developing standards for metabonomics as a clinical tool

Developing standards for metabonomics as a clinical tool.

Agnieszka M. Lichanska, Shaffinaz Abd Rahman

and Horst J. SchirraSchool of Dentistry and IMB, University of Queensland, Australia

Dr A. Lichanska, ComBio 2007

Introduction


Genomics and proteomics tells you what might happen, but metabolomics tells you what actually did happen.

- Bill Lasley, University of California, Davis


Genomics

Transcriptomics

Proteomics

MetabolomicsMetabonomics

DNA

RNA

Protein

Metabolites

25,000 genes

100,000 mRNAs

1,000,000 proteins

2,500 metabolites

Metabonomics in context


Introduction

Metabonomics•'The quantitative measurement of the dynamic multiparametric metabolic response of living systems to pathophysiological stimuli or genetic modification' (Nicholson et. al.)

•Use of statistical methods to detect changes in metabolites over time or between groups.

Metabolomics

•The characterisation of all metabolites in a sample/organism.

… a lot of people use both terms interchangeably…


Metabolic changes

Genetic changes (mutations)

Drugs, diet

Changes in metabolite concentration

Blood Urine other biofluids

NMR, MS spectra

Disease

Identification of individual metabolites

Detailed analysis

Metabolic changes and their analysis

Metabolite Database


Methods• Bruker 500MHz spectrometer with sample

changer• Urine from fasted male mice

– WT controls– Mutant mice– Age 2-12 months

• Samples frozen upon collection• 1M Phosphate buffer

• TSP, D2O


Nuclear Magnetic Resonance (NMR) - based metabonomics

• Advantages:

– Fully quantitative– Non-destructive– Minimal sample preparation– High throughput

• What can be analyzed?

– Analysis of all types of biofluids (urine, plasma, saliva, cerebrospinal fluid, sperm, synovial fluid, amniotic fluid)

– Solid samples (biopsies of organs and cell cultures)


Mouse studies - physiology of growth hormone

WT 569 391 GHR -/-

Rowland, Lichanska et al 2005, MCB 25:66-77

Model - GHR KI mice


Mouse studies - physiology of growth hormone

Schirra et al 2007, under review


Clinical Applications


Applications• Health management

– Non-invasive monitoring of asthma in children - University Hospital Padua

• Drug intervention - evaluation of drug treatment

• Risk management - exposure to toxic substances

• Lifestyle/diet studies – Nestle (age, gender, smoking, alcohol, menopause, sport, BMI)

• Nutritional applications - Nestle studies (chocolate, coffee)

• Diagnostics

– CARDIUM project - Varese Hospital

– Tumor markers - epithelial ovarian cancer (serum)

– Inborn metabolic disorders

– Meningitis diagnosis (cerebrospinal fluid)


Diagnosis of inborn errors of metabolism

Disorders of:• carbohydrate metabolism

– E.g. glycogen storage disease

• amino acid metabolism– E.g. phenylketonuria

• organic acid metabolism- E.g. alcaptonuria

• fatty acid oxidation and mitochondrial metabolism

• porphyrin metabolism• purine or pyrimidine metabolism

– E.g. Lesch-Nyhan syndrome

• steroid metabolism– E.g. congenital adrenal hyperplasia

• mitochondrial function• peroxisomal function

– Zellweger syndrome

• Lysosomal storage disorders– Gaucher's disease


Sample preparation study


Methods• Bruker 500MHz spectrometer with sample

changer• Urine from a healthy volunteer

– 1st urine of the day– Collected midstream

• 1M Phosphate buffer

• TSP, D2O

• Na Azide• Storage conditions variable


Study design

Untreated Centrifuged

First morning urine

Room Temp.

on ice / -20°C

1% Sodium Azide Ultra-Filtrated (MWCO 10 kDa)

The samples were stored either at -20oC or at RT and were measured on day 0, 2 and 9.

Sterile filtration 0.2m


Day 01% Sodium Azide

Ultra-Filtrated Centrifuged

Untreated

Blue Spectra – Room TemperatureRed Spectra – In Ice

• Spectra are identical, irrespective of treatments

• Ultra-filtrated samples had addition glycerol signals

Glycerol


Day 2

-20°C Untreated

RT Untreated

-20°C 1% Sodium Azide

RT 1% Sodium Azide

-20°C Centrifuged

RT Centrifuged Formate

Formate

Formate

Acetate

Ethanol

Acetate

AcetateEthanol

Ethanol


Comparison between treatments days 0-9

Day 0

Day 2

Day 9

Day 9

Day 2

Day 0

CentrifugedFormate

Formate

Formate

Formate

Ethanol

EthanolAcetate

Acetate

Acetate

Acetate

Untreated


Sample analysis

SDS-PAGE

SF

1

ULF

1

ULF

2

untr

eate

d 2

ULF

3

ULF

4

SF

1

SF

2

untr

eate

d 1

SF

2

Urine sample

SDS-PAGE Microbiological testing:

1. Microscopy2. Growth on basal media (agar plates)

Stain with Coomasie

Scoring for growth on plates and

presence/absence of yeast or bacteria by

microscopy


Summary• Storing samples at RT caused them to have ageing effects

formed from microbial contamination in the samples

• Sterile filtration samples kept at -20 °C were the only treatment that showed consistently no presence of those metabolites

• Optimal method:1. Sterile filter samples2. add 1% sodium azide3. Measure at Day 04. Store at -20°C

• Ethanol, acetate and formate signals should be excluded in all statistical study as it was proven that elevated concentrations of these metabolites were due to external ageing reactions.


Metabolomics standards initiative (MSI, http://msi-workgroups.sourceforge.net/ )

• Sample information – Collection details (date, place, method, frequency)– Extracts from tissues or solid state analysis - processing details– Patient information (diet, drugs, infections, chronic diseases, etc) – Volume collected, pH, osmolarity, – Sample storage (temperature, additives)– Sample processing details

• NMR/MS data acquisition– QC procedures, used of internal standards, – Instrument performance and maintenance logs has to be documented– Acquisition protocol details - SOP establishment– Instrument specifications

• Data analysis– All data manipulations should be specified, MSI has a format for reporting

analysis

• Data format – Exchangeable file format– Raw data access for future re-analysis or reference

http://msi-workgroups.sourceforge.net/


FDA and metabonomic studies

• Metabolomics data is currently being evaluated by the voluntary genomics data submission (VGDS) group.

• Such data is likely to be included in FDA submissions to support:– A mechanism of a drug– Metabolite/s are used biomarkers in evaluations

• Metabolic markers are seen as most relevant for understanding the mechanism of action, defining the safety of a compound, and for monitoring clinical efficacy.

• A metabolomic report should include a number of information mentioned before. The two important issues are the selection of controls and the analysis methods used to identify the biomarker/s


AcknowledgmentsIMBDr. Horst J. SchirraCameron AndersonLinda KerrSheryl MaherJenny RowlandProf. Mike J. Waters Prof. David J. Craik

Mater Children’s HospitalProf. Francis BowlingTeresa MunceDr. Gary LeongTony Huynh

School of Dentistry/IMBShaffinaz Abd Rahman

University of OhioProf. John Kopchik

Queensland Smart State Fellowship

developing standards for metabonomics as a clinical tool

Health & Medicine

c ethanol

metabolites metabonomics

c untreated rt untreated

sample changer urine

sodium azide rt

formate signals

pyrimidine metabolism

carbohydrate metabolism