1. METABOLOMICS
Dr. Neel Shah

5. What is metabolomics?
Quantifying metabolite levels in biological fluids
Using this data to infer meaningful insight into new biochemical pathways
And metabonomics, metabolome?

6. How to measure? Started of by measuring qualitatively
(Williams R J. Individual metabolic patterns and human disease : an exploratory study utilizing predominantly paper chromatographic methods,1951 )
Quantitative analysis began by use of LCMS, NMR
(Pauling L, Robinson AB, Teranishi R, Cary P. Quantitative Analysis of Urine Vapor and Breath by Gas-Liquid Partition Chromatography,1971)

7. 1. Separation of metabolites
HPLC, GC, CE, UPLC

8. 2. Detection and quantificationMS
Magnetic field/ Electric field (TOF MS)
Collision induced fragmentation
Tandem MS

9. 2. Detection and quantification
NMR (nuclear magnetic resonance)
NMR or LCMS alone is not sufficient to detect all metabolites

10. Identifying the compound
Based on mass, mass/charge ratio, retention time
If we know what to search for and analyze-targeted approach
If we don’t know which metabolite to search for or which one will get affected in that disease, we take help of statistics: ‘chemometrics’
PCA-principal component analysis-where mathematical models are formed to explain the maximum variation in metabolite levels between different subjects, just as in pharmacometrics using NON-MEM software

14. Applications 1. Identifying markers of good/poor response

15. Aspirin study
Higher levels of adenosine and inosine in poor responders
Good responders
Metabolic profiling
Poor responders
‘Metabolomics informed pharmacogenomics approach’
New hypothesis
SNP search in purine pathway
SNP in ADK gene linked with respone
Inosine, guanosine levels associated with this SNP

16. 2. Statin study
Good responders
Both had:
↑ arachidonic acid
↓ linoleic acid
Action independent of HMG-CoA reductase inhibition
Poor responders
New
mechanism
Arachidonic acid-
pro-inflammatory anti-inflammatory
Pre-treatment levels of 2◦ bile acids correlated positively with response
2-hydroxy valeric acid levels correlated negatively

17. 3. Markers of disease
Phenylketonuria - tandem MS used in USA for screening to detect phenylpyruvate in urine
Diabetic nephropathy - Elevated sphingomyelin and VLDL and reduced HDL in type 1 diabetes patients with nephropathy as compared to those without nephropathy
Chronic inflammation
RA-↓ Sr. glutathione, ↑ lipid peroxides, ↑ lactate, ketones and glycerol in synovial fluid
OA- ↑ valine (essential amino acid)
Crohn’s, ulcerative colitis- ↓ butyrate, acetate and methylamine in stool extracts

18. 4. Role of gut flora
P-cresol produced by flora leading to paracetamol toxicity?
Phosphatidylcholine, trimethylamine N-oxide, betaine causing cardiovascular diseases?

19. 5. Predicting CYP3A activity
Ln (CL) = X I X DHEA X R X R2
I = 1 for CYP3A5*1/*3, 0 for CYP3A5*3/*3
R1= 7-β-OH DHEA/DHEA
R2=6- β-OH cortisone/cortisone
The clearance calculated with the help of this model correlated well with the midazolam clearance

20. Predicting drug toxicity
Elevated long chain acylcarnitines- paracetamol toxicity before transaminases get elevated
Application in drug development process

21. Factors affecting metabolome
Reproduced from: Johnson CH, Patterson AD, Idle JR, Gonzalez FJ. Xenobiotic metabolomics: major impact on the metabolome. Annu Rev Pharmacol Toxicol 2012;52:37–56

22. How to nullify variation during experiments?
Affected by many factors, difficult to control
Human experiments:
Same age, gender, environment
Standardize food, avoid smoking, alcohol
Animal experiments:
Control housing conditions, breeding conditions
To resemble humans, enzyme of interest can be genetically modified, e.g.- PXR humanized mice, PPAR-γ humanized, CYP3E1 humanized mice

23. Summary To discover new pathways of drug action
To differentiate poor and good responders
Metabolomics informed pharmacogenomics
To find out markers of drug action
To understand effect of microbiome on metabolome
Find new disease markers
Predict status of metabolizing enzymes
Predict drug toxicity

24. Conclusion
Measuring metabolites is easier with LCMC, NMR and with large databases t hand
We have more data than can be understood
Metabolomics is the integration of proteomics, transcriptomics, genomics and environmental influence
It is a snapshot of the current pathophysiological states
Each person has his own characteristic metabolome

25. THANK YOU