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METABOLOMICS
Title
Modern and emerging form of
advanced diagnostic strategy in
chemical pathology
Title
Scientific study of chemical
processes involving metabolites
Title
Systematic study of the unique chemical
fingerprints that specific cellular processes
leave behind i.e. The study of their small
molecule metabolite profile
Definition
Quantitative measurement of the dynamic
multiparametric metabolite response of living
systems to pathological stimuli or genetic
modifications
metabolomics
Metabolite measurement
Integral part
• Clinical practice
• Clinical chemistry
Monitoring human physiology
• Quick
• Inexpensive
• Non-invasive
Urinary glucose
 Serum creatinine
Chemical pathology
Branch of pathology that deals with the
analysis and interpretation of biochemical
test and diagnosis
Clinical
chemistry
Clinical
biochemistry
Medical
biochemistry
Metabolomics vs Clinical Chemistry
Distinguishing
feature
fact
Ultra high throughput clinical chemistry
History
METABOLOMICS
Chinese doctors
1500 BC
Ancient Greeks
300 BC
“Humor”
The body fluid
Founding father
Sanctoria Sanctorius
17th Century
J J Thompson
1905
The first mass spectrometer
1990
Hydrophilic
interaction
chromatography
1960s
era of
chromatography
HPLC coupled DAD
GC/MS
LC/MS
TOF
GC & LC MS/MS
tandem system
Metabolite
Metabolome
Metabolic profiling
Any substance involved in metabolism either as a
product or an intermediate product of metabolism
is known as metabolite
Good indicator
of state of
health
Metabolite
dynamics
m/z ratio-2005
Cataloguing of 2500 metabolites-2007
40,000 metabolites/largest repository-2011
Metabolites and Metabolomics
Molecule of < 1 kDa
Exceptions
• Sample type
• Detection method
Lipoprotein
Albumin
Human based metabolomics
Exogenous
Endogenous
Xenometabolites
Metabolome
 It is the quantitative complement of all low molecular weight molecules,
present in the cells in a particular physiological or developmental state
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Represents the collection of all metabolites
Dynamic: changing from second to second
Human metabolome- 7800 metabolites
Familiar clinical
standards
Horning
Amino acids
1971
Glucose
Creatinine
Urea
Standard
metabolomic
run
Lesser known compounds
Lactate
Pyruvate
Taurine
Glycerol
Metabolic
profiling
Thrombaxne
Citrulline
Citrate
Comprehensive
picture
Measure all metabolite
at one time
Insight in patients
physiology/metabolism
Metabolomic measurement and
information
Important physiological information
Gene chips
2 D gels
Tissue biopsies
Profiling
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2
Detailed analysis by hyphenated techniques
• GC/MS
• LC/MS
• CE/MS
Detailed chromatographic profile of samples
measurements of :
• Relative amounts
• Absolute amounts
3
Number of components measured
• Resolution of chromatographic system
• Specificity of detection technique
Profiling Redefined
“untargeted analysis of comparative samples using
hyphenated approaches”
In vitro metabolic profiling
 Versatile analytical
method
 LC/MS
 qualitative
 quantitative
 Use of MS as a
detection method
 High detection
specificity
 Mass selective detection
 Mass to charge ratio
(m/z)
 Ionization
 TOF spectrometry
Sample requirements
Biofluids
•blood
•Urine
•Bile
•CSF
Cryo vials
Bio fluids vs Tissues
Easier to process/analyze
MS
NMR
HPLC
fluids
Sample preparation
Deproteinization
Lyophilization
Chemical derivatization
Oximation
Trimethylsilation
QC Samples
•Theoretically identical samples
•Similar metabolic and matrix composition
Types of QC samples
Pooled QC samples
• Pool of all biological samples to be studied
Commercial QC samples
• Commercially available biofluids composed of
multiple biological samples not present in the study
Reasons for applying QC samples
1
To condition or equilibrate the analytical platform e.g.
after preventive maintenance
2
To obtain data to calculate technical precision within each
analytical block
3
To obtain data to be used for signal correction within and
between analytical blocks
Instrumentation
Separation
techniques
GC
Detection
techniques
LC
MS
CE
NMR
HPLC
UPLC
Combined
techniques
GC/MS
HPLC/MS
LC/MS
TANDEM
MASS SPECTROMETRY
Mass spectrometer
Combined with separation devices
GC
LC
MS/MS
Analogous technique
1st stage separation
2nd stage separation
Wrong concept
Metabolic profiling and identification
Aim
In vitro profiling
Is to find out the number of metabolites formed by various
biotransformation reactions and abundances of the formed metabolites
Versatile analytical methods

Combination
 qualitative
 quantitative
Mass spectrometry
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High detection specificity
Mass selective
chromatographic
separation


Low complete
chromatographic
separation
Different molecular
weight
Metabolomics data



Digitized spectra
List of metabolite levels
Matrix
 Rows
 columns
.
Statistical programmes


Mass spectrometry
Nuclear magnetic
resonance spectroscopy
MS data software

Distinguish molecules that
vary in subject groups on the
basis of
 Mass
 Retention time
Comprehensive metabolomics software
• XCMS
• Global MS-based metabolomics
data sets developed in 2006
• Other programmes for mass
spectral analysis
• MZmine
• MetAlign
• Statistical projection methods
• Principal components analysis
• Partial least squares regression
Emerging applications of metabolomic
profiling
o
Clinical and epidemiological metabolomics provide a unique
opportunity to look at genotype-phenotype relationships
Provides information
o Universal outcome of influencing factors on disease states
o Great potential
o Early diagnosis
o Therapy
o Monitoring of disease
o Understanding pathogenesis of the disease
New modalities
•Discover new ways to aid diagnosis
•Assessment of glycaemic status
•Reduce diabetic complications
•Improve quality of life
New PUTATIVE biomarkers
•Peptides
•Proteins
•Metabolites
•Nucleic acids
Metabolomics as an approach
.identification/assessment of metabolic characteristics
.increasing feasibility because of sensitivity/specificitivity
.advances in analytical/information technologies
Metabolomics application in clinical
diagnosis and prognosis of diabetes
ADA recommendations

Officially recommends HbA1C testing

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
Diagnosis
Monitoring
Need for new biomarkers

Drive to reconsider diagnostic criteria in GDM
Metabolic markers of type-2 DM
Established, new, and emerging metabolomic
biomarkers for type 2 diabetes
Metabolic markers
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Insulin
Glucose
Gamma-Glutamyl transferase (GGT )
Alanine aminotransferase (ALT)
Ferritin
Pancreatic polypeptide
Fibronectin
Fetuin A
Sex hormone–binding globulin SHBG
Free testosterone
Insulin-like growth factor I( IGF-I)
Insulin receptor
Creatine kinase-MB (CKMB )
MR-Pro atrial natriuretic peptide( MR_PRO)
NT-Pro B-type natriuretic peptide( NT-PRO-BNP)
B-type natriuretic peptide (BNP)
Positive correlation
•Insulin resistance
•Oxidative stress
•Ch low grade inflammation
Hepatic secretory
peptide
•Binds insulin receptors
•Inhibits insulin action
Biomarkers of glycaemia

Glycated hemoglobin HbA1c

Fructosamine

1,5-Anhydroglucitol (1,5AG)

Glycated albumin

Glycated insulin

Glycosylated amylin

Glycated LDL
Predictor of onset
of DM
• normal glycaemic
control
Markers of oxidative stress and
nutrient status

Glutathione GSH

Advanced glycated end products receptor (RAGE)
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Ascorbic acid Vitamin C

25-Hydroxyvitamin D Vitamin D

Homocysteine

Branched-chain and aromatic amino acids Leucine, Isoleucine,
Valine, Tyrosine, Phenylalanine
Lipid-related markers
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Leptin
Adiponectin
Apolipoprotein B (ApoB)
Apolipoprotein A (ApoA)
Endothelial and inflammatory
markers
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C-reactive protein
Interleukin-18
Interleukin-1 receptor antagonist (IL-1ra)
Interleukin-2 receptor antagonist (IL-2ra)
Interleukin-6
Plasminogen activator inhibitor-1
Cell adhesion molecule
Tissue plasminogen activator antigen
Neopterin
Von Willebrand factor
Branched chain amino acid profiles

Assessing diabetes risk
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Elevated levels
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Predict early onset
Combination (branched chain aromatic amino acids)
 Leucine
 Iso-leucine
 Valine
 Tyrosine
 Phenylalanine
Profile vs single amino acid
Panels of combined biomarkers
Awareness
Facilitate
Reliance
Diabetes related
metabolomic
analytes
Use of panels of
combined
biomarkers
on single
biomarker
6-biomarker model

Kolberg et al
○ Evaluation of 6-biomarker model
 Adiponectin
 CRP
 Ferritin
 IL-2ra
 Glucose
 Insulin
○ Danish inter 99 cohort
 Developed Type 2 Diabetes Mellitus
Conclusion of study
Showed improved performance over single marker, HbA1c or FBG
4-biomarker model

Salomaa et al
 Evaluation
of 31 novel biomarkers
 4-biomarker
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panel
Adiponectin
Apo B
CRP
Ferritin
Study group
Number
(n)
Clinical
incident
DM(n)
Median
follow-up
(years)
FINRISK 97
7827
417
10.8
Health 2000
4977
179
7.1
Inference
Metabolic profiling in Diabetes Mellitus
Data, biomarker scores, significant potential, future prediction ,amino acid profiles
Metabolic profiling in heart diseases
Scope
•Identification of potential markers
Efficient / timely delivery
•Available therapeutic resources
Type of a new diagnostic test
•Considerable promise
•Clinical management of CAD
•Insight into the underlying
metabolic disturbances
Urinary metabolic profiling
•Expanding field of systems
biology research
•Methodologies
•LC/MS
•GC/MS
•NMR spectroscopy
Eric Chun Yong
•GC/MS results are comparable to NMR and LC/MS
•Urinary metabolic profiling protocol
•400-600 metabolites in 120 urine samples per week
Thank you
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