metabolomics & biomarker discovery

METABOLOMICS&

Biomarker discovery

Anika Vaarhorst (a.a.m.vaarhorst@lumc.nl)Section of Molecular EpidemiologyLeiden University Medical CentreLeiden, The Netherlands

What is Metabolomics

• The nonbiased identification and quantification of all metabolites in a biological system

• Metabolites are the biochemicals including lipids, sugars, nucleotides, amino acids and related amines of < 2000 Dalton to be found in biological fluids

• All metabolites combined make the human metabolome

Why metabolomics

• More than 4000 metabolites can be measured by different platforms in blood. Not all at high throughput yet.

• Blood is the highway for degraded, secreted, discarded and synthesized molecules.

• Indicates tissues lesions, organ dysfunction and pathological state

• As -omics technology is close to biomedical phenotypes.

Epigenome

Pathman.smpdb.ca

Suhre et al. PLoS ONE | November 2010 | Volume 5 | Issue 11

Metabolites marking diabetes in patients

environment

Metabolome PhenotypeGenotype

Wang et al., Nat Med 2011: markers of 4 x increased T2D risk branched chain amino acids, tyrosine and

phenylalanine

Suhre et al., Nat 2011 Genetically Determined Metabotypes 37 genetic loci accounting for 10-60 variance in level

Administration of branched amino acids increased insulin resistance

Psychogios et al. 2011 PloS One

A step to step approachBiological

experiment

Raw data

Clean data

Data fit for analysis

Rank the important metabolites

Sample extraction NMR analysis

Data preprocessing

Data pretreatment

Data analysis

Van den Berg et al. 2006 BMC Genomics

Sample analysis 1H-NMR spectroscopy

vacuum

Liquid nitrogen

Liquid helium

coil

core

The sample is in the tube, which is in the probe, which is in the core of the magnetic field.

Metabolomics, NMR

1, imidazole; 2, urea; 3,D-glucose; 4, L-lactic acid; 5, glycerol; 6, L-glutamine; 7, L-alanine; 8, DSS; 9, glycine; 10, L-glutamic acid; 11, L-valine; 12, L-proline; 13, L-lysine; 14, Lhistidine;15, L-threonine; 16, propylene glycol; 17, L-leucine; 18, L-tyrosine; 19, L-phenylalanine; 20, methanol; 21,creatinine; 22, 3-hydroxybutyricacid; 23, ornithine; 24, L-isoleucine; 25, citric acid; 26, acetic acid; 27, carnitine; 28, 2-hydroxybutyric acid; 29, creatine; 30, betaine; 31, formic acid; 32,isopropyl alcohol; 33, pyruvic acid; 34, choline; 35, acetone; 36, glycerol.

Analyse known variables 50

Data pretreatment

• Check for outliers• Check for distribution

• Centering• Scaling• Transformations

Data analysis

• Univariate analysis• Univariate analysis combined with step wise

regression– multicollinearity

• LASSO regression, elastic net, ridge regression, PLS-DA

Multiple testing

• Bonferoni correction– 100 tests, test with a significance level of 0.05– P after Bonferoni correction: 0.05/100 = 0.0005– For metabolomics to conservative

• Replicate your findings in independent studies• Cross-validation

Storey and Tibshirani 2003, PNAS

Confounding

• Confounder variable: a variable other than the predictor variables that potentially affects the outcome variable

• Prevent confounding:– Matching– Stratification

• Controlling for confounding– Include the known confounders as covariates in your

model

Metabolite

Outcome variable

Confounder

Problems: Confounding• Brindle JT et al., 2002. Nat Med. 8(12), 1439-

45. → NMR spectroscopy is diagnostic for the occurrence and severity of CAD

• But according to: Kirschenlohr et al. 2006. Nat Med. 12(6), 705-10.– Gender & statin treatment affect the ‘biomarkers’

of disease → groups must be stratified

– NMR analysis of plasma is a weak predictor for CAD

BBMRI Rainbow RP4 MetabolomicsApplying Metabolomics in Dutch cohorts

Reference populations • Leiden Longevity Study (LLS)• Netherlands Twin Register (NTR)• Erasmus Rucphen Family study (ERF)

• Selection based on existing metabolomics data • Extensive phenotypic data

High throughput / high resolution NMR

LUMCDeelder et al.

Mass spectrometry: Biocrates platform Gieger et al.

Mass spectrometry: Nederlands Metabolomics Centre, lipid platformHankemeier et al.

Netherlands Twin Registry

Leiden Longevity Study

Erasmus Rucphen Study

Lipidomics

Matrix Citrate plasma Citrate plasma Citrate plasma

Stored at -30°C -80°C -80°C

Fasted yes no Yes

N 3000 2201 3000 1H-NMR

Matrix EDTA plasma EDTA plasma Serum

Stored at -30°C -80°C -80°C

Fasted Yes No Yes

N 3000 2487 3000

Biocrates

Matrix Serum Serum Serum

Stored at -30°C -80°C -80°C

Fasted yes 267 (yes)/390(no) Yes

N 1900 657 994

327 metabolites measured

146

124

512

40

Biocrates N=163

Lipidomics N=1291H-NMR N=52

The practical

Long-lived siblings

Offspring of long-lived siblingsSpouses as controls

Which metabolites differ between controls and offspring of long-lived siblings