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

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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