Claudio LuchinatClaudio Luchinat
CERMCERMUniversità di FirenzeUniversità di Firenze
Centro Europeo di Centro Europeo di Risonanze MagneticheRisonanze Magnetiche
una infrastruttura di ricerca nel Polo una infrastruttura di ricerca nel Polo Scientifico dell’Università di FirenzeScientifico dell’Università di Firenze
Il Polo Scientifico di Sesto Fiorentino
800800700b700b
850ss850ss
700700
400400
500500
Bio-labsBio-labs
LibraryLibrary
700s700sss
900900
GENEXPRESS, CRYST, CISMGENEXPRESS, CRYST, CISM
Department Department of Chemistryof Chemistry(offices, bio-labs, (offices, bio-labs, relaxometer, instruments..)relaxometer, instruments..)
WorkshopWorkshop
Conference roomConference room
600b600b
The Magnetic Resonance Center in The Magnetic Resonance Center in FlorenceFlorence
Computer room Computer room 600600
DaVEB BiobankDaVEB Biobank
950950
NMR instrumentationCERM instrumentationCERM instrumentation
400 MHz400 MHz 600 MHz600 MHz
CryoCryo700 MHz (a)700 MHz (a)
CryoCryo700 MHz (b)700 MHz (b)
Cryo Cryo 500 MHz500 MHz
Cryo 900 MHzCryo 900 MHz
CryoCryo800 MHz800 MHz700 MHz WB700 MHz WB
850 MHz WB850 MHz WB
Cryo Cryo 600 MHz600 MHz
Cryo 950 MHzCryo 950 MHz
800800700b700b
850ss850ss
700700
400400
500500
Bio-labsBio-labs
LibraryLibrary
700s700sss
900900
GENEXPRESS, CRYST, CISMGENEXPRESS, CRYST, CISM
Department Department of Chemistryof Chemistry(offices, bio-labs, (offices, bio-labs, relaxometer, instruments..)relaxometer, instruments..)
WorkshopWorkshop
Conference roomConference room
600b600b
The Magnetic Resonance Center in The Magnetic Resonance Center in FlorenceFlorence
Computer room Computer room
Electron/nuclear relaxation (Relaxometry)Electron/nuclear relaxation (Relaxometry)Drug discoveryDrug discovery
Structural proteomicsStructural proteomicsMetabolomicsMetabolomics
Protein structure determinationProtein structure determinationMethodological advancements in NMRMethodological advancements in NMRSolid state NMRSolid state NMRICT and computational biologyICT and computational biology
600600
DaVEB BiobankDaVEB Biobank
We provide access to European researchers We provide access to European researchers since 1994since 1994New access program Bio-NMR (2010-2014) New access program Bio-NMR (2010-2014) started September 2010started September 2010Access provided by Florence, Frankfurt, Utrecht, Lyon/Grenoble, Access provided by Florence, Frankfurt, Utrecht, Lyon/Grenoble, Berlin, Zurich, Brno, Ljubljana, Oxford, Birmingham, GoteborgBerlin, Zurich, Brno, Ljubljana, Oxford, Birmingham, Goteborg
950950
Claudio LuchinatClaudio Luchinat
CERMCERMUniversità di FirenzeUniversità di Firenze
Metabolomica:Metabolomica:uno sguardo molecolare uno sguardo molecolare
sulla salute e sulle malattiesulla salute e sulle malattie
The Research Centers of FiorGenThe Research Centers of FiorGen
CERMScientific CampusSesto Fiorentino
Biomedical CampusCareggi
Scientific PublicationsScientific Publications146 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”The scientific production of FiorGen is quite impressive”Prof. Arturo Falaschi
Scuola Normale Superiore – PisaDistinguished Scientist ICGEB Trieste
Aprile 2008
““The scientific productivity of FiorGen is of excellent level”The scientific productivity of FiorGen is of excellent level”Prof. Giuseppe Novelli
Tor Vergata University of RomeUniversity 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)
H2N
O
OH
Glycine
NH2
NH
O
OH
Tryptophan
NH2
HN
NH
H2N
O
OH
Arginine
OHHO
ONN
H2N
N
N
PO
O
OH
O
P
O
OH
O
PO
OH
OH
Adenosine-5'-triphosphate
Acetyl CoA
ExamplesExamples of of metabolitesmetabolites
O
O
OH
Pyruvic acid
O
OH
O
HO
Succinic acid
O
O
HO
O
OH
Oxaloacetic acid
Study of small molecules in biological fluids
+
MetabolomicsMetabolomics
Metabolic fingerprint
11H NMR spectrum of ethanolH NMR spectrum of ethanol
C C
H
H
HH
H
HO__
||
| | ____ __
1H NMR spectrum (upfield part) of human urine1H NMR spectrum (upfield part) of human urine
1H NMR spectrum 1H NMR spectrum (downfield part)(downfield part) of human urineof human urine
1234567ppm
hippurate urea
allantoin creatininehippurate
2-oxoglutarate
citrate
TMAO
succinatefumarate
water
creatinine
taurine
1234567ppm
-25-20-15-10-505
10152025
-30 -20 -10 0 10
PC1
PC2
Quantitativemethods
Chemometric methods(fingerprinting and pattern recognition)
Two approaches:Two approaches:• Identify as many metabolites as possibleIdentify as many metabolites as possible• Use the whole spectrum as a fingerprint (statistics)Use the whole spectrum as a fingerprint (statistics)
2 Routes to Metabolomics2 Routes to Metabolomics
The fingerprintThe fingerprint
Few already known metabolites for
some disease (e.g. glucose for diabetes,
etc…)
Metabolomics:Traditional clinical analysis:
All metabolites are analyzed together
without prior knowledge
The fingerprintThe fingerprint
What are they doing ?
The fingerprintThe fingerprint
Only an analysis at a global level can tell the whole story
Ind 1
Ind 2
10.00 7.50 5.00 2.50 ppm
METabolomic REFerenceMETabolomic REFerence
Ind 1
Ind 2
10.00 7.50 5.00 2.50 ppm
METabolomic REFerenceMETabolomic REFerence
METabolomic REFerenceMETabolomic REFerenceConvex hulls of 22 donors in the three most significant PCA-CA dimensionsConvex hulls of 22 donors in the three most significant PCA-CA dimensions
Assfalg, Bertini, Colangiuli, Luchinat, SchAssfalg, Bertini, Colangiuli, Luchinat, Schääfer, Schfer, Schüütz, Spraul, tz, Spraul, PNASPNAS, , 20082008, 105, 1420-4, 105, 1420-4
PCA for data PCA for data reduction reduction
CA for CA for obtainobtain well separated well separated clustersclusters
KNN for KNN for classificationclassification
99% accuracy 99% accuracy in montecarlo in montecarlo cross validationcross validation
““natural” gender discriminationnatural” gender discrimination
MALEMALEFEMALEFEMALE
Bernini, P.; Bertini, I.; Luchinat, C.; Nepi, S.; Saccenti, E.; Schäfer, H.; Schütz, B.; Spraul, M.; Tenori, L. J. Prot. Res. 2009
• 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, SchAssfalg, Bertini, Colangiuli, Luchinat, Schääfer, Schfer, Schüütz, Spraul, tz, Spraul, PNASPNAS, , 20082008
The signature of Our BodyThe signature of Our Body
Metabolomics @CERM/CIRMMPMetabolomics @CERM/CIRMMPCollaborative 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+) 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/CIRMMPMetabolomics @CERM/CIRMMPCollaborations•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 MetabolomicsCeliac 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 MetabolomicsCeliac Disease Metabolomics
Clusterization of Celiac and Healthy subject serum spectraand 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 diseaseCeliac disease
Celiac – Healthy Subjects – Cross: predicted Potential Celiac
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
There exist a metabolic fingerprint of celiac disease
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 CDBertini, 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
http://www.fiorgen.net/ https://www. davincieuropeanbiobank.org
Breast cancer metabolomicsBreast cancer metabolomics
Healthy vs Met
Accuracy 73.44%
Healthy vsPost-op
Accuracy 75.80%
Post vs Met
Accuracy 74.96%
NOESY
Healthy vsMet
Accuracy 72.67%
Healthy vsPost-op
Accuracy 70.00%
Post-op vsMet
Accuracy 70.00%
CPMG
Classification between Pre-Op and Metastatic subjects.
Accuracy ~80%
Other comparisons
Colorectal Cancer MetabolomicsColorectal Cancer Metabolomics
Cross-validated results on the Training Set:
Sensitivity : 79.9%Specificity: 76.4% Accuracy: 78.5%
Univariate Cox Regression Analysis for the Validation Set:
HR: 3.3095% CI: 2.02 to 5.37P: 1.75 ∙ 10-6
PLS-CA model: long survival, in blue; short survival, in yellow
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
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
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%
Classification between different subgroups of Heart failure patients (1D CPMG spectra).
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.
Heart failure metabolomics
Patients vs Healthy 85.11% 91.04% 87.29%
Metabolomics of MelanomaMetabolomics 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 ObesityFingerprint of Obesity
Fingerprint of obesity
NW vs SONW vs SO 94.094.0
OW vs SOOW vs SO 79.679.6
NW vs OWNW vs OW 69.769.7
NW vs OW+SONW vs OW+SO 87.887.8
NW+OW vs SONW+OW vs SO 84.184.1
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 sanoSpettro NMR di urina di un donatore sano FROM METABOLOMICS
Metabolomic analysis
Validation of sample quality
in biobanks
Definition of new SOPs
TO BIOBANKS
Dalla Metabolomica
Analisi Metabolomica
Controllo Qualità di campioni
Nelle biobanche
Definizione di
Nuove SOP
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. Scompenso cardiaco (Prof. Gianfranco Gensini)2. Melanoma (Prof. Nicola Pimpinelli)3. Cancro alla mammella (Prof. Angelo Di Leo, e USA)4. Cancro al colon (Prof. Benny V. Jensen, Danimarca)5. Disturbi alla prostata (Prof. Marco Carini)6. Celiachia (Prof. Antonio Calabrò)7. Osteoporosi (Prof.ssa Maria Luisa Brandi)
http://www.fiorgen.net/ https://www. davincieuropeanbiobank.org
The Future of MedicineThe Future of Medicine
Metabolomics can monitor the same individual in a multidimensional space
Intestinal bowel disease
Hypertension
hepatocarcinoma
steatosis
cirrhosis
Diabetes
Metabolic syndrome
Colorectal cancer
Hearth Failure
Healthy aging
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 MedicineThe Future of Medicine
From general to personalized medicine
Ivano Bertini
December 6, 1940– July 7, 2012
Metabolomics @CERM/CIRMMPMetabolomics @CERM/CIRMMPMetabolomics 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/CIRMMPMetabolomics @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/CIRMMPMetabolomics @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).
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
Our interest in metabolomicsOur interest in metabolomics
NMR analysis
Metabolites identification
Data processing and bucketingStatistical analysis
Handling and preparation of
samples
Metabolomics steps
Collect Store Processing
Distribute
Biological samples for scientific research
BioBank ProjectBioBank Project
The Future of MedicineThe 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 The FiorGen FoundationFoundation
• 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.
How was FiorGen bornHow was FiorGen born
ADMINISTRATION COUNCIL
Vasco Galgani (President)
Calogero Surrenti (Vicepresident)
Gianni Amunni
Paolo Asso
Lucia Banci
Francesco Barbolla
Ivano Bertini
Gianfranco Gensini
Claudio Luchinat
SCIENTIFIC COMMITTEE
Ivano Bertini (President)
Rosanna Abbate
Andrea Galli
Maurizio Genuardi
Cristina Nativi
Governing BodiesGoverning Bodies
• Charity auction “Art and Solidarity for the research”
• Campaign "Adopt a Researcher"
Fund RaisingFund Raising
CF: 94100210486
n. 1 n.2 n.3 n.4
CommunicationCommunication
Newsletter FiorGenews
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
Research Areas of FiorGenResearch Areas of FiorGen
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