This document discusses the evaluation of drug toxicity through metabolomic profiling. It describes how metabolomics can be used to detect liver and kidney toxicity induced by various compounds. The study designs involve administering hepatotoxic or nephrotoxic drugs to animals and collecting blood, urine, and tissue samples for analysis. Nuclear magnetic resonance spectroscopy is used to analyze metabolic profiles in biofluids and multivariate statistical analysis is applied to identify biomarkers of toxicity. The document outlines several studies conducted by the National Institute of Food and Drug Safety Evaluation investigating drug toxicity using metabolomics approaches.
UGC NET Paper 1 Mathematical Reasoning & Aptitude.pdf
2009 약물대사기반 심포지엄-정호상(3)
1. Evaluation of Drug Toxicity
by Metabolom Profiling
Ho-Sang Jeong, Ph. D
Div. of Pharmacological Research, NIFDS
2. From Genes To Metabolites
GENOME
protein-gene
interactions
PROTEOME
protein-protein
interactions
METABOLISM
Bio-chemical
reactions
Citrate Cycle
3. Metabolomics: A Multidisciplinary Study
Urine
Serum
tissue
NMR spectra processed PCA
Raw NMR spectra
control STOCSY
Discovery of biomarkers disease or
Identification of metabolic pathway toxicity
4. Effort of NIFDS for Metabolomic Study
Year Budget (KWon) Contents
Metabolomics를 이용한내분비장애추정물질의 안전성 예측 방법 연구
2006 32,000 (metabolic study of putative endocrine disruptor)
식욕억제제의 약물동태 및 대사 연구
(Pharmacokinetic study of anorexic drug using metabolomics)
Metabolomics를 이용한 간독성 평가방법 개발 (Liver toxicity study using metabolomics)
NSAIDs 약물의 약물이상반응에 대한 안전성 예측 연구 (1)
(ADR study of NSAIDs using metabolomics)
2007 46,000 대사체 생체지표를 이용한 내분비계 장애작용 예측 연구
(metabolic study of putative endocrine disruptor)
And etc
Metabolomics를 이용한 신독성 평가방법 개발 (Kidney toxicity study using metabolomics)
NSAIDs 약물의 약물이상반응에 대한 안전성 예측 연구 (2)
(ADR study of NSAIDs using metabolomics)
2008 41,500
And etc
간독성평가를 위한 시험관내시험계에서의 전사체대사체 발현 분석 연구
(In vitro liver toxicity study using integrated omics technologies)
2009 37,000 NSAIDs 약물의 약물이상반응에 대한 안전성 예측 연구 (3)
(ADR study of NSAIDs using metabolomics)
And etc.
Total 156,500
8. Treatment and sample collection: Liver Toxicity
CCl4 1 ml/kg, p.o
Acetaminophen (AAP) 2 g/kg, p.o for 2 days
D-Galactosamine (GalN) 0.8 g/kg, i.p
Plasma clinical chemistry (blood)
Histopathology (liver)
Urinal NMR (urine)
0 1 2
Day
9. Study Design: Kidney Toxicity
Nephrotoxicity
Clinical Chemistry
HgCl2
Kidney weight Kidney Damage
Cis-platin
SD Histopathology
Gentamicin
p-Aminophenol
Metabolomics
- Urine Nephrotoxicity biomarker
Administration HgCl2 0.1 or 0.75 mg/kg, ip
Cis-platin (CP) 5 mg/kg for 2 days or 20 mg/kg for single, ip
Gentamicin (GEN) 5 or 160 mg/kg for 2 days, ip
p-Aminophenol (PAP) 10 or 200 mg/kg, ip
11. Biomaterial collection for PAP treatment
Plasma clinical chemistry (blood)
Histopathology (kidney)
Kidney wt
Urinal clinical chemistry (urine)
Urinal NMR (urine)
Treatment
0 1 2 3
Days
12. Import techniques and procedures in
metabonomics
NMR
Pattern recognition methods
Supervised techniques (PCA)
Unsupervised techniques (PLS-DA)
13. Histopathology: Liver
Control, Day 2 CCl4 1 ml/kg, Day 1 CCl4 1 ml/kg, Day 2
A B C
AAP 2 g/kg, Day 2 GalN 0.8 g/kg, Day 1 10
F
D E 8
**
Liver injury score
**
6
**
**
4 **
2
0
1
2
2
1
2
1
2
2
1
2
ay
ay
ay
ay
ay
ay
ay
ay
ay
ay
D
D
D
D
D
D
D
D
D
D
N
N
on
on
on
P
on
on
l4
l4
A
C
C
al
al
C
C
C
C
C
A
C
C
G
G
CCl4 AAP GalN
15. Multivariate statistical data analysis
SIMCA-P ver.11 (Umetrics, Umeå, Sweden)
Partial Least Squares (PLS) discriminant analysis
Very importance variables (VIP) were also utilized to
select putative markers for hepatotoxicity induced by
CCl4, AAP, and GalN.
16. Global profiling : Liver Toxicity
■ Day 0
● Day 1
♦ Day 2
CCl4 AAP GalN
A B C
17. Global profiling of hepatotoxicants
GalN Day1
Class 1
GalN Day5
Class 2
CCl4 Day 1
Class 9
CCl4 Day 11
Class 2
AAP Day 16
Class 2
Control (Day 0)
Class 19
23. C
C on
on _C
_C C
C l4
0.0
2.5
5.0
7.5
10.0
l4 _D
0
1
2
3
_D C ay
C ay C C
C C on l4_ 1
**
on l4_ 1 _ C Da
C y
*
_ C Da
C y l4 1
l4 1 _D
_D C ay
C ay C Cl4 2
2 on _
C Cl4
on _D _ A Da *
A y
**
_A ay P 2
A 2 _D
P
_D A ay
C A
A ay
C A on P_ 1
on P_ 1 _ G Da
y
*
Taurine
_ G Da al
y N 1
al 1 _D
N G ay
_D a
C
2-Oxoglutarate
G ay
C a on lN_ 1
_ G Da
**
on lN_ 1
y
**
al
_ G Da N 1
al y _D
N 1 G
_D ay
al
G ay N 2
al _D
N 2 ay
_D
ay 2
2
C
C on
on _C
_C C
C l4
0
1
2
3
4
5
l4 _D
0
1
2
3
4
_D C ay
C ay C C
C C on l4_ 1
on l4_ 1 _ C Da
**
_ C Da C y
C y l4 1
l4 1 _D
_D C ay
C ay C Cl4 2
C Cl4 2 on _
on _
*
_ A Da
A y
*
_ A Da
A y P 2
P 2 _D
_D A ay
A ay C A
C A on P_ 1
Citrate
on P_ 1 _G D
_G D ay
ay al
N 1
Succinate
al
N 1 _
_D G Da
G ay C a y
C a on lN_ 1
on lN_ 1 _G D
_G D ay
ay al
al N 1
N 1 _D
_ G ay
G Da
Determination of endogenous metabolites
al
al y N 2
N 2 _D
_D ay
ay 2
2
24. C C
on on
_C _C
C C
l4
0.0
0.1
0.2
0.3
l4
0
5
10
15
_D _D 20
C ay C
C 1 C
ay
C l C l4 1
on 4_
D
on _
**
_C ay _ C Da
C 1 C y
l4 l4 1
_D _D
C ay C ay
C 2 C C 2
C l4 on l4
_D
on _D
_A ay _A ay
A 2 A 2
P P
_D _D
A ay A ay
A C A
C 1 on P_ 1
Acetate
on P_
D _ G Da
_G ay al y
al 1 N 1
N _D
_D G
Betaine
ay
G ay C al
N 1
C al
N 1 on _
on _D _ G Da
_G al y
ay N 1
al
N 1 _D
_D G ay
al 2
G ay N
al
N 2 _D
_D ay
ay 2
2
C
on
C _C
on
_C C
l4
0
2
4
6
8
10
C _D
l4 C
_
0
1
2
3
4
5
ay
C C
C Da
C C y on l4_ 1
on l4 1 _ C Da
_C _D C y
l4 1
C ay _D
l4
_ 1 C ay
C Da C Cl4 2
C Cl y on _
on 4_ 2 _ A Da
_A D A y2
A ay P
P _D
_ 2 A a
A Da C A y
C on P_ 1
o n AP y 1
Lactate
_ G Da
_G _D al y
1
Allantoin
al ay N
N _D
_ 1 G a
G Da
C a C alN y 1
on lN y 1 on _
_G _D _ G Da
al y
al ay N 1
N _D
_ 1 a
G
Determination of endogenous metabolites
G Da
al y al y 2
N
N _d
*
_D 2
ay
**
ay
2
2
25. C
C on
on _C
_C C
C l4
0.0
0.1
0.2
0.3
l4 _D 0.4
0.00
0.05
0.10
0.15
0.20
_D C ay
C ay C C
C C on l4_ 1
on l4_ 1 _ C Da
*
_ C Da C y
**
C y l4 1
l4 1 _D
_D C ay
C ay C Cl4 2
C Cl4 2 on _
on _ _ A Da
_ A Da A y
A y P 2
P 2 _D
_D
A ay
A ay C A
C A on P_ 1
**
on P_ 1 _ G Da
_ G Da y
al y al
N 1
N 1
Phenylacetate
_D
_D G ay
Hippurate
G ay C a
C a on lN_ 1
on lN_ 1 _ G Da
*
_ G Da y
al y al
N 1
N 1 _D
_D G ay
G ay al
al N 2
N 2 _D
_D ay
ay ** 2
2
C
on
C _C
on
C
_C l4
0.0
0.2
0.4
0.6
C _D
l4
0
1
2
3
C ay
_D C 1
C ay C l4
C C 1
on _D
*
on l4_ _C ay
_ C Da C 1
y l4
C 1 _D
l4
_D C ay
C C 2
C
ay C l4
C l4 2 on _D
on _D _A ay
**
_A ay A 2
A P
P 2 _D
_D
A ay
A ay C A 1
C A 1 on P
on P_ _D
_G ay
_ G Da
y al
N 1
al
N 1 _D
_D
G a
G
Benzoate
ay al y 1
C al 1 C N
1-Methylnicotinamide
o n N_ on _
*
_ G Da
**
_ G Da
y al y 1
al
N 1 N
_D _D
G G a
Determination of endogenous metabolites
al ay
N al y 2
N
_4 2 _D
D
*
ay ay
2 2
26. Fingerprint of endogenous metabolites
Standard deviations from mean compound concentration
-3.0 -2.5 -2.0 -1.5 -1.0 -0.5 0.5 1.0 1.5 2.0 2.5 3.0
Compounds
Controls
Samples
Hepatotoxicant
27. Results and conclusion
□ Current study provides that urinary 1H NMR spectral based
metabolomics is a new approach to determine the change in
endogenous metabolites in animals exposed to hepatotoxicants of
CCl4, AAP, and GalN. NMR spectra showed pattern recognition
using PLS-DA through distinct separation of clustering in
hepatotoxicants-treated urine samples.
This pattern recognition may be used to screen hepatotoxic new
drug candidates in early preclinical studies.
We proposed 12 putative biomarkers to predict hepatotoxicity
induced by chemicals using NMR targeted analysis.
□ Classical clinical chemistry and histopathology provided
validation for this study and this database of biomarker patterns
may be useful for further study.
□ The suggested biomarkers should be explained how to involve in
mechanism of hepatic injury. The further study with other
hepatotoxicants needs to identify the endogenous biomarkers.
28. Histopathology : Kidney-HgCl2
Control HgCl2_0.1 mg/kg_D3 HgCl2_0.1 mg/kg_D6
a b c
d e
×100
HgCl2_0.75 mg/kg_D3 HgCl2_0.75 mg/kg_D6
