Next Generation Metabolic Screening

11th Middle East Metabolic

Group meeting - MEMG22-25 October 2014, Marrakech, Morocco

Prof. dr. Ron Wevers, Department of Laboratory Medicine,

Radboudumc, Nijmegen, The Netherlands

1997

There is no single analytical platform that canmeasure all metabolites

The metabolome

NMR based metabolomics

BODY FLUID NMR SPECTROSCOPY IN INBORN ERRORS OF METABOLISM

Body fluid NMR• Diagnosis of 106 IEM (1D

and 2D COSY)• 1H resonances from 158

metabolites involved IEM• Seven novel inborn errors

could be defined

LimitationSensitivity: low micromolarrange

Molecular complexity in Life Science

Number of Dynamic molecular entities range__

Genomics 104 103

Proteomics 106 1010+

Metabolomics 104 106+

Typical eukaryotic organisms contain between 4000 and 50000 metabolites (Kegg: 16896; HMDB 2012: 7900; HMDB 3.6: 41808)

METABOLIC SCREENING

IN THE INDIVIDUAL PATIENT

Metabolomics – analysis of “all” metabolites

Human plasma, CSF(urine)

Controls vs. patient

Agilent QTOF MS-data

- Reverse phase liquid chromatography- Positive and negative mode- Features

• Accurate mass (165.07898)• Retention time• Intensity

(New) biomarkers for diseases

XCMS

AlignmentPeak comparison> 10,000 Features

Q-tof mass spectrometry

Molecular mass: 118.0266

C4H6O4

Methylmalonic acid

Accuracy of Q-tof analysis

Deviation from actual mass for 19 metabolites(Mass range 90.0552 – 428.3737 Dalton)

mass number of metabolites

0.0000 20.0001 100.0002 40.0003 20.0004 1

19

Q-tof sensitivity

Sensitivity

Q-TOF low nanomolar range

NMR low micromolar range

Factor 1000 more sensitive thanNMR!

Pipecolic acid

S/N=20

500 nmol/L

50 nmol/L

5 nmol/L

no addition

Pipecolic acid added to urine (diluted 50x)

Validation Next Generation Metabolic Screening (NGMS)

• Comparison signal intensity withconcentratios classical assays

• Mass accuracy on QTOF:95%: ΔM < 0,0003 Da(range: 90-425 Da; n=19)

• Sensitivity of UHPLC-QTOF MS assay in low nM range!(~1000 fold more sensitive than NMR)

• Intra: CV in RT: <0.5%; CV in signal intensity: <15%Inter: CV in RT: <1%; CV in signal intensity: <25-30%

• Clinical validation: diagnosis established in16 individual patients with different IEMs

Standard operation procedure for plasma and CSF samples introduced in patient care in 2014

Where is/are the biomarker(s)?

10,480 features

10,480 Features (incl. adducts etc)Mass, Retention time, Intensity

INPUT

Endogenous metabolites

Diet derived

Intestinal flora input

Medication

ANALYTICAL

Original small molecules

Adduct information (Na+, K+, NH4+)

In source fragments

13C variants

How to explain 10.000 features in plasma?

Which features are the IEM biomarkers

10,480 features

Experiment

Alignment

Peak Comparison

Raw data

Corrected t-test

Intensity/P Ranking

Dat

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Identification T20

Verification

Dat

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Pre

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Dat

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sG sT Feature

Patient 7 Feature

Intensity P-value Mass Ret1 74 1909 24490807 2E-17 166.08634 3.672 51 1695 8386343 8E-21 120.08065 3.673 47 1683 2915430 6E-21 167.08956 3.674 62 1780 751272 2E-19 121.08385 3.675 56 1765 556095 3E-20 103.05433 3.676 38 1611 480141 1E-22 120.12527 3.677 57 1956 460491 3E-20 166.19191 3.678 55 1761 403223 3E-20 131.04910 3.679 35 1559 355404 2E-23 188.06796 3.67

10 3 1137 303853 8E-40 295.12893 5.8811 65 4994 291156 5E-19 188.12476 3.6612 49 1762 269007 7E-21 107.04902 3.6713 43 1659 252382 6E-22 168.09171 3.6714 52 1727 250238 8E-21 149.05937 3.6715 32 1492 140562 6E-25 120.15785 3.6716 76 2854 135373 2E-17 189.07304 1.0417 16 1018 126136 7E-29 328.13918 4.0118 23 1516 96662 1E-26 120.17050 3.6719 135 265 93406 1E-10 104.10735 12.8520 96 670 77111 4E-14 397.23525 14.3121 128 294 76090 3E-11 104.10733 12.6722 120 79 64437 3E-12 467.25918 7.4523 66 1719 61501 6E-19 204.04192 3.6724 125 89 60054 2E-11 467.00845 7.4525 121 91 57801 3E-12 622.67550 7.4526 108 87 57092 9E-13 622.34113 7.4527 4 1139 51484 2E-37 296.13220 5.8828 97 65 51462 5E-14 405.22508 12.55

▼

Patiënt 7

Feature 1909

Controls

P7P7

PKU

HMDB: phenylalanine

Feature 1137

Controls

P7P7

PKU

HMDB: glutamylphenylalanine

PKU: two biomarkers

Phenylketonuria

Patiënt Metaboliet rI rP

PKU-1 (BB07/01056)

Phe=204 (ref 17-140)

L-Phenylalanine

F8091 (m152.94715; 18.34)

F1018 (m328.13918; r4.01)

Glutamylphenylalanine

N-Acetyl-L-phenylalanine

1

5

15

16

134

285

141

28

51

162

PKU-2 (BB09/01551)

Phe=202 (ref 17-140)

L-Phenylalanine

Glutamylphenylalanine

F1018 (m328.13918; r4.01)

N-Acetyl-L-phenylalanine

1

16

20

126

447

42

28

86

PKU-3 (BB09/01183)

Phe=355 (ref 17-140)

L-Phenylalanine

Glutamylphenylalanine

F1018 (m328.13918; r4.01)

N-Acetyl-L-phenylalanine

1

14

15

128

100

9

8

116

PKU-4 (BB09/00590)

Phe=528 (ref 17-140)

L-Phenylalanine

Glutamylphenylalanine

F1018 (m328.13918; r4.01)

N-Acetyl-L-phenylalanine

1

9

12

42

1

10

8

12

PKU-5 (BB09/01951)

Phe=384 (ref 17-140)

L-Phenylalanine

Glutamylphenylalanine

F1018 (m328.13918; r4.01)

N-Acetyl-L-phenylalanine

1

58

59

142

204

93

66

67

PKU-6 (BB09/02152)

Phe=241 (ref 17-140)

L-Phenylalanine

F1018 (m328.13918; r4.01)

Glutamylphenylalanine

1

13

14

101

19

32

PKU-7 (BB10/00030)

Phe=359 (ref 17-140)

L-Phenylalanine

Glutamylphenylalanine

F1018 (m328.13918; r4.01)

N-Acetyl-L-phenylalanine

1

10

17

160

74

3

16

117

Control

PKU

P6P6

N-Acetyl-L-phenylalanine[F1031; m208.0968, r7.65]

I

F1018 is an as yet unidentified biomarker for PKU

II

PKU: but also two as yet unknown biomarkers

rI rP Feature

Patient 7 Feature

Intensity P-value Mass Ret1 74 1909 24490807 2E-17 166.08634 3.672 51 1695 8386343 8E-21 120.08065 3.673 47 1683 2915430 6E-21 167.08956 3.674 62 1780 751272 2E-19 121.08385 3.675 56 1765 556095 3E-20 103.05433 3.676 38 1611 480141 1E-22 120.12527 3.677 57 1956 460491 3E-20 166.19191 3.678 55 1761 403223 3E-20 131.04910 3.679 35 1559 355404 2E-23 188.06796 3.67

10 3 1137 303853 8E-40 295.12893 5.8811 65 4994 291156 5E-19 188.12476 3.6612 49 1762 269007 7E-21 107.04902 3.6713 43 1659 252382 6E-22 168.09171 3.6714 52 1727 250238 8E-21 149.05937 3.6715 32 1492 140562 6E-25 120.15785 3.6716 76 2854 135373 2E-17 189.07304 1.0417 16 1018 126136 7E-29 328.13918 4.0118 23 1516 96662 1E-26 120.17050 3.6719 135 265 93406 1E-10 104.10735 12.8520 96 670 77111 4E-14 397.23525 14.3121 128 294 76090 3E-11 104.10733 12.6722 120 79 64437 3E-12 467.25918 7.4523 66 1719 61501 6E-19 204.04192 3.6724 125 89 60054 2E-11 467.00845 7.4525 121 91 57801 3E-12 622.67550 7.4526 108 87 57092 9E-13 622.34113 7.4527 4 1139 51484 2E-37 296.13220 5.8828 97 65 51462 5E-14 405.22508 12.55

▼

222

Compound Adduct In-sourceL-Phenylalanine M+H

L-Phenylalanine +L-Phenylalanine 13C

L-Phenylalanine +L-Phenylalanine +L-Phenylalanine +L-Phenylalanine +L-Phenylalanine +L-Phenylalanine M+Na

Glutamylphenylalanine M+Na

L-Phenylalanine +L-Phenylalanine +L-Phenylalanine +L-Phenylalanine +L-Phenylalanine +

?? N-(1-Deoxy-1-fructosyl)phenylalanine

L-Phenylalanine +????

L-Phenylalanine M+K

???

Glutamylphenylalanine 13C

?

Patient 7: Phe=359 µmol/L (ref 17-140)

PKU166

PKU5197

PKU664

PKU373

PKU490

PKU780

PKU2195

45 features(7 metabolites)

- Phenylalanine- Glutamylphenylalanine- Phenylalanine + C6H10O5

- Mass 278.17518 Unknown- Prolyl-L-phenylalanine + H2

- N-Acetyl-L-phenylalanine- Mass 424.17163 Unknown

Plasma biomarkers for PKU patients

Untargeted metabolomics: Xanthinuria

Xanthine Uric acid

Child, 2.5 months with kidney stones; urine metabolome analysis

Xanthine

Xanthine oxidase

Uric acid

CONCLUSIONS:• Xanthinuria I (isolated xanthine oxidase)• Xanthinuria II (combined xanthine oxidase

+ aldehyde oxidase defect)

Targeted analysis of markers specific for xanthinuria type II

CONCLUSION:

Xanthinuria type II (diagnosed in urine sample without allopurinol loading)

Hydantoin 5-propionate Pyridoxal

The clinical validation

Amino acid disorders

Fatty acid oxidation

Organic acidurias Miscellaneous

PKU MCAD MSUD Xanthinuria II

Hyperprolinemia II VLCAD HMG-CoA lyase Amino acylase I

Hyperlysinemia MCC Antiquitin (ATQ) def.

MAT I/III IVA Beta-ketothiolase

Alcaptonuria Dimethylglycinuria

Ureidopropionase

Diagnosis on plasma samples

Current status: 23 inborn errors

Where is Wally?

2012

PatientTargeted

Metabolic screen

Targeted gene

analysis

Diagnosis+ follow-up

2013 / 2014

Patient

Whole exome

sequencingTargeted

confirmatory metabolite +

enzyme testing

Diagnosis+ follow-up

Targeted assays vs holistic approach

Next generation metabolic screening

Times are changing… whole exome analysis

Nijmegen four day march

The bridge between the exome and the metabolome

The Nijmegen approach

Conclusions

• Next Generation Metabolic Screening (NGMS) introduced

in diagnostics of the individual patient

• NGMS will change the metabolic laboratory

• NGMS bridges whole exome sequencing and metabolic

diagnostics: integrative biology in a functional genomics

setting

• The technique we have developed is also of interest outside

the field of inborn errors

METABOLIC SCREENING

The individual patient suspected for an IEM WES and NMGS in parallel together with dept. Genetics Radboudumc

C.D.G Huigen

E. van der Heeft

U.F.H. Engelke

R.A. Wevers

L.A.J. Kluijtmans

Nijmegen metabolomics

C. van Karnebeek,

Vancouver

J. Engel

S. Wortmann-Hagemann

The human metabolome HMDB

Food constituents FooDB

Medication Drugbank

Genetic disease OMIM

Pathway analysis Pathman-SMP

(Kegg)

Challenge - 1

Integrate databases

Challenge - 2

The issue

ApolarLC-Qtof This lecture (reversed phase)* column options Zhang T; Anal Chem 2012

PolarGC-(tof)MS Fiehn O; Trends in Anal Chem 2008 Capillary Electrophoresis-(tof)MS Ramataur R; Mol Biosyst 2011HILIC Nijmegen, 2014

Challenge - 3

The big data

• Pathway analysis• How to integrate Whole Exome Sequencing data with the

metabolomics data?

METABOLIC SCREENING

IN THE INDIVIDUAL PATIENT

DNA SEQUENCING

IN THE INDIVIDUAL PATIENT

Integratingsoftware

The next step

The coding data of the humangenes

10

,48

0

Challenge - 4

The intracellular metabolome

HILIC-ToF-MS analysis urine samples (XBridge amide)

Reproducibility retention times

Standard solution polar compounds (n = 4)

Verbinding Retentietijd

gemiddelde %CV

Arginine 10.07 0.08

Asparagine 8.59 0.10

Aspartic acid 9.47 0.41

Glutamic acid 8.69 0.33

Glutamine 8.37 0.18

Histidine 9.84 0.46

Isoleucine 5.77 0.48

Leucine 5.50 0.57

Lysine 10.33 0.14

Methionine 6.07 0.37

Phenylalanine 5.35 0.34

Proline 6.52 0.49

Serine 8.46 0.20

Threonine 7.81 0.17

Tryptophan 5.31 0.11

Tyrosine 6.44 0.00

Valine 6.39 0.08

Quality requirement RT: CV ≤ 0.5%

HILIC-ToF-MS analyse van urinemonsters. Kolom: XBridge amide

Herhaalbaarheid retentietijden

Analyse standaardoplossing polaire metabolieten (n = 2)

Eis: retentietijd %CV ≤ 0.5%Verbinding Retentietijd

gemiddelde ∆rt

Cytosine 4.33 0.04

Kreatinine 3.61 0.05

Betaine 5.92 0.09

Nicotinic acid 3.94 0.17

Kreatine 7.47 0.06

Adenine 3.28 0.01

Hypoxanthine 3.60 0.06

Xanthine 3.97 0.04

Carnitine 6.75 0.09

2,8-Dihydroxyadenine 7.36 0.03

Cafeïne 1.42 -0.01

Cytidine 5.41 0.08

2'-deoxyadenosine 3.08 0.01

2'-deoxyinosine 3.96 0.06

2'-deoxyguanosine 4.93 0.04

Adenosine 3.68 0.02

Inosine 4.78 0.08

Guanosine 5.76 0.07

Xanthosine 5.52 0.12