Centro Europeo di
Risonanze Magnetiche
una infrastruttura di ricerca nel Polo
Scientifico dell’Università di Firenze
Claudio Luchinat
CERM
Università di Firenze
Il Polo Scientifico di Sesto Fiorentino
The Magnetic Resonance Center in
Florence
700b
Bio-labs
800
950
850ss
900
700
Conference room
Library
Workshop
Computer room
400
500
600b
600
700ss
Department
of Chemistry
(offices, bio-labs,
relaxometer, instruments..)
GENEXPRESS, CRYST, CISM
DaVEB Biobank
CERMinstrumentation
instrumentation
NMR
Cryo
400 MHz 500 MHz
600 MHz
Cryo 900 MHz
Cryo
600 MHz
Cryo
700 MHz (a) 700 MHz WB
850 MHz WB
Cryo
Cryo
700 MHz (b) 800 MHz
Cryo 950 MHz
The Magnetic Resonance Center in
Florence
Electron/nuclear relaxation (Relaxometry)
Drug discovery
Structural proteomics
Metabolomics
Protein structure determination
Methodological advancements in NMR
Solid state NMR
ICT and computational biology
700b
Bio-labs
800
950
850ss
900
700
Conference room
Library
Workshop
Computer room
400
500
600b
Department
of Chemistry
(offices, bio-labs,
relaxometer, instruments..)
600
700ss
We provide access to European researchers
since 1994
New access program Bio-NMR (2010-2014)
started September 2010
Access provided by Florence, Frankfurt, Utrecht, Lyon/Grenoble,
Berlin, Zurich, Brno, Ljubljana, Oxford, Birmingham, Goteborg
GENEXPRESS, CRYST, CISM
DaVEB Biobank
Metabolomica:
uno sguardo molecolare
sulla salute e sulle malattie
Claudio Luchinat
CERM
Università di Firenze
The Research Centers of FiorGen
CERM
Scientific Campus
Sesto Fiorentino
Biomedical Campus
Careggi
Scientific Publications
146 publications on high level journals, starting from 2004
Independent reviewers attested the high scientific level of the Foundation
“The scientific production of FiorGen is quite impressive”
Prof. Arturo Falaschi
Scuola Normale Superiore – Pisa
Distinguished Scientist ICGEB Trieste
Aprile 2008
“The scientific productivity of FiorGen is of excellent level”
Prof. Giuseppe Novelli
Tor Vergata University of Rome
University of Arkansas (USA)
WPQ PGx EMEA (UK)
Maggio 2008
What is Metabolomics?
Metabolomics is a further “omic” science that is now emerging with the purpose of
“elaborating a comprehensive analysis of the metabolome, which is the complete set of
metabolites in an organism or cell”.
Genomics tells you what could happen. Metabolomics tells you what has
happened. Only a few thousand metabolites.
!! However, not negligible external variability !! (source of noise)
Examples of metabolites
NH2
H
N
H2N
OH
OH
NH
O
O
Arginine
P
N
O
H2N
OH
O
N
O
P
H2N
OH
O
Glycine
N
O
O
N
O
OH
OH
O
P
OH
NH2
HO
OH
Adenosine-5'-triphosphate
N
H
Tryptophan
O
O
OH
OH
HO
Succinic acid
O
O
O
Pyruvic acid
OH
HO
O
O
Oxaloacetic acid
Acetyl CoA
Metabolomics
Study of small molecules in biological fluids
+
Metabolic fingerprint
1H
NMR spectrum of ethanol
H
__
H
H
|
|
H
H
__ | __ | __
O C C H
1H NMR spectrum (upfield part) of human urine
1H NMR spectrum (downfield part) of human urine
2 Routes to Metabolomics
Two approaches:
• Identify as many metabolites as possible
• Use the whole spectrum as a fingerprint (statistics)
ppm
7
6
5
TMAO creatinine
hippurate
allantoin creatinine taurine citrate
urea
2-oxoglutarate
succinate
water
fumarate
ppm
7
6
5
4
3
2
1
Chemometric methods
(fingerprinting and pattern recognition)
Quantitative
methods
hippurate
4
3
2
1
25
PC2
20
15
10
5
0
-5
-10
-15
-20
-25
-30
PC1
-20
-10
0
10
The fingerprint
Traditional clinical analysis:
Metabolomics:
Few already known
metabolites for some
disease (e.g. glucose
for diabetes, etc…)
All metabolites are
analyzed together
without prior
knowledge
The fingerprint
What are they doing ?
The fingerprint
Only an analysis at a global
level can tell the whole story
METabolomic REFerence
Ind 1
Ind 2
10.00
7.50
5.00
2.50
ppm
METabolomic REFerence
Ind 1
Ind 2
10.00
7.50
5.00
2.50
ppm
METabolomic REFerence
Convex hulls of 22 donors in the three most significant PCA-CA dimensions
PCA for data
reduction
“natural” gender discrimination
CA for obtain
well separated
clusters
KNN for
classification
99% accuracy
in montecarlo
cross validation
MALE
FEMALE
Assfalg, Bertini, Colangiuli, Luchinat, Schäfer, Schütz, Spraul, PNAS, 2008, 105, 1420-4
The signature of Our Body
• There exists an individual human metabolic phenotype (metabotype)
• The metabotype consists of a variable part (environment) and an invariant part
(genetics + environment)
• The invariant part persists for at least two-three years (if the diet is averaged using
collection of multiple samples)
• The discovery of the existence of individual metabotypes is the baseline for Biomedical
Researches
Assfalg, Bertini, Colangiuli, Luchinat, Schäfer, Schütz, Spraul, PNAS, 2008
Bernini, P.; Bertini, I.; Luchinat, C.; Nepi, S.; Saccenti, E.; Schäfer, H.; Schütz, B.; Spraul, M.; Tenori, L. J. Prot. Res. 2009
Metabolomics @CERM/CIRMMP
Collaborative Projects
•SPIDIA (7th framework program)
Standardization and improvement of pre-analytical procedures for in-vitro diagnostics.
•CHANCE (7th framework program)
Evaluation of the impact of nutritional criticalities in population at risk of poverty using NMR
metabolomics.
•livSYSiPS (ErasysBio+)
The sistem biology of network stress based on data generated from in vitro differentiated
hepatocytes derived from individual-specific human iPS cells.
•ITFoM (FET Flagship Initiative)
The aim of ITFoM is to develop models of human pathways, tissues, and ultimately of the whole
human, to create a “virtual patient” which will enable physicians to identify personalised prevention
schedules and treatments adapted to each person.
•Progetto COSMOS (EU Coordination action)
To develop new standard for metabolomics sutdies
•Progetto BioMedBridges (EU Coordination action)
To develop a unified framework for biomedical studies in Europe
•Progetto Melanoma (Ente Cassa di Risparmio di Firenze)
New strategies for diagnosis prognosis and treatment of melanoma.
Metabolomics @CERM/CIRMMP
Collaborations
•Celiac Disease (Prof. Antonio Calabrò, Careggi Hospital)
•Geriatric patients (Dr. Laura Biganzoli, Prato Hospital)
•Diabetes in young (Dr. Sonia Toni, Mayer Children’s Hospital)
•BPCO (Dr. Massimo Miniati, Careggi Hospital and CNR Pisa)
•Metastatic Colorectal Cancer (Dr. Benny W. Jensen, Herlev Hospital, Copenhagen)
•Periodonitis (Dr. Mario Aimetti, University of Turin)
•Bladder and Prostate Cancer (Dr. Marco Carini, Careggi Hospital)
•Cardiovascular Risk (Dr. Adriana Tognaccini, Pistoia Hospital and AVIS Toscana)
•Intestinal Bowel Diseases (Prof. Maurizio Vecchi, University of Milan)
•Heart Failure (Prof. Franco Gensini, University of Florence)
•Breast Cancer (Dr. Angelo Di Leo, Prato Hospital)
•Bariatric Surgery (Prof. Bernd Schultes, St. Gallen Hospital, Switzerland)
•Metabolomics of the Mitochondrion (Prof. Roland Lill, University of Marburg, Germany)
•Osteoarthritis (Prof. Brandi, University of Florence)
•Krabbe disease (Dott.sa Alice Luddi, University of Siena)
•Gestational diabetes (Dr. Dani, Careggi Hospital)
Celiac Disease Metabolomics
Clusterization of Celiac and Healthy subject serum spectra
Bertini, I.; Calabrò, A.; De Carli, V.; Luchinat, C.; Nepi, S.; Porfirio, B.; Renzi, D.; Saccenti, E.;
Tenori, L. The metabonomic signature of celiac disease, J. Proteome Res. 2009, 8(1), 170
Celiac Disease Metabolomics
Clusterization of Celiac and Healthy subject serum spectra
and corresponding Follow-up
Bertini, I.; Calabrò, A.; De Carli, V.; Luchinat, C.; Nepi, S.; Porfirio, B.; Renzi, D.; Saccenti, E.;
Tenori, L. The metabonomic signature of celiac disease, J. Proteome Res. 2009, 8(1), 170
Celiac disease
There exist a metabolic fingerprint of
celiac disease
Celiac – Healthy Subjects – Cross: predicted Potential Celiac
These alteration are present also in
potential celiac subjects: so they
precede the intestinal damage
Potential CD largely shares the
metabonomic signature of overt CD.
Most metabolites found to be
significantly different between control
and CD subjects were also altered in
potential CD. Our results suggest
early institution of GFD in patients
with potential CD
Bertini, I.; Calabrò, A.; De Carli, V.; Luchinat, C.; Nepi, S.; Porfirio, B.; Renzi, D.; Saccenti, E.; Tenori, L. The metabonomic
signature of celiac disease, J. Proteome Res. 2009, 8(1), 170
Bernini P, Bertini I, Calabrò A, la Marca G, Lami G, Luchinat C, Renzi D, Tenori L. Are patients with potential celiac disease really
potential? The answer of metabonomics. J. Proteome Res. 2010
http://www.fiorgen.net/
https://www. davincieuropeanbiobank.org
Breast cancer metabolomics
Classification between
Pre-Op and Metastatic
subjects.
Accuracy ~80%
Other comparisons
NOESY
CPMG
Healthy vs
Met
Accuracy
73.44%
Healthy vs
Post-op
Accuracy
75.80%
Post vs
Met
Accuracy
74.96%
Healthy vs
Met
Accuracy
72.67%
Healthy vs
Post-op
Accuracy
70.00%
Post-op vs
Met
Accuracy
70.00%
Colorectal Cancer Metabolomics
Serum samples from 139 HS and 155 patients with
mCRC, included in a prospective phase II study of 3rd
line treatment with cetuximab and irinotecan
We can discriminate healthy controls from mCRC with
almost 100% accuracy.
We can predict the overall survival of the patients
Cross-validated results on the Training Set:
PLS-CA model: long survival, in
blue; short survival, in yellow
Sensitivity :
Specificity:
Accuracy:
79.9%
76.4%
78.5%
Univariate Cox Regression Analysis for the Validation
Set:
HR:
3.30
95% CI:
P:
2.02 to 5.37
1.75 ∙ 10-6
Bertini I, Cacciatore S, Jensen BV, Schou JV, Johansen JS, Kruhøffer M, Luchinat C,
Nielsen DL, Turano P., Cancer Res. 2012 Jan 1;72(1):356-64. Epub 2011 Nov 11
Heart failure metabolomics
Classification between different subgroups of Heart failure
patients (1D CPMG spectra).
Sensitivity
Specificity
Accuracy
CMD vs CMS
45.52%
68.29%
61.19%
NYHA1 vs NYHA 2
61.88%
71.42%
67.71%
NYHA2 vs NYHA 3/4
73.62%
56.44%
68.04%
NYHA 1 vs NYHA 3/4
74.83%
68.55%
72.15%
Patients vs Healthy
85.11%
91.04%
87.29%
Patients are separated from healthy, but there is not any significant
difference between the disease grading that could reflect the clinical
severity of the disease.
Although good discrimination between healthy and HF subjects with a severe
disease, if not expected, was easy to be hypothesized, a comparable good
discrimination ability between healthy and HF subjects with a mild disease was
unexpected and appears rather counter-intuitive.
Metabolomics of Melanoma
NOESY Spectra
SERUM
URINE
Sensitivity (%)
Specificity (%)
Accuracy (%)
Sensitivity
(%)
Specificity (%)
Accuracy (%)
Healthy vs. Melanoma
91.38
81.67
89.89
95.46
70.52
91.37
Stage I/II vs. Healthy
85.49
85.34
85.25
91.03
79.02
87.46
Stage III/IV vs. Healthy
88.84
91.40
89.3
85.44
80.25
82.93
Stage I/II vs III/IV
85.18
73.28
79.94
75.40
67.86
72.98
Fingerprint of Obesity
Fingerprint of obesity
NW vs SO
94.0
OW vs SO
79.6
NW vs OW
69.7
NW vs OW+SO 87.8
NW+OW vs SO 84.1
The prediction of OW (stars) using the NW (green) vs SO (blue)
model classify almost all OW as SO (except two)
Da Vinci European BioBank
Metabolomica
L’approccio combinato di metabolomica (Prof. Claudio Luchinat) e
biobanca (Prof. Paola Turano) ci rende unici in questo settore della
scienza
Spettro NMR di urina di un donatore sano
FROM
DallaMETABOLOMICS
Metabolomica
Metabolomic
analysis
Analisi
Metabolomica
Validation
Controllo of
sample
quality
Qualità di campioni
Nelle
biobanche
in biobanks
Definizione
di
Definition of
new SOPs
Nuove
SOP
TO BIOBANKS
Alle
Biobanche
http://www.fiorgen.net/
https://www. davincieuropeanbiobank.org
Fiorgen ha implementato una Biobanca su standard europei che è inserita nei
programmi nazionali ed europei. Essa raccoglie campioni biologici (sangue,
urine, biopsie) di molte malattie .
Collezioni di campioni della Biobanca:
1.
2.
3.
4.
5.
6.
7.
Scompenso cardiaco (Prof. Gianfranco Gensini)
Melanoma (Prof. Nicola Pimpinelli)
Cancro alla mammella (Prof. Angelo Di Leo, e USA)
Cancro al colon (Prof. Benny V. Jensen, Danimarca)
Disturbi alla prostata (Prof. Marco Carini)
Celiachia (Prof. Antonio Calabrò)
Osteoporosi (Prof.ssa Maria Luisa Brandi)
http://www.fiorgen.net/
https://www. davincieuropeanbiobank.org
The Future of Medicine
Metabolomics can monitor the same individual in a
multidimensional space
hepatocarcinoma
Colorectal cancer
cirrhosis
steatosis
Intestinal bowel disease
Metabolic syndrome
Healthy aging
Diabetes
Hearth Failure
Hypertension
Et interviene di questa come dicono e’ fisici
dello etico, che nel principio del suo male
è facile a curare e difficile a conoscere,
ma, nel progresso del tempo, non l’avendo
in principio conosciuta né medicata,
diventa facile a conoscere e difficile a
curare.
Machiavelli, Il Principe, cap. 3
Il sogno
Dotare ogni cittadino di un chip in cui
sono riportati il genoma, il proteoma e il
metaboloma al fine di monitorarne nel
tempo lo stato di salute
http://www.fiorgen.net/
https://www. davincieuropeanbiobank.org
The Future of Medicine
From general to personalized medicine
Ivano Bertini
December 6, 1940
– July 7, 2012
Metabolomics @CERM/CIRMMP
Metabolomics Publications
Human phenotypes
• Assfalg M, Bertini I, Colangiuli D, Luchinat C, Schäfer H, Schütz B, Spraul M. Evidence of different
metabolic phenotypes in humans. Proc Natl Acad Sci U S A 2008;105(5):1420-4. (IF=9.771).
• Bernini P, Bertini I, Luchinat C, Nepi S, Saccenti E, Schäfer H, Schütz B, Spraul M, Tenori L.
Individual human phenotypes in metabolic space and time. J Proteome Res. 2009 Sep;8(9):4264-71.
(IF=5.460).
Cardiovascular diseases
•
Bernini P, Bertini I, Luchinat C, Tenori L, Tognaccini A. The cardiovascular risk of healthy individuals
studied by NMR metabonomics of plasma samples. J Proteome Res 2011. [Epub ahead of print]
(IF=5.460).
Celiac disease
•
Bernini P, Bertini I, Calabrò A, la Marca G, Lami G, Luchinat C, Renzi D, Tenori L. Are patients with
potential celiac disease really potential? The answer of metabonomics. J Proteome Res 2011 Feb
4;10(2):714-21. (IF=5.460).
Bertini I, Calabrò A, De Carli V, Luchinat C, Nepi S, Porfirio B, Renzi D, Saccenti E, Tenori L. The
metabonomic signature of celiac disease. J Proteome Res. 2009 Jan;8(1):170-7. (IF=5.460).
•
Ozono terapy
•
Travagli V, Zanardi I, Bernini P, Nepi S, Tenori L, Bocci V. Effects of ozone blood treatment on the
metabolite profile of human blood. Int J Toxicol 2010;29(2):165-74. (IF=1.762).
Metabolomics @CERM/CIRMMP
Breast cancer
•
Tenori L, Oakman C, Claudino WM, Bernini P, Cappadona S, Nepi S, Biganzoli L, Arbushites MC,
Luchinat C, Bertini I, Di Leo A. Exploration of serum metabolomic profiles and outcomes in women with
metastatic breast cancer: A pilot study. Mol Oncol. 2012 Jun 1. (IF=4.250).
Oakman C, Tenori L, Claudino WM, Cappadona S, Nepi S, Battaglia A, Bernini P, Zafarana E,
Saccenti E, Fornier M, Morris PG, Biganzoli L, Luchinat C, Bertini I, Di Leo A. Identification of a
serum-detectable metabolomic fingerprint potentially correlated with the presence of
micrometastatic disease in early breast cancer patients at varying risks of disease relapse by
traditional prognostic methods. Ann Oncol 2011 Jun;22(6):1295-301. (IF=6.452).
Oakman C, Tenori L, Biganzoli L, Santarpia L, Cappadona S, Luchinat C, Di Leo A. Uncovering the
metabolomic fingerprint of breast cancer. Int J Biochem Cell Biol 2011 Jul;43(7):1010-20. Review.
(IF=4.956).
Claudino WM, Quattrone A, Biganzoli L, Pestrin M, Bertini I, Di Leo A. Metabolomics: available
results, current research projects in breast cancer, and future applications. J Clin Oncol. 2007 Jul
1;25(19):2840-6. (IF=18.970).
Di Leo A, Claudino W, Colangiuli D, Bessi S, Pestrin M, Biganzoli L. New strategies to identify
molecular markers predicting chemotherapy activity and toxicity in breast cancer. Ann Oncol. 2007;18
Suppl 12:xii8-14. Review. (IF=6.452).
•
•
•
•
Colorectal Cancer
•
Bertini I, Cacciatore S, Jensen BV, Schou JV, Johansen JS, Kruhøffer M, Luchinat C, Nielsen DL,
Turano P. Metabolomic NMR fingerprinting to identify and predict survival of patients with metastatic
colorectal cancer. Cancer Res. 2012 Jan 1;72(1):356-64. (IF=8.234).
Metabolomics @CERM/CIRMMP
Peridontal diseases
•
Mario Aimetti, Stefano Cacciatore, Antonio Graziano and Leonardo Tenori. Metabonomic analysis of
saliva reveals generalized chronic periodontitis signature. Metabolomics; Online First™ (IF=3.608).
Standard Operating Procedures
•
Bernini P, Bertini I, Luchinat C, Nincheri P, Staderini S, Turano P. Standard operating procedures
for pre-analytical handling of blood and urine for metabolomic studies and biobanks. J Biomol NMR.
2011 Apr;49(3-4):231-43. (IF=3.047).
The future of medicine
•
Bertini I; Luchinat C; Tenori L. Metabolomics for the future of personalized medicine through
information and communication technologies. PERSONALIZED MEDICINE Volume: 9
Issue: 2
(IF=0.783).
Our interest in metabolomics
Metabolic signature of individuals:
Metabolic phenotype
Metabolic signature of diseases
• Coeliac disease
• tumor  metastasis
• heart failure, pulmonary diseases,etc…
Metabolites and biobank samples
• Sensitive reporters of stability
• Assess sample preparation and preanalytical procedures
• SOP
Metabolomics steps
Handling and
preparation of
samples
NMR analysis
Metabolites identification
Statistical analysis
Data processing and bucketing
BioBank Project
Collect
Store
Processing
Distribute
Biological samples for scientific research
The Future of Medicine
The need for individual metabolomic
screening
We are proposing to collect individual metabolomics
data for a large screening of the Tuscany population
The FiorGen
Foundation
How was FiorGen born
• FiorGen Foundation, a “non-profit organization of social
utility” (ONLUS), was founded in 2002, with the purpose of
favoring scientific, cultural and social development.
• FiorGen Foundation is the result of a strong link between
different scientific actors such as the Magnetic Resonance
Center (CERM) of the Scientific Campus of Sesto Fiorentino
and the Biomedical Campus of Careggi, which has been
supported by the Chamber of Commerce, Industry and
Handicrafts of Florence and the Ente Cassa di Risparmio of
Florence.
Governing Bodies
ADMINISTRATION COUNCIL SCIENTIFIC COMMITTEE
Vasco Galgani (President)
Calogero Surrenti (Vicepresident)
Gianni Amunni
Paolo Asso
Lucia Banci
Francesco Barbolla
Ivano Bertini
Gianfranco Gensini
Claudio Luchinat
Ivano Bertini (President)
Rosanna Abbate
Andrea Galli
Maurizio Genuardi
Cristina Nativi
Fund Raising
• Charity auction “Art and
Solidarity for the research”
CF: 94100210486
•
Campaign "Adopt a Researcher"
Communication
Newsletter FiorGenews
n. 1
n.2
n.3
n.4
Research Areas of FiorGen
Research Area 1: Bersagli e farmaci antitumorali
•Agonisti di recettori nucleari nella modulazione della crescita ed invasività
tumorale
•Delezione organo specifica del recettore ARP-1 in modelli murini
Research Area 2: Fisiopatologia e farmacogenetica delle malattie cardiovascolari
•Progetto Malattia Aneurismatica e Carotidea
•Progetto variabilità nella risposta alla terapia antiaggregante (aspirina e
clopidogrel)
Research Area 3: Origine malattie genetiche
•Studio delle basi genetiche della predisposizione a neoplasie umane
•Studi sull'origine della Sclerosi Laterale Amiotrofica
•Caratterizzazione strutturale della proteina beta amiloide coinvolta nel morbo di
Alzheimer
Research Area 4: Metabolomica
Research Area 5: BioBanca da Vinci European BioBank - daVEB
Research Area 6: Melanoma: nuovi possibili biomarcatori di diagnosi e
progressione