h2> Essentiality: High (direct evidence) <ul> <li> FGF15/FGF19 is a direct FXR target in the ileum, and its secretion is necessary to repress hepatic CYP7A1 and maintain bile acid homeostasis. Blocking FGF15/FGF19 (e.g. in FGF15‑deficient mice, or through reduced FXR activation) leads to increased CYP7A1 activity, elevated bile acid synthesis, and aggravated hepatic injury under metabolic or cholestatic stress. </li> <li> Restoration of FGF19 (by exogenous administration or FXR agonists) reduces bile acid synthesis, improves liver histology and lowers transaminases in animal models and in clinical studies, demonstrating that correcting KE1 can reverse or attenuate several downstream KEs (altered bile acid synthesis, steatosis, inflammation) and improve the AO. </li> <li> The tight causal linkage between FGF15/FGF19 levels and hepatic bile acid synthesis provides strong evidence for essentiality. </li> </ul> <h2>KE2 – Ileal bile acid transporters (IBABP, OSTα/β), decreased</h2> Essentiality: Moderate (mixed direct/indirect evidence) <ul> <li> IBABP and OSTα/β are FXR‑regulated transporters that buffer and export bile acids in ileal enterocytes. Genetic or pharmacological reduction of these transporters disrupts enterohepatic bile acid circulation and can lead to local bile acid accumulation and epithelial stress. </li> <li> Experimental data show that knockdown/knockout of OSTα/β or IBABP alters bile acid distribution and can contribute to intestinal injury and barrier defects, which in turn favour gut–liver axis inflammation. However, the extent to which modulation of these individual transporters alone is sufficient to drive the full sequence of downstream KEs up to steatohepatitis is less well quantified. </li> <li> Overall, there is reasonable evidence that attenuation or restoration of these transporters modulates downstream events, but essentiality is considered moderate rather than high. </li> </ul> <h2>KE3 – Intestinal barrier integrity, decreased</h2> Essentiality: Moderate (strong indirect evidence) <ul> <li> Multiple models show that increased intestinal permeability and loss of barrier integrity are associated with higher portal LPS levels, Kupffer cell activation and worsening hepatic inflammation and fibrosis. Interventions that preserve or restore barrier function (e.g. FXR agonists, probiotics, prebiotics, SCFAs) often attenuate hepatic inflammation and histological liver damage. </li> <li> However, steatohepatitis can also develop via mechanisms that do not primarily rely on barrier breakdown (e.g. pure metabolic/lipotoxic pathways), and barrier damage is not unique to FXR‑mediated toxicity. </li> <li> Therefore, barrier dysfunction is clearly an important amplifier and modulator of downstream inflammation and the AO, but it may not be strictly essential in all contexts; essentiality is judged as moderate. </li> </ul> <h2>KE4 – Hepatic SHP, decreased; CYP7A1/CYP8B1, derepressed</h2> Essentiality: High (direct evidence) <ul> <li> Hepatic FXR–SHP signalling is a central negative regulator of CYP7A1 and CYP8B1. In hepatic Fxr or Shp knockout mice, CYP7A1 is derepressed, bile acid synthesis is increased and liver injury is exacerbated under cholestatic or metabolic stress; restoring or enhancing this pathway reduces bile acid synthesis and hepatic damage. </li> <li> Pharmacological activation of FXR in the liver increases SHP, represses CYP7A1 and improves bile acid homeostasis and liver histology. Blocking this KE (e.g. by SHP loss or sustained CYP7A1 overexpression) prevents FXR‑FGF19‑mediated feedback from fully normalising bile acid synthesis and liver injury. </li> <li> These data show that this KE is essential for transmitting signals from intestinal FXR/FGF15/FGF19 to hepatic bile acid synthesis and downstream events. </li> </ul> <h2>KE5 – Hepatic BSEP (ABCB11) and MRP2 (ABCC2), decreased</h2> Essentiality: High (direct evidence for bile acid–mediated toxicity) <ul> <li> BSEP and MRP2 are key canalicular transporters for bile acid and organic anion excretion. Genetic deficiency or functional inhibition of BSEP in humans and animals causes intrahepatic cholestasis, bile acid retention, hepatocellular injury and progression to steatosis, inflammation and fibrosis. </li> <li> Experimental models show that FXR activation increases BSEP/MRP2 expression and improves bile acid excretion and liver histology, whereas FXR suppression or transporter inhibition worsens intrahepatic bile acid accumulation and liver injury. </li> <li> Since bile acid retention is a major driver of hepatocellular stress and inflammation, maintenance of this KE is critical, and its disruption is strongly linked to downstream KEs and the AO. </li> </ul> <h2>KE6 – Hepatic lipid accumulation (steatosis), increased</h2> Essentiality: High for steatohepatitis as defined <ul> <li> Steatohepatitis, by definition, requires the presence of hepatic steatosis along with inflammation and cell injury. Genetic or dietary interventions that reduce steatosis (e.g. enhancing β‑oxidation, inhibiting de novo lipogenesis, or correcting insulin resistance) generally decrease the severity of inflammation and histological steatohepatitis, even when other insults are present. </li> <li> Conversely, models with severe steatosis promote oxidative stress, inflammatory signalling and progression to steatohepatitis, particularly in the presence of additional hits such as bile acid toxicity or endotoxemia. </li> <li> While limited inflammatory changes can occasionally occur without marked steatosis, the overall body of evidence supports hepatic steatosis as an essential prerequisite for the AO in the context of this AOP. </li> </ul> <h2>KE7 – Hepatic oxidative and endoplasmic reticulum stress, increased</h2> Essentiality: Moderate (good indirect evidence) <ul> <li> Numerous studies show that reducing oxidative/ER stress (e.g. via antioxidants, ER stress inhibitors, genetic manipulation of stress pathways) mitigates liver injury, inflammation and fibrosis in steatohepatitis models, suggesting a causal contribution of this KE. </li> <li> However, oxidative and ER stress are broadly involved in many forms of liver injury and can be both cause and consequence of other KEs (steatosis, inflammation). Complete elimination of oxidative/ER stress is rarely achieved experimentally, and some degree of inflammation can occur even with partially reduced stress. </li> <li> Therefore, this KE is a key amplifier and mediator but may not be strictly essential in all contexts; essentiality is rated as moderate. </li> </ul> <h2>KE8 – Hepatic inflammation, increased</h2> Essentiality: High (direct evidence relative to AO definition) <ul> <li> Steatohepatitis is defined histologically by the coexistence of steatosis and lobular inflammation with hepatocyte injury. Interventions that specifically reduce hepatic inflammation (e.g. NF‑κB inhibitors, anti‑TNF/IL‑1β strategies, macrophage‑targeted treatments) consistently attenuate the severity of steatohepatitis and slow or prevent progression to fibrosis, even when some degree of steatosis persists. </li> <li> Conversely, genetic or pharmacological manipulations that enhance inflammatory signalling in the liver exacerbate steatohepatitis. </li> <li> Given that inflammation is a defining component of the AO itself, this KE is essential for the expression of steatohepatitis as the endpoint of this AOP. </li> </ul> Summary Taken together, essentiality is strongest for KEs directly under FXR control (intestinal FXR, ileal FGF15/FGF19, hepatic SHP/CYP7A1 and BSEP) and for the defining hepatic manifestations of the AO (steatosis and inflammation). Intestinal barrier dysfunction and oxidative/ER stress are well‑supported contributors and amplifiers, but may not be strictly required in every possible context. Nonetheless, under the conditions for which this AOP is intended (metabolic stress plus gut–liver axis perturbation), modulation of each KE produces qualitatively consistent changes in downstream events and in the incidence and severity of steatohepatitis, providing an overall moderate‑to‑high level of support for essentiality across the pathway.

<h2>1) KER1 – Intestinal FXR inhibition → Ileal FGF15/FGF19 secretion, decreased</h2> Biological plausibility Intestinal FXR is highly expressed in ileal enterocytes and directly controls FGF15/FGF19 transcription through FXR response elements in the FGF15/FGF19 promoter. This FXR–FGF15/FGF19 axis is a central component of bile acid endocrine feedback and is well established in both rodents (FGF15) and humans (FGF19). Loss of FXR activation is therefore expected to reduce FGF15/FGF19 expression and secretion. Empirical support Multiple in vitro, animal and human studies show that bile acid or FXR agonist exposure robustly induces ileal FGF15/FGF19, whereas FXR inhibition, bile acid depletion, or FXR knockout markedly decrease it. Intestinal FXR knockout mice display reduced FGF15 and increased hepatic bile acid synthesis; FXR agonists or FGF19 analogues restore FGF19 levels and suppress bile acid synthesis. Overall, empirical support is strong and consistent across models. Quantitative understanding Quantitative relationships between FXR activation and FGF19 output have been described in cell models, ileal explants and human studies (e.g. FGF19 versus C4). However, explicit dose–response models linking defined degrees of FXR inhibition to FGF19 reduction across species are still limited; quantitative understanding is moderate. <h2>2) KER2 – Intestinal FXR inhibition → Ileal bile acid transporters (IBABP, OSTα/β), decreased</h2> Biological plausibility FXR directly regulates the expression of ileal BA transporters, including IBABP (FABP6) and OSTα/OSTβ (SLC51A/B), which are critical for intracellular BA buffering and basolateral export. Reduced FXR activity is expected to decrease transcription of these genes and impair ileal handling of bile acids. Empirical support FXR agonists increase IBABP and OSTα/β expression in vitro and in vivo, whereas FXR deficiency or inhibition reduces their expression. In FXR‑deficient or BA‑deprived models, intestinal BA transport is altered and BA distribution shifts, consistent with changes in transporter expression. Nevertheless, fewer studies directly quantify transporter changes in the specific context of steatohepatitis, so empirical support is moderate. Quantitative understanding Dose–response relationships between FXR activity and transporter expression have been demonstrated in cell models, but systematic quantitative data across species and time are limited. Quantitative understanding is low‑to‑moderate. <h2>3) KER3 – Ileal bile acid transporters, decreased → Intestinal barrier integrity, decreased</h2> Biological plausibility Loss of BA buffering and export (IBABP, OSTα/β) can increase intracellular and luminal accumulation of cytotoxic bile acids, which damage epithelial cells and tight junctions. FXR also contributes more broadly to barrier maintenance; reduced transporter expression therefore plausibly contributes to barrier dysfunction. Empirical support Several studies show that altered BA handling and FXR suppression are associated with decreased tight junction protein expression, increased intestinal permeability and enhanced bacterial translocation. Interventions that improve FXR signalling or modulate the BA pool can restore barrier function. However, most studies manipulate FXR or BA pools globally rather than isolating transporter changes, so causal separation of “transporter effect” from other FXR‑mediated effects is incomplete. Empirical support is moderate. Quantitative understanding Quantitative links between defined levels of transporter reduction and specific changes in permeability (e.g. TEER, FITC‑dextran flux) are sparse. Barrier disruption is typically reported qualitatively or semi‑quantitatively. Quantitative understanding is low. <h2>4) KER4 – Ileal FGF15/FGF19 secretion, decreased → Hepatic SHP decreased; CYP7A1/CYP8B1 derepressed</h2> Biological plausibility FGF15/FGF19 is a key endocrine mediator of negative feedback from intestine to liver. By activating FGFR4/β‑Klotho in hepatocytes, it induces SHP and represses CYP7A1/CYP8B1, thereby reducing bile acid synthesis. Reduced FGF15/FGF19 is therefore expected to diminish SHP signalling and derepress CYP7A1/CYP8B1. Empirical support FGF15/FGF19 deficiency or impaired FGFR4/β‑Klotho signalling leads to elevated CYP7A1 expression and increased bile acid synthesis in rodents and humans. Exogenous FGF19 or FXR agonists that restore FGF19 decrease CYP7A1 and BA synthesis. Correlations between lower FGF19 and higher C4 (a surrogate of CYP7A1 activity) in humans further support this relationship. Empirical support is strong. Quantitative understanding There is good quantitative correlation between serum FGF19 and C4 in humans, and dose–response data for FGF19 analogues exist in clinical and preclinical studies. However, complete quantitative models spanning from intestinal FXR perturbation to hepatic CYP7A1 output are not yet fully developed. Quantitative understanding is moderate. <h2>5) KER5 – Hepatic SHP,decreased; CYP7A1/CYP8B1,increased → Hepatic BSEP/MRP2 decreased</h2> Biological plausibility Hepatic FXR–SHP signalling coordinates BA synthesis and export. Reduced FXR/SHP activity that derepresses CYP7A1/CYP8B1 and increases BA synthesis tends to be accompanied by decreased expression of canalicular BA transporters (BSEP, MRP2), both of which are FXR targets. Thus, sustained reduction in FXR signalling is expected to decrease BSEP/MRP2 in parallel with increased BA synthesis, favouring intrahepatic BA retention. Empirical support FXR or SHP knockout models show both increased CYP7A1 and decreased BSEP expression, associated with BA retention and liver injury. FXR agonists increase BSEP/MRP2 expression and improve cholestatic phenotypes. However, not all studies directly link CYP7A1 increases with BSEP/MRP2 changes in a time‑resolved manner, and some compensatory responses occur. Empirical support is moderate‑to‑strong. Quantitative understanding Quantitative transcriptional and protein changes in BSEP/MRP2 after FXR modulation are available, but integrated quantitative models linking specific CYP7A1 increases to transporter changes and BA retention are limited. Quantitative understanding is low‑to‑moderate. <h2>6) KER6 – Hepatic BSEP/MRP2 decreased → Hepatic lipid accumulation (steatosis), increased</h2> Biological plausibility Reduced canalicular export of bile acids leads to intrahepatic BA accumulation, which disrupts hepatocyte metabolism, mitochondrial function and lipid handling. BA‑mediated stress can promote steatosis by impairing β‑oxidation and enhancing lipogenic signalling. Thus, loss of BSEP/MRP2 can indirectly favour steatosis in a susceptible metabolic background. Empirical support Human and animal models with BSEP deficiency or inhibition show BA retention, cholestasis and frequently co‑existing steatosis. FXR agonists that restore BSEP function often reduce both cholestatic markers and hepatic lipid accumulation. However, steatosis can arise through multiple mechanisms, and BSEP/MRP2 reduction is not universally required. Empirical support is moderate. Quantitative understanding While BA levels, transporter expression and steatosis scores are often reported together, formal dose–response relationships between transporter inhibition and degree of steatosis are not well characterised. Quantitative understanding is low. <h2>7) KER7 – Hepatic lipid accumulation increased → Hepatic oxidative and ER stress increased</h2> Biological plausibility Hepatic steatosis increases substrate flux through mitochondrial β‑oxidation and ER lipid handling, promoting ROS generation, lipid peroxidation and unfolded protein responses. Excess lipid load also leads to lipotoxic species that trigger ER stress and mitochondrial dysfunction. Thus, increased steatosis is expected to increase oxidative and ER stress. Empirical support Numerous models show that high‑fat diets or genetic manipulations causing steatosis are accompanied by increased markers of oxidative stress (e.g., MDA, 4‑HNE, 8‑OHdG) and ER stress (e.g., GRP78, CHOP). Interventions that reduce steatosis (e.g., improved insulin sensitivity, enhanced β‑oxidation) typically lower these stress markers, while forced lipid accumulation intensifies them. Empirical support is strong. Quantitative understanding Semi‑quantitative relationships (e.g., correlation between liver triglyceride content and oxidative stress markers) are frequently reported. Fully quantitative, mechanistic models exist in some systems biology studies but are not yet standard for this specific AOP context. Quantitative understanding is moderate. <h2>8) KER8 – Hepatic oxidative/ER stress increased → Hepatic inflammation increased</h2> Biological plausibility Oxidative and ER stress induce DAMP release, activate pattern‑recognition receptors, inflammasomes and stress‑activated kinases and converge on NF‑κB and AP‑1 activation. These pathways drive pro‑inflammatory cytokine and chemokine expression, recruiting and activating Kupffer cells and infiltrating leukocytes. Thus, increased oxidative/ER stress is expected to promote hepatic inflammation. Empirical support In steatohepatitis models, oxidative/ER stress markers and inflammatory markers increase in parallel. Genetic or pharmacological attenuation of oxidative/ER stress (e.g., antioxidants, chemical chaperones, inhibition of specific stress pathways) reduces hepatic inflammation and histological scores. Conversely, enhancing oxidative stress or ER stress increases inflammatory responses. Empirical support is strong. Quantitative understanding Correlations between the magnitude of oxidative/ER stress and inflammatory readouts are documented, but formal dose–response models and temporal mapping at the whole‑pathway level remain limited. Quantitative understanding is moderate. <h2>9) KER9 – Intestinal barrier integrity decreased → Hepatic inflammation increased</h2> Biological plausibility Loss of intestinal barrier integrity increases translocation of LPS and other microbial products into portal blood, where they activate TLRs and other receptors on Kupffer cells and liver sinusoidal cells. This drives NF‑κB activation and production of pro‑inflammatory mediators, contributing to hepatic inflammation. This gut–liver axis mechanism is well recognised. Empirical support Models with increased intestinal permeability (due to diet, FXR deficiency, microbiota imbalance or chemical insult) show elevated portal LPS, increased hepatic TLR signalling and enhanced liver inflammation. Interventions that restore barrier function (e.g., FXR agonists, probiotics, barrier‑strengthening agents) reduce LPS levels and hepatic inflammatory markers. Empirical support is strong, though barrier damage is not the only route to liver inflammation. Quantitative understanding Some quantitative data relate permeability measures (e.g., FITC‑dextran flux, zonulin levels) to portal LPS concentrations and inflammatory markers, but there is no standardised quantitative model across species. Quantitative understanding is low‑to‑moderate. <h2>10) KER10 – Hepatic inflammation increased → Steatohepatitis</h2> Biological plausibility Steatohepatitis, by definition, requires steatosis plus lobular inflammation and hepatocyte injury (ballooning). Sustained hepatic inflammation drives cell death, ballooning and fibrogenic activation, converting simple steatosis into steatohepatitis and promoting progression to fibrosis. Empirical support In animal and human steatohepatitis, inflammatory cell infiltration and cytokine production correlate with histological steatohepatitis severity. Anti‑inflammatory interventions (e.g., NF‑κB or cytokine targeting) reduce lobular inflammation and ballooning, attenuating steatohepatitis even when some steatosis persists. Conversely, enhancing inflammatory signalling exacerbates steatohepatitis. Empirical support is strong. Quantitative understanding Histological grading systems (e.g., NAS) incorporate inflammatory lesions; quantitative relationships exist between inflammatory scores and progression to steatohepatitis and fibrosis. However, fully quantitative mechanistic models linking specific inflammation magnitudes to AO incidence across populations are still emerging. Quantitative understanding is moderate.

<div> <table class="table table-bordered table-fullwidth"> <thead> <tr> <th>Modulating Factor (MF)</th> <th>Influence or Outcome</th> <th>KER(s) involved</th> </tr> </thead> <tbody> <tr> <td>Diet composition (high fat/fructose, low fibre, choline deficiency)</td> <td>Promotes steatosis and oxidative stress; low fibre and choline deficiency promote dysbiosis and barrier disruption. For the same FXR perturbation, Western‑type diets lead to earlier and more severe hepatic steatosis and inflammation.</td> <td>KER3 (barrier integrity ↓); KER6 (steatosis ↑); KER7 (oxidative/ER stress ↑); KER8 (hepatic inflammation ↑); KER10 (inflammation ↑ → steatohepatitis)</td> </tr> <tr> <td>Co‑medications and co‑exposures affecting FXR or BA pathways (e.g. FXR agonists/antagonists, BA sequestrants, some antibiotics)</td> <td>Can either exacerbate or attenuate intestinal FXR inhibition and BA dysregulation. FXR agonists may partially compensate for weak environmental FXR inhibitors, while other drugs that perturb BA homeostasis can sensitize the system, shifting response–response curves left or right.</td> <td>KER1 (FXR → FGF15/FGF19); KER2 (FXR → transporters); KER4 (FGF15/FGF19 → SHP/CYP7A1); KER5 (FXR/SHP → BSEP/MRP2)</td> </tr> <tr> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>Genetic variation in FXR–FGF19 axis and BA/lipid metabolism (FXR, FGF19, FGFR4, BSEP, CYP7A1, etc.)</td> <td>Alters sensitivity and capacity of FXR signalling and downstream responses. Loss‑of‑function variants can lower the level of upstream perturbation needed to trigger downstream KEs and AO; protective variants may increase resilience.</td> <td>MIE (intestinal FXR inhibition); KER1 (FXR → FGF15/FGF19); KER4 (FGF15/FGF19 → SHP/CYP7A1); KER5 (FXR/SHP → BSEP/MRP2); KER6–KER8 (steatosis, stress, inflammation)</td> </tr> <tr> <td>Co‑existing liver injury (alcohol, viral hepatitis, other hepatotoxins)</td> <td>Provides an inflammatory and fibrogenic background that amplifies oxidative stress and immune activation. For the same gut–liver perturbation, hepatic inflammation and steatohepatitis develop more rapidly and severely.</td> <td>KER7 (oxidative/ER stress ↑ → inflammation ↑); KER8 (hepatic inflammation ↑); KER10 (inflammation ↑ → steatohepatitis)</td> </tr> </tbody> </table> </div>

For this AOP, the overall quantitative understanding is semi‑quantitative and heterogeneous across KERs. Proximal FXR‑dependent steps are best characterised: dose–response relationships between bile acid/FXR agonist exposure and ileal FGF15/FGF19 expression and secretion are available from in vitro models, ileal explants and human studies, and there is a robust inverse relationship between circulating FGF19 and markers of hepatic bile acid synthesis (e.g., C4), supporting a reasonably well‑defined quantitative link between the MIE, KE1 and KE4. Likewise, multiple studies provide semi‑quantitative associations between the magnitude of hepatic steatosis (KE6) and markers of oxidative/ER stress (KE7) and inflammation (KE8), as well as between histological activity scores and the severity of steatohepatitis (AO). However, for several intermediate KERs—particularly those involving ileal bile acid transporters and intestinal barrier integrity, and the transition from altered bile acid export (KE5) to steatosis (KE6)—data are largely correlative or categorical, and explicit dose–response and time‑course functions are sparse. Species differences in bile acid composition and FXR ligand potency, and the influence of modulating factors such as metabolic status and microbiota, further complicate quantitative extrapolation to humans. Overall, while the direction and relative sensitivity of most KERs are supported by multiple datasets, fully parameterised response–response functions suitable for formal quantitative AOP (qAOP) modelling exist only for selected parts of the pathway (e.g., FXR–FGF19–CYP7A1), and the AOP is currently best used in a qualitative or semi‑quantitative manner rather than for precise numerical prediction of steatohepatitis incidence.

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